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76 results (BibTeX)

2000

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Knowledge Discovery in Databases: An Information Retrieval Perspective

Ong, CS.

Malaysian Journal of Computer Science, 13(2):54-63, December 2000 (article)

Abstract
The current trend of increasing capabilities in data generation and collection has resulted in an urgent need for data mining applications, also called knowledge discovery in databases. This paper identifies and examines the issues involved in extracting useful grains of knowledge from large amounts of data. It describes a framework to categorise data mining systems. The author also gives an overview of the issues pertaining to data pre processing, as well as various information gathering methodologies and techniques. The paper covers some popular tools such as classification, clustering, and generalisation. A summary of statistical and machine learning techniques used currently is also provided.

ei

PDF [BibTex]

2000

ei Ong, CS. Knowledge Discovery in Databases: An Information Retrieval Perspective Malaysian Journal of Computer Science, 13(2):54-63, December 2000 (article)

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A real-time model of the human knee for application in virtual orthopaedic trainer

Peters, J., Riener, R.

In Proceedings of the 10th International Conference on BioMedical Engineering (ICBME 2000), 10, pages: 1-2, 10th International Conference on BioMedical Engineering (ICBME) , December 2000 (inproceedings)

Abstract
In this paper a real-time capable computational model of the human knee is presented. The model describes the passive elastic joint characteristics in six degrees-of-freedom (DOF). A black-box approach was chosen, where experimental data were approximated by piecewise polynomial functions. The knee model has been applied in a the Virtual Orthopaedic Trainer, which can support training of physical knee evaluation required for diagnosis and surgical planning.

ei

PDF Web [BibTex]

ei Peters, J., Riener, R. A real-time model of the human knee for application in virtual orthopaedic trainer In Proceedings of the 10th International Conference on BioMedical Engineering (ICBME 2000), 10, pages: 1-2, 10th International Conference on BioMedical Engineering (ICBME) , December 2000 (inproceedings)

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Reciprocal excitation between biological and robotic research

Schaal, S., Sternad, D., Dean, W., Kotoska, S., Osu, R., Kawato, M.

In Sensor Fusion and Decentralized Control in Robotic Systems III, Proceedings of SPIE, 4196, pages: 30-40, Boston, MA, Nov.5-8, 2000, November 2000, clmc (inproceedings)

Abstract
While biological principles have inspired researchers in computational and engineering research for a long time, there is still rather limited knowledge flow back from computational to biological domains. This paper presents examples of our work where research on anthropomorphic robots lead us to new insights into explaining biological movement phenomena, starting from behavioral studies up to brain imaging studies. Our research over the past years has focused on principles of trajectory formation with nonlinear dynamical systems, on learning internal models for nonlinear control, and on advanced topics like imitation learning. The formal and empirical analyses of the kinematics and dynamics of movements systems and the tasks that they need to perform lead us to suggest principles of motor control that later on we found surprisingly related to human behavior and even brain activity.

am

link (url) [BibTex]

am Schaal, S., Sternad, D., Dean, W., Kotoska, S., Osu, R., Kawato, M. Reciprocal excitation between biological and robotic research In Sensor Fusion and Decentralized Control in Robotic Systems III, Proceedings of SPIE, 4196, pages: 30-40, Boston, MA, Nov.5-8, 2000, November 2000, clmc (inproceedings)

link (url) [BibTex]

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A Simple Iterative Approach to Parameter Optimization

Zien, A., Zimmer, R., Lengauer, T.

Journal of Computational Biology, 7(3,4):483-501, November 2000 (article)

Abstract
Various bioinformatics problems require optimizing several different properties simultaneously. For example, in the protein threading problem, a scoring function combines the values for different parameters of possible sequence-to-structure alignments into a single score to allow for unambiguous optimization. In this context, an essential question is how each property should be weighted. As the native structures are known for some sequences, a partial ordering on optimal alignments to other structures, e.g., derived from structural comparisons, may be used to adjust the weights. To resolve the arising interdependence of weights and computed solutions, we propose a heuristic approach: iterating the computation of solutions (here, threading alignments) given the weights and the estimation of optimal weights of the scoring function given these solutions via systematic calibration methods. For our application (i.e., threading), this iterative approach results in structurally meaningful weights that significantly improve performance on both the training and the test data sets. In addition, the optimized parameters show significant improvements on the recognition rate for a grossly enlarged comprehensive benchmark, a modified recognition protocol as well as modified alignment types (local instead of global and profiles instead of single sequences). These results show the general validity of the optimized weights for the given threading program and the associated scoring contributions.

ei

Web [BibTex]

ei Zien, A., Zimmer, R., Lengauer, T. A Simple Iterative Approach to Parameter Optimization Journal of Computational Biology, 7(3,4):483-501, November 2000 (article)

Web [BibTex]

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Identification of Drug Target Proteins

Zien, A., Küffner, R., Mevissen, T., Zimmer, R., Lengauer, T.

ERCIM News, 43, pages: 16-17, October 2000 (article)

ei

Web [BibTex]

ei Zien, A., Küffner, R., Mevissen, T., Zimmer, R., Lengauer, T. Identification of Drug Target Proteins ERCIM News, 43, pages: 16-17, October 2000 (article)

Web [BibTex]

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On Designing an Automated Malaysian Stemmer for the Malay Language

Tai, SY., Ong, CS., Abullah, NA.

In Fifth International Workshop on Information Retrieval with Asian Languages, pages: 207-208, ACM Press, New York, NY, USA, Fifth International Workshop on Information Retrieval with Asian Languages, October 2000 (inproceedings)

Abstract
Online and interactive information retrieval systems are likely to play an increasing role in the Malay Language community. To facilitate and automate the process of matching morphological term variants, a stemmer focusing on common affix removal algorithms is proposed as part of the design of an information retrieval system for the Malay Language. Stemming is a morphological process of normalizing word tokens down to their essential roots. The proposed stemmer strips prefixes and suffixes off the word. The experiment conducted with web sites selected from the World Wide Web has exhibited substantial improvements in the number of words indexed.

ei

PostScript Web DOI [BibTex]

ei Tai, SY., Ong, CS., Abullah, NA. On Designing an Automated Malaysian Stemmer for the Malay Language In Fifth International Workshop on Information Retrieval with Asian Languages, pages: 207-208, ACM Press, New York, NY, USA, Fifth International Workshop on Information Retrieval with Asian Languages, October 2000 (inproceedings)

PostScript Web DOI [BibTex]

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Robust ensemble learning

Rätsch, G., Schölkopf, B., Smola, A., Mika, S., Onoda, T., Müller, K.

In Advances in Large Margin Classifiers, pages: 207-220, Neural Information Processing Series, (Editors: AJ Smola and PJ Bartlett and B Schölkopf and D. Schuurmans), MIT Press, Cambridge, MA, USA, October 2000 (inbook)

ei

[BibTex]

ei Rätsch, G., Schölkopf, B., Smola, A., Mika, S., Onoda, T., Müller, K. Robust ensemble learning In Advances in Large Margin Classifiers, pages: 207-220, Neural Information Processing Series, (Editors: AJ Smola and PJ Bartlett and B Schölkopf and D. Schuurmans), MIT Press, Cambridge, MA, USA, October 2000 (inbook)

[BibTex]

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Entropy numbers for convex combinations and MLPs

Smola, A., Elisseeff, A., Schölkopf, B., Williamson, R.

In Advances in Large Margin Classifiers, pages: 369-387, Neural Information Processing Series, (Editors: AJ Smola and PL Bartlett and B Schölkopf and D Schuurmans), MIT Press, Cambridge, MA,, October 2000 (inbook)

ei

[BibTex]

ei Smola, A., Elisseeff, A., Schölkopf, B., Williamson, R. Entropy numbers for convex combinations and MLPs In Advances in Large Margin Classifiers, pages: 369-387, Neural Information Processing Series, (Editors: AJ Smola and PL Bartlett and B Schölkopf and D Schuurmans), MIT Press, Cambridge, MA,, October 2000 (inbook)

[BibTex]

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Advances in Large Margin Classifiers

Smola, A., Bartlett, P., Schölkopf, B., Schuurmans, D.

pages: 422, Neural Information Processing, MIT Press, Cambridge, MA, USA, October 2000 (book)

Abstract
The concept of large margins is a unifying principle for the analysis of many different approaches to the classification of data from examples, including boosting, mathematical programming, neural networks, and support vector machines. The fact that it is the margin, or confidence level, of a classification--that is, a scale parameter--rather than a raw training error that matters has become a key tool for dealing with classifiers. This book shows how this idea applies to both the theoretical analysis and the design of algorithms. The book provides an overview of recent developments in large margin classifiers, examines connections with other methods (e.g., Bayesian inference), and identifies strengths and weaknesses of the method, as well as directions for future research. Among the contributors are Manfred Opper, Vladimir Vapnik, and Grace Wahba.

ei

Web [BibTex]

ei Smola, A., Bartlett, P., Schölkopf, B., Schuurmans, D. Advances in Large Margin Classifiers pages: 422, Neural Information Processing, MIT Press, Cambridge, MA, USA, October 2000 (book)

Web [BibTex]

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Ensemble of Specialized Networks based on Input Space Partition

Shin, H., Lee, H., Cho, S.

In Proc. of the Korean Operations Research and Management Science Conference, pages: 33-36, Korean Operations Research and Management Science Conference, October 2000 (inproceedings)

ei

[BibTex]

ei Shin, H., Lee, H., Cho, S. Ensemble of Specialized Networks based on Input Space Partition In Proc. of the Korean Operations Research and Management Science Conference, pages: 33-36, Korean Operations Research and Management Science Conference, October 2000 (inproceedings)

[BibTex]

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DES Approach Failure Recovery of Pump-valve System

Son, HI., Kim, KW., Lee, S.

In Korean Society of Precision Engineering (KSPE) Conference, pages: 647-650, Annual Meeting of the Korean Society of Precision Engineering (KSPE), October 2000 (inproceedings)

ei

PDF [BibTex]

ei Son, HI., Kim, KW., Lee, S. DES Approach Failure Recovery of Pump-valve System In Korean Society of Precision Engineering (KSPE) Conference, pages: 647-650, Annual Meeting of the Korean Society of Precision Engineering (KSPE), October 2000 (inproceedings)

PDF [BibTex]

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Natural Regularization from Generative Models

Oliver, N., Schölkopf, B., Smola, A.

In Advances in Large Margin Classifiers, pages: 51-60, Neural Information Processing Series, (Editors: AJ Smola and PJ Bartlett and B Schölkopf and D Schuurmans), MIT Press, Cambridge, MA, USA, October 2000 (inbook)

ei

[BibTex]

ei Oliver, N., Schölkopf, B., Smola, A. Natural Regularization from Generative Models In Advances in Large Margin Classifiers, pages: 51-60, Neural Information Processing Series, (Editors: AJ Smola and PJ Bartlett and B Schölkopf and D Schuurmans), MIT Press, Cambridge, MA, USA, October 2000 (inbook)

[BibTex]

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Ensemble Learning Algorithm of Specialized Networks

Shin, H., Lee, H., Cho, S.

In Proc. of the Korea Information Science Conference, pages: 308-310, Korea Information Science Conference, October 2000 (inproceedings)

ei

[BibTex]

ei Shin, H., Lee, H., Cho, S. Ensemble Learning Algorithm of Specialized Networks In Proc. of the Korea Information Science Conference, pages: 308-310, Korea Information Science Conference, October 2000 (inproceedings)

[BibTex]

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DES Approach Failure Diagnosis of Pump-valve System

Son, HI., Kim, KW., Lee, S.

In Korean Society of Precision Engineering (KSPE) Conference, pages: 643-646, Annual Meeting of the Korean Society of Precision Engineering (KSPE), October 2000 (inproceedings)

Abstract
As many industrial systems become more complex, it becomes extremely difficult to diagnose the cause of failures. This paper presents a failure diagnosis approach based on discrete event system theory. In particular, the approach is a hybrid of event-based and state-based ones leading to a simpler failure diagnoser with supervisory control capability. The design procedure is presented along with a pump-valve system as an example.

ei

PDF [BibTex]

ei Son, HI., Kim, KW., Lee, S. DES Approach Failure Diagnosis of Pump-valve System In Korean Society of Precision Engineering (KSPE) Conference, pages: 643-646, Annual Meeting of the Korean Society of Precision Engineering (KSPE), October 2000 (inproceedings)

PDF [BibTex]

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Nonlinear dynamical systems as movement primitives

Schaal, S., Kotosaka, S., Sternad, D.

In Humanoids2000, First IEEE-RAS International Conference on Humanoid Robots, CD-Proceedings, Cambridge, MA, September 2000, clmc (inproceedings)

Abstract
This paper explores the idea to create complex human-like movements from movement primitives based on nonlinear attractor dynamics. Each degree-of-freedom of a limb is assumed to have two independent abilities to create movement, one through a discrete dynamic system, and one through a rhythmic system. The discrete system creates point-to-point movements based on internal or external target specifications. The rhythmic system can add an additional oscillatory movement relative to the current position of the discrete system. In the present study, we develop appropriate dynamic systems that can realize the above model, motivate the particular choice of the systems from a biological and engineering point of view, and present simulation results of the performance of such movement primitives. The model was implemented for a drumming task on a humanoid robot

am

link (url) [BibTex]

am Schaal, S., Kotosaka, S., Sternad, D. Nonlinear dynamical systems as movement primitives In Humanoids2000, First IEEE-RAS International Conference on Humanoid Robots, CD-Proceedings, Cambridge, MA, September 2000, clmc (inproceedings)

link (url) [BibTex]

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Real Time Learning in Humanoids: A challenge for scalability of Online Algorithms

Vijayakumar, S., Schaal, S.

In Humanoids2000, First IEEE-RAS International Conference on Humanoid Robots, CD-Proceedings, Cambridge, MA, September 2000, clmc (inproceedings)

Abstract
While recent research in neural networks and statistical learning has focused mostly on learning from finite data sets without stringent constraints on computational efficiency, there is an increasing number of learning problems that require real-time performance from an essentially infinite stream of incrementally arriving data. This paper demonstrates how even high-dimensional learning problems of this kind can successfully be dealt with by techniques from nonparametric regression and locally weighted learning. As an example, we describe the application of one of the most advanced of such algorithms, Locally Weighted Projection Regression (LWPR), to the on-line learning of the inverse dynamics model of an actual seven degree-of-freedom anthropomorphic robot arm. LWPR's linear computational complexity in the number of input dimensions, its inherent mechanisms of local dimensionality reduction, and its sound learning rule based on incremental stochastic leave-one-out cross validation allows -- to our knowledge for the first time -- implementing inverse dynamics learning for such a complex robot with real-time performance. In our sample task, the robot acquires the local inverse dynamics model needed to trace a figure-8 in only 60 seconds of training.

am

link (url) [BibTex]

am Vijayakumar, S., Schaal, S. Real Time Learning in Humanoids: A challenge for scalability of Online Algorithms In Humanoids2000, First IEEE-RAS International Conference on Humanoid Robots, CD-Proceedings, Cambridge, MA, September 2000, clmc (inproceedings)

link (url) [BibTex]

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Engineering Support Vector Machine Kernels That Recognize Translation Initiation Sites

Zien, A., Rätsch, G., Mika, S., Schölkopf, B., Lengauer, T., Müller, K.

Bioinformatics, 16(9):799-807, September 2000 (article)

Abstract
Motivation: In order to extract protein sequences from nucleotide sequences, it is an important step to recognize points at which regions start that code for proteins. These points are called translation initiation sites (TIS). Results: The task of finding TIS can be modeled as a classification problem. We demonstrate the applicability of support vector machines for this task, and show how to incorporate prior biological knowledge by engineering an appropriate kernel function. With the described techniques the recognition performance can be improved by 26% over leading existing approaches. We provide evidence that existing related methods (e.g. ESTScan) could profit from advanced TIS recognition.

ei

Web DOI [BibTex]

ei Zien, A., Rätsch, G., Mika, S., Schölkopf, B., Lengauer, T., Müller, K. Engineering Support Vector Machine Kernels That Recognize Translation Initiation Sites Bioinformatics, 16(9):799-807, September 2000 (article)

Web DOI [BibTex]

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Three-dimensional reconstruction of planar scenes

Urbanek, M.

Biologische Kybernetik, INP Grenoble, Warsaw University of Technology, September 2000 (diplomathesis)

Abstract
For a planar scene, we propose an algorithm to estimate its 3D structure. Homographies between corresponding planes are employed in order to recover camera motion parameters - between camera positions from which images of the scene were taken. Cases of one- and multiple- corresponding planes present on the scene are distinguished. Solutions are proposed for both cases.

ei

ZIP [BibTex]

ei Urbanek, M. Three-dimensional reconstruction of planar scenes Biologische Kybernetik, INP Grenoble, Warsaw University of Technology, September 2000 (diplomathesis)

ZIP [BibTex]

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Synchronized robot drumming by neural oscillator

Kotosaka, S., Schaal, S.

In The International Symposium on Adaptive Motion of Animals and Machines, Montreal, Canada, August 2000, clmc (inproceedings)

Abstract
Sensory-motor integration is one of the key issues in robotics. In this paper, we propose an approach to rhythmic arm movement control that is synchronized with an external signal based on exploiting a simple neural oscillator network. Trajectory generation by the neural oscillator is a biologically inspired method that can allow us to generate a smooth and continuous trajectory. The parameter tuning of the oscillators is used to generate a synchronized movement with wide intervals. We adopted the method for the drumming task as an example task. By using this method, the robot can realize synchronized drumming with wide drumming intervals in real time. The paper also shows the experimental results of drumming by a humanoid robot.

am

link (url) [BibTex]

am Kotosaka, S., Schaal, S. Synchronized robot drumming by neural oscillator In The International Symposium on Adaptive Motion of Animals and Machines, Montreal, Canada, August 2000, clmc (inproceedings)

link (url) [BibTex]

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Analysis of Gene Expression Data with Pathway Scores

Zien, A., Küffner, R., Zimmer, R., Lengauer, T.

In ISMB 2000, pages: 407-417, AAAI Press, Menlo Park, CA, USA, 8th International Conference on Intelligent Systems for Molecular Biology, August 2000 (inproceedings)

Abstract
We present a new approach for the evaluation of gene expression data. The basic idea is to generate biologically possible pathways and to score them with respect to gene expression measurements. We suggest sample scoring functions for different problem specifications. The significance of the scores for the investigated pathways is assessed by comparison to a number of scores for random pathways. We show that simple scoring functions can assign statistically significant scores to biologically relevant pathways. This suggests that the combination of appropriate scoring functions with the systematic generation of pathways can be used in order to select the most interesting pathways based on gene expression measurements.

ei

PDF [BibTex]

ei Zien, A., Küffner, R., Zimmer, R., Lengauer, T. Analysis of Gene Expression Data with Pathway Scores In ISMB 2000, pages: 407-417, AAAI Press, Menlo Park, CA, USA, 8th International Conference on Intelligent Systems for Molecular Biology, August 2000 (inproceedings)

PDF [BibTex]

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A Meanfield Approach to the Thermodynamics of a Protein-Solvent System with Application to the Oligomerization of the Tumour Suppressor p53.

Noolandi, J., Davison, TS., Vokel, A., Nie, F., Kay, C., Arrowsmith, C.

Proceedings of the National Academy of Sciences of the United States of America, 97(18):9955-9960, August 2000 (article)

ei

Web [BibTex]

ei Noolandi, J., Davison, TS., Vokel, A., Nie, F., Kay, C., Arrowsmith, C. A Meanfield Approach to the Thermodynamics of a Protein-Solvent System with Application to the Oligomerization of the Tumour Suppressor p53. Proceedings of the National Academy of Sciences of the United States of America, 97(18):9955-9960, August 2000 (article)

Web [BibTex]

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Observational Learning with Modular Networks

Shin, H., Lee, H., Cho, S.

In Lecture Notes in Computer Science (LNCS 1983), LNCS 1983, pages: 126-132, Springer-Verlag, Heidelberg, International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), July 2000 (inproceedings)

Abstract
Observational learning algorithm is an ensemble algorithm where each network is initially trained with a bootstrapped data set and virtual data are generated from the ensemble for training. Here we propose a modular OLA approach where the original training set is partitioned into clusters and then each network is instead trained with one of the clusters. Networks are combined with different weighting factors now that are inversely proportional to the distance from the input vector to the cluster centers. Comparison with bagging and boosting shows that the proposed approach reduces generalization error with a smaller number of networks employed.

ei

PDF [BibTex]

ei Shin, H., Lee, H., Cho, S. Observational Learning with Modular Networks In Lecture Notes in Computer Science (LNCS 1983), LNCS 1983, pages: 126-132, Springer-Verlag, Heidelberg, International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), July 2000 (inproceedings)

PDF [BibTex]

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Probabilistic detection and tracking of motion boundaries

Black, M. J., Fleet, D. J.

Int. J. of Computer Vision, 38(3):231-245, July 2000 (article)

Abstract
We propose a Bayesian framework for representing and recognizing local image motion in terms of two basic models: translational motion and motion boundaries. Motion boundaries are represented using a non-linear generative model that explicitly encodes the orientation of the boundary, the velocities on either side, the motion of the occluding edge over time, and the appearance/disappearance of pixels at the boundary. We represent the posterior probability distribution over the model parameters given the image data using discrete samples. This distribution is propagated over time using a particle filtering algorithm. To efficiently represent such a high-dimensional space we initialize samples using the responses of a low-level motion discontinuity detector. The formulation and computational model provide a general probabilistic framework for motion estimation with multiple, non-linear, models.

ps

pdf pdf from publisher Video [BibTex]

ps Black, M. J., Fleet, D. J. Probabilistic detection and tracking of motion boundaries Int. J. of Computer Vision, 38(3):231-245, July 2000 (article)

pdf pdf from publisher Video [BibTex]

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The Infinite Gaussian Mixture Model

Rasmussen, CE.

In Advances in Neural Information Processing Systems 12, pages: 554-560, (Editors: Solla, S.A. , T.K. Leen, K-R Müller), MIT Press, Cambridge, MA, USA, Thirteenth Annual Neural Information Processing Systems Conference (NIPS), June 2000 (inproceedings)

Abstract
In a Bayesian mixture model it is not necessary a priori to limit the number of components to be finite. In this paper an infinite Gaussian mixture model is presented which neatly sidesteps the difficult problem of finding the ``right'' number of mixture components. Inference in the model is done using an efficient parameter-free Markov Chain that relies entirely on Gibbs sampling.

ei

PDF Web [BibTex]

ei Rasmussen, CE. The Infinite Gaussian Mixture Model In Advances in Neural Information Processing Systems 12, pages: 554-560, (Editors: Solla, S.A. , T.K. Leen, K-R Müller), MIT Press, Cambridge, MA, USA, Thirteenth Annual Neural Information Processing Systems Conference (NIPS), June 2000 (inproceedings)

PDF Web [BibTex]

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Generalization Abilities of Ensemble Learning Algorithms

Shin, H., Jang, M., Cho, S.

In Proc. of the Korean Brain Society Conference, pages: 129-133, Korean Brain Society Conference, June 2000 (inproceedings)

ei

[BibTex]

ei Shin, H., Jang, M., Cho, S. Generalization Abilities of Ensemble Learning Algorithms In Proc. of the Korean Brain Society Conference, pages: 129-133, Korean Brain Society Conference, June 2000 (inproceedings)

[BibTex]

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Support vector method for novelty detection

Schölkopf, B., Williamson, R., Smola, A., Shawe-Taylor, J., Platt, J.

In Advances in Neural Information Processing Systems 12, pages: 582-588, (Editors: SA Solla and TK Leen and K-R Müller), MIT Press, Cambridge, MA, USA, 13th Annual Neural Information Processing Systems Conference (NIPS), June 2000 (inproceedings)

Abstract
Suppose you are given some dataset drawn from an underlying probability distribution ¤ and you want to estimate a “simple” subset ¥ of input space such that the probability that a test point drawn from ¤ lies outside of ¥ equals some a priori specified ¦ between § and ¨. We propose a method to approach this problem by trying to estimate a function © which is positive on ¥ and negative on the complement. The functional form of © is given by a kernel expansion in terms of a potentially small subset of the training data; it is regularized by controlling the length of the weight vector in an associated feature space. We provide a theoretical analysis of the statistical performance of our algorithm. The algorithm is a natural extension of the support vector algorithm to the case of unlabelled data.

ei

PDF Web [BibTex]

ei Schölkopf, B., Williamson, R., Smola, A., Shawe-Taylor, J., Platt, J. Support vector method for novelty detection In Advances in Neural Information Processing Systems 12, pages: 582-588, (Editors: SA Solla and TK Leen and K-R Müller), MIT Press, Cambridge, MA, USA, 13th Annual Neural Information Processing Systems Conference (NIPS), June 2000 (inproceedings)

PDF Web [BibTex]

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Solving Satisfiability Problems with Genetic Algorithms

Harmeling, S.

In Genetic Algorithms and Genetic Programming at Stanford 2000, pages: 206-213, (Editors: Koza, J. R.), Stanford Bookstore, Stanford, CA, USA, June 2000 (inbook)

Abstract
We show how to solve hard 3-SAT problems using genetic algorithms. Furthermore, we explore other genetic operators that may be useful to tackle 3-SAT problems, and discuss their pros and cons.

ei

PDF [BibTex]

ei Harmeling, S. Solving Satisfiability Problems with Genetic Algorithms In Genetic Algorithms and Genetic Programming at Stanford 2000, pages: 206-213, (Editors: Koza, J. R.), Stanford Bookstore, Stanford, CA, USA, June 2000 (inbook)

PDF [BibTex]

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v-Arc: Ensemble Learning in the Presence of Outliers

Rätsch, G., Schölkopf, B., Smola, A., Müller, K., Onoda, T., Mika, S.

In Advances in Neural Information Processing Systems 12, pages: 561-567, (Editors: SA Solla and TK Leen and K-R Müller), MIT Press, Cambridge, MA, USA, 13th Annual Neural Information Processing Systems Conference (NIPS), June 2000 (inproceedings)

Abstract
AdaBoost and other ensemble methods have successfully been applied to a number of classification tasks, seemingly defying problems of overfitting. AdaBoost performs gradient descent in an error function with respect to the margin, asymptotically concentrating on the patterns which are hardest to learn. For very noisy problems, however, this can be disadvantageous. Indeed, theoretical analysis has shown that the margin distribution, as opposed to just the minimal margin, plays a crucial role in understanding this phenomenon. Loosely speaking, some outliers should be tolerated if this has the benefit of substantially increasing the margin on the remaining points. We propose a new boosting algorithm which allows for the possibility of a pre-specified fraction of points to lie in the margin area or even on the wrong side of the decision boundary.

ei

PDF Web [BibTex]

ei Rätsch, G., Schölkopf, B., Smola, A., Müller, K., Onoda, T., Mika, S. v-Arc: Ensemble Learning in the Presence of Outliers In Advances in Neural Information Processing Systems 12, pages: 561-567, (Editors: SA Solla and TK Leen and K-R Müller), MIT Press, Cambridge, MA, USA, 13th Annual Neural Information Processing Systems Conference (NIPS), June 2000 (inproceedings)

PDF Web [BibTex]

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Transductive Inference for Estimating Values of Functions

Chapelle, O., Vapnik, V., Weston, J.

In Advances in Neural Information Processing Systems 12, pages: 421-427, (Editors: Solla, S.A. , T.K. Leen, K-R Müller), MIT Press, Cambridge, MA, USA, Thirteenth Annual Neural Information Processing Systems Conference (NIPS), June 2000 (inproceedings)

Abstract
We introduce an algorithm for estimating the values of a function at a set of test points $x_1^*,dots,x^*_m$ given a set of training points $(x_1,y_1),dots,(x_ell,y_ell)$ without estimating (as an intermediate step) the regression function. We demonstrate that this direct (transductive) way for estimating values of the regression (or classification in pattern recognition) is more accurate than the traditional one based on two steps, first estimating the function and then calculating the values of this function at the points of interest.

ei

PDF Web [BibTex]

ei Chapelle, O., Vapnik, V., Weston, J. Transductive Inference for Estimating Values of Functions In Advances in Neural Information Processing Systems 12, pages: 421-427, (Editors: Solla, S.A. , T.K. Leen, K-R Müller), MIT Press, Cambridge, MA, USA, Thirteenth Annual Neural Information Processing Systems Conference (NIPS), June 2000 (inproceedings)

PDF Web [BibTex]

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Invariant feature extraction and classification in kernel spaces

Mika, S., Rätsch, G., Weston, J., Schölkopf, B., Smola, A., Müller, K.

In Advances in neural information processing systems 12, pages: 526-532, (Editors: SA Solla and TK Leen and K-R Müller), MIT Press, Cambridge, MA, USA, 13th Annual Neural Information Processing Systems Conference (NIPS), June 2000 (inproceedings)

ei

PDF Web [BibTex]

ei Mika, S., Rätsch, G., Weston, J., Schölkopf, B., Smola, A., Müller, K. Invariant feature extraction and classification in kernel spaces In Advances in neural information processing systems 12, pages: 526-532, (Editors: SA Solla and TK Leen and K-R Müller), MIT Press, Cambridge, MA, USA, 13th Annual Neural Information Processing Systems Conference (NIPS), June 2000 (inproceedings)

PDF Web [BibTex]

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Model Selection for Support Vector Machines

Chapelle, O., Vapnik, V.

In Advances in Neural Information Processing Systems 12, pages: 230-236, (Editors: Solla, S.A. , T.K. Leen, K-R Müller), MIT Press, Cambridge, MA, USA, Thirteenth Annual Neural Information Processing Systems Conference (NIPS), June 2000 (inproceedings)

Abstract
New functionals for parameter (model) selection of Support Vector Machines are introduced based on the concepts of the span of support vectors and rescaling of the feature space. It is shown that using these functionals, one can both predict the best choice of parameters of the model and the relative quality of performance for any value of parameter.

ei

PDF Web [BibTex]

ei Chapelle, O., Vapnik, V. Model Selection for Support Vector Machines In Advances in Neural Information Processing Systems 12, pages: 230-236, (Editors: Solla, S.A. , T.K. Leen, K-R Müller), MIT Press, Cambridge, MA, USA, Thirteenth Annual Neural Information Processing Systems Conference (NIPS), June 2000 (inproceedings)

PDF Web [BibTex]

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The entropy regularization information criterion

Smola, A., Shawe-Taylor, J., Schölkopf, B., Williamson, R.

In Advances in Neural Information Processing Systems 12, pages: 342-348, (Editors: SA Solla and TK Leen and K-R Müller), MIT Press, Cambridge, MA, USA, 13th Annual Neural Information Processing Systems Conference (NIPS), June 2000 (inproceedings)

Abstract
Effective methods of capacity control via uniform convergence bounds for function expansions have been largely limited to Support Vector machines, where good bounds are obtainable by the entropy number approach. We extend these methods to systems with expansions in terms of arbitrary (parametrized) basis functions and a wide range of regularization methods covering the whole range of general linear additive models. This is achieved by a data dependent analysis of the eigenvalues of the corresponding design matrix.

ei

PDF Web [BibTex]

ei Smola, A., Shawe-Taylor, J., Schölkopf, B., Williamson, R. The entropy regularization information criterion In Advances in Neural Information Processing Systems 12, pages: 342-348, (Editors: SA Solla and TK Leen and K-R Müller), MIT Press, Cambridge, MA, USA, 13th Annual Neural Information Processing Systems Conference (NIPS), June 2000 (inproceedings)

PDF Web [BibTex]

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Stochastic tracking of 3D human figures using 2D image motion

(Winner of the 2010 Koenderink Prize for Fundamental Contributions in Computer Vision)

Sidenbladh, H., Black, M. J., Fleet, D.

In European Conference on Computer Vision, ECCV, pages: 702-718, LNCS 1843, Springer Verlag, Dublin, Ireland, June 2000 (inproceedings)

Abstract
A probabilistic method for tracking 3D articulated human figures in monocular image sequences is presented. Within a Bayesian framework, we define a generative model of image appearance, a robust likelihood function based on image gray level differences, and a prior probability distribution over pose and joint angles that models how humans move. The posterior probability distribution over model parameters is represented using a discrete set of samples and is propagated over time using particle filtering. The approach extends previous work on parameterized optical flow estimation to exploit a complex 3D articulated motion model. It also extends previous work on human motion tracking by including a perspective camera model, by modeling limb self occlusion, and by recovering 3D motion from a monocular sequence. The explicit posterior probability distribution represents ambiguities due to image matching, model singularities, and perspective projection. The method relies only on a frame-to-frame assumption of brightness constancy and hence is able to track people under changing viewpoints, in grayscale image sequences, and with complex unknown backgrounds.

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pdf code [BibTex]

ps Sidenbladh, H., Black, M. J., Fleet, D. Stochastic tracking of 3D human figures using 2D image motion In European Conference on Computer Vision, ECCV, pages: 702-718, LNCS 1843, Springer Verlag, Dublin, Ireland, June 2000 (inproceedings)

pdf code [BibTex]

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New Support Vector Algorithms

Schölkopf, B., Smola, A., Williamson, R., Bartlett, P.

Neural Computation, 12(5):1207-1245, May 2000 (article)

Abstract
We propose a new class of support vector algorithms for regression and classification. In these algorithms, a parameter {nu} lets one effectively control the number of support vectors. While this can be useful in its own right, the parameterization has the additional benefit of enabling us to eliminate one of the other free parameters of the algorithm: the accuracy parameter {epsilon} in the regression case, and the regularization constant C in the classification case. We describe the algorithms, give some theoretical results concerning the meaning and the choice of {nu}, and report experimental results.

ei

Web DOI [BibTex]

ei Schölkopf, B., Smola, A., Williamson, R., Bartlett, P. New Support Vector Algorithms Neural Computation, 12(5):1207-1245, May 2000 (article)

Web DOI [BibTex]

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Functional analysis of human motion data

Ormoneit, D., Hastie, T., Black, M. J.

In In Proc. 5th World Congress of the Bernoulli Society for Probability and Mathematical Statistics and 63rd Annual Meeting of the Institute of Mathematical Statistics, Guanajuato, Mexico, May 2000 (inproceedings)

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[BibTex]

ps Ormoneit, D., Hastie, T., Black, M. J. Functional analysis of human motion data In In Proc. 5th World Congress of the Bernoulli Society for Probability and Mathematical Statistics and 63rd Annual Meeting of the Institute of Mathematical Statistics, Guanajuato, Mexico, May 2000 (inproceedings)

[BibTex]

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Generalization Abilities of Ensemble Learning Algorithms: OLA, Bagging, Boosting

Shin, H., Jang, M., Cho, S., Lee, B., Lim, Y.

In Proc. of the Korea Information Science Conference, pages: 226-228, Conference on Korean Information Science, April 2000 (inproceedings)

ei

[BibTex]

ei Shin, H., Jang, M., Cho, S., Lee, B., Lim, Y. Generalization Abilities of Ensemble Learning Algorithms: OLA, Bagging, Boosting In Proc. of the Korea Information Science Conference, pages: 226-228, Conference on Korean Information Science, April 2000 (inproceedings)

[BibTex]

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A simple iterative approach to parameter optimization

Zien, A., Zimmer, R., Lengauer, T.

In RECOMB2000, pages: 318-327, ACM Press, New York, NY, USA, Forth Annual Conference on Research in Computational Molecular Biology, April 2000 (inproceedings)

Abstract
Various bioinformatics problems require optimizing several different properties simultaneously. For example, in the protein threading problem, a linear scoring function combines the values for different properties of possible sequence-to-structure alignments into a single score to allow for unambigous optimization. In this context, an essential question is how each property should be weighted. As the native structures are known for some sequences, the implied partial ordering on optimal alignments may be used to adjust the weights. To resolve the arising interdependence of weights and computed solutions, we propose a novel approach: iterating the computation of solutions (here: threading alignments) given the weights and the estimation of optimal weights of the scoring function given these solutions via a systematic calibration method. We show that this procedure converges to structurally meaningful weights, that also lead to significantly improved performance on comprehensive test data sets as measured in different ways. The latter indicates that the performance of threading can be improved in general.

ei

Web DOI [BibTex]

ei Zien, A., Zimmer, R., Lengauer, T. A simple iterative approach to parameter optimization In RECOMB2000, pages: 318-327, ACM Press, New York, NY, USA, Forth Annual Conference on Research in Computational Molecular Biology, April 2000 (inproceedings)

Web DOI [BibTex]

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Stochastic modeling and tracking of human motion

Ormoneit, D., Sidenbladh, H., Black, M. J., Hastie, T.

Learning 2000, Snowbird, UT, April 2000 (conference)

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abstract [BibTex]

ps Ormoneit, D., Sidenbladh, H., Black, M. J., Hastie, T. Stochastic modeling and tracking of human motion Learning 2000, Snowbird, UT, April 2000 (conference)

abstract [BibTex]

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A framework for modeling the appearance of 3D articulated figures

Sidenbladh, H., De la Torre, F., Black, M. J.

In Int. Conf. on Automatic Face and Gesture Recognition, pages: 368-375, Grenoble, France, March 2000 (inproceedings)

ps

pdf [BibTex]

ps Sidenbladh, H., De la Torre, F., Black, M. J. A framework for modeling the appearance of 3D articulated figures In Int. Conf. on Automatic Face and Gesture Recognition, pages: 368-375, Grenoble, France, March 2000 (inproceedings)

pdf [BibTex]

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Contrast discrimination using periodic pulse trains

Wichmann, F., Henning, G.

pages: 74, 3. T{\"u}binger Wahrnehmungskonferenz (TWK), February 2000 (poster)

Abstract
Understanding contrast transduction is essential for understanding spatial vision. Previous research (Wichmann et al. 1998; Wichmann, 1999; Henning and Wichmann, 1999) has demonstrated the importance of high contrasts to distinguish between alternative models of contrast discrimination. However, the modulation transfer function of the eye imposes large contrast losses on stimuli, particularly for stimuli of high spatial frequency, making high retinal contrasts difficult to obtain using sinusoidal gratings. Standard 2AFC contrast discrimination experiments were conducted using periodic pulse trains as stimuli. Given our Mitsubishi display we achieve stimuli with up to 160% contrast at the fundamental frequency. The shape of the threshold versus (pedestal) contrast (TvC) curve using pulse trains shows the characteristic dipper shape, i.e. contrast discrimination is sometimes “easier” than detection. The rising part of the TvC function has the same slope as that measured for contrast discrimination using sinusoidal gratings of the same frequency as the fundamental. Periodic pulse trains offer the possibility to explore the visual system’s properties using high retinal contrasts. Thus they might prove useful in tasks other than contrast discrimination. Second, at least for high spatial frequencies (8 c/deg) it appears that contrast discrimination using sinusoids and periodic pulse trains results in virtually identical TvC functions, indicating a lack of probability summation. Further implications of these results are discussed.

ei

Web [BibTex]

ei Wichmann, F., Henning, G. Contrast discrimination using periodic pulse trains pages: 74, 3. T{\"u}binger Wahrnehmungskonferenz (TWK), February 2000 (poster)

Web [BibTex]

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Subliminale Darbietung verkehrsrelevanter Information in Kraftfahrzeugen

Staedtgen, M., Hahn, S., Franz, MO., Spitzer, M.

pages: 98, (Editors: H.H. Bülthoff, K.R. Gegenfurtner, H.A. Mallot), 3. T{\"u}binger Wahrnehmungskonferenz (TWK), February 2000 (poster)

Abstract
Durch moderne Bildverarbeitungstechnologien ist es m{\"o}glich, in Kraftfahrzeugen bestimmte kritische Verkehrssituationen automatisch zu erkennen und den Fahrer zu warnen bzw. zu informieren. Ein Problem ist dabei die Darbietung der Ergebnisse, die den Fahrer m{\"o}glichst wenig belasten und seine Aufmerksamkeit nicht durch zus{\"a}tzliche Warnleuchten oder akustische Signale vom Verkehrsgeschehen ablenken soll. In einer Reihe von Experimenten wurde deshalb untersucht, ob subliminal dargebotene, das heißt nicht bewußt wahrgenommene, verkehrsrelevante Informationen verhaltenswirksam werden und zur Informations{\"u}bermittlung an den Fahrer genutzt werden k{\"o}nnen. In einem Experiment zur semantischen Bahnung konnte mit Hilfe einer lexikalischen Entscheidungsaufgabe gezeigt werden, daß auf den Straßenverkehr bezogene Worte schneller verarbeitet werden, wenn vorher ein damit in Zusammenhang stehendes Bild eines Verkehrsschildes subliminal pr{\"a}sentiert wurde. Auch bei parafovealer Darbietung der subliminalen Stimuli wurde eine Beschleunigung erzielt. In einer visuellen Suchaufgabe wurden in Bildern realer Verkehrssituationen Verkehrszeichen schneller entdeckt, wenn das Bild des Verkehrszeichens vorher subliminal dargeboten wurde. In beiden Experimenten betrug die Pr{\"a}sentationszeit f{\"u}r die Hinweisreize 17 ms, zus{\"a}tzlich wurde durch Vorw{\"a}rts- und R{\"u}ckw{\"a}rtsmaskierung die bewußteWahrnehmung verhindert. Diese Laboruntersuchungen zeigten, daß sich auch im Kontext des Straßenverkehrs Beschleunigungen der Informationsverarbeitung durch subliminal dargebotene Stimuli erreichen lassen. In einem dritten Experiment wurde die Darbietung eines subliminalen Hinweisreizes auf die Reaktionszeit beim Bremsen in einem realen Fahrversuch untersucht. Die Versuchspersonen (n=17) sollten so schnell wie m{\"o}glich bremsen, wenn die Bremsleuchten eines im Abstand von 12-15 m voran fahrenden Fahrzeuges aufleuchteten. In 50 von insgesamt 100 Durchg{\"a}ngen wurde ein subliminaler Stimulus (zwei rote Punkte mit einem Zentimeter Durchmesser und zehn Zentimeter Abstand) 150 ms vor Aufleuchten der Bremslichter pr{\"a}sentiert. Die Darbietung erfolgte durch ein im Auto an Stelle des Tachometers integriertes TFT-LCD Display. Im Vergleich zur Reaktion ohne subliminalen Stimulus verk{\"u}rzte sich die Reaktionszeit dadurch signifikant um 51 ms. In den beschriebenen Experimenten konnte gezeigt werden, daß die subliminale Darbietung verkehrsrelevanter Information auch in Kraftfahrzeugen verhaltenswirksam werden kann. In Zukunft k{\"o}nnte durch die Kombination der online-Bildverarbeitung im Kraftfahrzeug mit subliminaler Darbietung der Ergebnisse eine Erh{\"o}hung der Verkehrssicherheit und des Komforts erreicht werden.

ei

Web [BibTex]

ei Staedtgen, M., Hahn, S., Franz, MO., Spitzer, M. Subliminale Darbietung verkehrsrelevanter Information in Kraftfahrzeugen pages: 98, (Editors: H.H. Bülthoff, K.R. Gegenfurtner, H.A. Mallot), 3. T{\"u}binger Wahrnehmungskonferenz (TWK), February 2000 (poster)

Web [BibTex]

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Statistical Learning and Kernel Methods

Schölkopf, B.

In CISM Courses and Lectures, International Centre for Mechanical Sciences Vol.431, CISM Courses and Lectures, International Centre for Mechanical Sciences, 431(23):3-24, (Editors: G Della Riccia and H-J Lenz and R Kruse), Springer, Vienna, Data Fusion and Perception, 2000 (inbook)

ei

[BibTex]

ei Schölkopf, B. Statistical Learning and Kernel Methods In CISM Courses and Lectures, International Centre for Mechanical Sciences Vol.431, CISM Courses and Lectures, International Centre for Mechanical Sciences, 431(23):3-24, (Editors: G Della Riccia and H-J Lenz and R Kruse), Springer, Vienna, Data Fusion and Perception, 2000 (inbook)

[BibTex]

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Bounds on Error Expectation for Support Vector Machines

Vapnik, V., Chapelle, O.

Neural Computation, 12(9):2013-2036, 2000 (article)

Abstract
We introduce the concept of span of support vectors (SV) and show that the generalization ability of support vector machines (SVM) depends on this new geometrical concept. We prove that the value of the span is always smaller (and can be much smaller) than the diameter of the smallest sphere containing th e support vectors, used in previous bounds. We also demonstate experimentally that the prediction of the test error given by the span is very accurate and has direct application in model selection (choice of the optimal parameters of the SVM)

ei

GZIP [BibTex]

ei Vapnik, V., Chapelle, O. Bounds on Error Expectation for Support Vector Machines Neural Computation, 12(9):2013-2036, 2000 (article)

GZIP [BibTex]

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Intelligence as a Complex System

Zhou, D.

Biologische Kybernetik, 2000 (phdthesis)

ei

[BibTex]

ei Zhou, D. Intelligence as a Complex System Biologische Kybernetik, 2000 (phdthesis)

[BibTex]

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Neural Networks in Robot Control

Peters, J.

Biologische Kybernetik, Fernuniversität Hagen, Hagen, Germany, 2000 (diplomathesis)

ei

[BibTex]

ei Peters, J. Neural Networks in Robot Control Biologische Kybernetik, Fernuniversität Hagen, Hagen, Germany, 2000 (diplomathesis)

[BibTex]

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Choosing nu in support vector regression with different noise models — theory and experiments

Chalimourda, A., Schölkopf, B., Smola, A.

In Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, IJCNN 2000, Neural Computing: New Challenges and Perspectives for the New Millennium, IEEE, International Joint Conference on Neural Networks, 2000 (inproceedings)

ei

[BibTex]

ei Chalimourda, A., Schölkopf, B., Smola, A. Choosing nu in support vector regression with different noise models — theory and experiments In Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, IJCNN 2000, Neural Computing: New Challenges and Perspectives for the New Millennium, IEEE, International Joint Conference on Neural Networks, 2000 (inproceedings)

[BibTex]

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Bayesian modelling of fMRI time series

, PADFR., Rasmussen, CE., Hansen, LK.

In pages: 754-760, (Editors: Sara A. Solla, Todd K. Leen and Klaus-Robert Müller), 2000 (inproceedings)

Abstract
We present a Hidden Markov Model (HMM) for inferring the hidden psychological state (or neural activity) during single trial fMRI activation experiments with blocked task paradigms. Inference is based on Bayesian methodology, using a combination of analytical and a variety of Markov Chain Monte Carlo (MCMC) sampling techniques. The advantage of this method is that detection of short time learning effects between repeated trials is possible since inference is based only on single trial experiments.

ei

PDF PostScript [BibTex]

ei , PADFR., Rasmussen, CE., Hansen, LK. Bayesian modelling of fMRI time series In pages: 754-760, (Editors: Sara A. Solla, Todd K. Leen and Klaus-Robert Müller), 2000 (inproceedings)

PDF PostScript [BibTex]

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An Introduction to Kernel-Based Learning Algorithms

Müller, K., Mika, S., Rätsch, G., Tsuda, K., Schölkopf, B.

In Handbook of Neural Network Signal Processing, 4, (Editors: Yu Hen Hu and Jang-Neng Hwang), CRC Press, 2000 (inbook)

ei

[BibTex]

ei Müller, K., Mika, S., Rätsch, G., Tsuda, K., Schölkopf, B. An Introduction to Kernel-Based Learning Algorithms In Handbook of Neural Network Signal Processing, 4, (Editors: Yu Hen Hu and Jang-Neng Hwang), CRC Press, 2000 (inbook)

[BibTex]

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A High Resolution and Accurate Pentium Based Timer

Ong, CS., Wong, F., Lai, WK.

In 2000 (inproceedings)

ei

PDF [BibTex]

ei Ong, CS., Wong, F., Lai, WK. A High Resolution and Accurate Pentium Based Timer In 2000 (inproceedings)

PDF [BibTex]

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Robust Ensemble Learning for Data Mining

Rätsch, G., Schölkopf, B., Smola, A., Mika, S., Onoda, T., Müller, K.

In Fourth Pacific-Asia Conference on Knowledge Discovery and Data Mining, 1805, pages: 341-341, Lecture Notes in Artificial Intelligence, (Editors: H. Terano), Fourth Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2000 (inproceedings)

ei

[BibTex]

ei Rätsch, G., Schölkopf, B., Smola, A., Mika, S., Onoda, T., Müller, K. Robust Ensemble Learning for Data Mining In Fourth Pacific-Asia Conference on Knowledge Discovery and Data Mining, 1805, pages: 341-341, Lecture Notes in Artificial Intelligence, (Editors: H. Terano), Fourth Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2000 (inproceedings)

[BibTex]

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