NIPS 2001: Vancouver, British Columbia, Canada
Thomas G. Dietterich, Suzanna Becker, Zoubin Ghahramani (Eds.): Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, NIPS 2001, December 3-8, 2001, Vancouver, British Columbia, Canada]. MIT Press 2001- Peter Dayan: Motivated Reinforcement Learning. 11-18
- Shimon Edelman, Benjamin P. Hiles, Hwajin Yang, Nathan Intrator: Probabilistic principles in unsupervised learning of visual structure: human data and a model. 19-26
- David Jacobs, Bas Rokers, Archisman Rudra, Zili Liu: Fragment Completion in Humans and Machines. 27-34
- Dan Klein, Christopher D. Manning: Natural Language Grammar Induction Using a Constituent-Context Model. 35-42
- Michael Kositsky, Andrew G. Barto: The Emergence of Multiple Movement Units in the Presence of Noise and Feedback Delay. 43-50
- Michael C. Mozer, Michael D. Colagrosso, David E. Huber: A Rational Analysis of Cognitive Control in a Speeded Discrimination Task. 51-57
- S. Narayanan, Daniel Jurafsky: A Bayesian Model Predicts Human Parse Preference and Reading Times in Sentence Processing. 59-65
- Michiro Negishi, Stephen Jose Hanson: Grammar Transfer in a Second Order Recurrent Neural Network. 67-73
- Randall C. O'Reilly, R. S. Busby: Generalizable Relational Binding from Coarse-coded Distributed Representations. 75-82
- Mark A. Paskin: Grammatical Bigrams. 91-97
- Bob Rehder: Causal Categorization with Bayes Nets. 99-105
- Wheeler Ruml: Constructing Distributed Representations Using Additive Clustering. 107-114
- Jonathan L. Shapiro, J. Wearden: Reinforcement Learning and Time Perception -- a Model of Animal Experiments. 115-122
- Giorgio A. Ascoli, Alexei V. Samsonovich: Bayesian morphometry of hippocampal cells suggests same-cell somatodendritic repulsion. 133-139
- A. d'Avella, M. C. Tresch: Modularity in the motor system: decomposition of muscle patterns as combinations of time-varying synergies. 141-148
- J. A. Beintema, A. V. van den Berg, M. Lappe: Receptive field structure of flow detectors for heading perception. 149-156
- Benjamin Blankertz, Gabriel Curio, Klaus-Robert Müller: Classifying Single Trial EEG: Towards Brain Computer Interfacing. 157-164
- Neil Burgess, Tom Hartley: Orientational and Geometric Determinants of Place and Head-direction. 165-172
- Gal Chechik, Amir Globerson, M. J. Anderson, E. D. Young, Israel Nelken, Naftali Tishby: Group Redundancy Measures Reveal Redundancy Reduction in the Auditory Pathway. 173-180
- H. Colonius, A. Diederich: A Maximum-Likelihood Approach to Modeling Multisensory Enhancement. 181-187
- O. Donchin, Reza Shadmehr: Linking Motor Learning to Function Approximation: Learning in an Unlearnable Force Field. 197-203
- Julian Eggert, Berthold Bäuml: Exact differential equation population dynamics for integrate-and-fire neurons. 205-212
- Yun Gao, Michael J. Black, Elie Bienenstock, Shy Shoham, John P. Donoghue: Probabilistic Inference of Hand Motion from Neural Activity in Motor Cortex. 213-220
- Richard H. R. Hahnloser, Xiaohui Xie, H. Sebastian Seung: A theory of neural integration in the head-direction system. 221-228
- Peter E. Latham: Associative memory in realistic neuronal networks. 237-244
- N. Matsumoto, M. Okada: Self-regulation Mechanism of Temporally Asymmetric Hebbian Plasticity. 245-252
- Antonino Casile, Michele Rucci: Eye movements and the maturation of cortical orientation selectivity. 261-267
- Odelia Schwartz, E. J. Chichilnisky, Eero P. Simoncelli: Characterizing Neural Gain Control using Spike-triggered Covariance. 269-276
- Thomas P. Trappenberg, Edmund T. Rolls, Simon M. Stringer: Effective Size of Receptive Fields of Inferior Temporal Visual Cortex Neurons in Natural Scenes. 293-300
- B. D. Wright, Kamal Sen, William Bialek, A. J. Doupe: Spike timing and the coding of naturalistic sounds in a central auditory area of songbirds. 309-316
- Xiaohui Xie, Martin A. Giese: Generating velocity tuning by asymmetric recurrent connections. 325-332
- Dimitris Achlioptas, Frank McSherry, Bernhard Schölkopf: Sampling Techniques for Kernel Methods. 335-342
- Shun-ichi Amari, Hyeyoung Park, Tomoko Ozeki: Geometrical Singularities in the Neuromanifold of Multilayer Perceptrons. 343-350
- Mikio L. Braun, Joachim M. Buhmann: The Noisy Euclidean Traveling Salesman Problem and Learning. 351-358
- Nicolò Cesa-Bianchi, Alex Conconi, Claudio Gentile: On the Generalization Ability of On-Line Learning Algorithms. 359-366
- Nello Cristianini, John Shawe-Taylor, André Elisseeff, Jaz S. Kandola: On Kernel-Target Alignment. 367-373
- Sanjoy Dasgupta, Michael L. Littman, David A. McAllester: PAC Generalization Bounds for Co-training. 375-382
- Marcus Hutter: Distribution of Mutual Information. 399-406
- Shiro Ikeda, Toshiyuki Tanaka, Shun-ichi Amari: Information Geometrical Framework for Analyzing Belief Propagation Decoder. 407-414
- Hilbert J. Kappen, Wim Wiegerinck: Novel iteration schemes for the Cluster Variation Method. 415-422
- Roni Khardon, Dan Roth, Rocco A. Servedio: Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms. 423-430
- Jon M. Kleinberg: Small-World Phenomena and the Dynamics of Information. 431-438
- Manfred Opper, Robert Urbanczik: Asymptotic Universality for Learning Curves of Support Vector Machines. 479-486
- M. Schmitt: Computing Time Lower Bounds for Recurrent Sigmoidal Neural Networks. 503-510
- John Shawe-Taylor, Nello Cristianini, Jaz S. Kandola: On the Concentration of Spectral Properties. 511-517
- Peter Sollich: Gaussian Process Regression with Mismatched Models. 519-526
- Toshiyuki Tanaka, Shiro Ikeda, Shun-ichi Amari: Information-Geometrical Significance of Sparsity in Gallager Codes. 527-534
- T. Zhang: Generalization Performance of Some Learning Problems in Hilbert Functional Spaces. 543-550
- Christophe Andrieu, Nando de Freitas, Arnaud Doucet: Rao-Blackwellised Particle Filtering via Data Augmentation. 561-567
- Matthew J. Beal, Zoubin Ghahramani, Carl Edward Rasmussen: The Infinite Hidden Markov Model. 577-584
- Mikhail Belkin, Partha Niyogi: Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering. 585-591
- Olivier Chapelle, Bernhard Schölkopf: Incorporating Invariances in Non-Linear Support Vector Machines. 609-616
- Michael Collins, S. Dasgupta, Robert E. Schapire: A Generalization of Principal Components Analysis to the Exponential Family. 617-624
- Ronan Collobert, Samy Bengio, Yoshua Bengio: A Parallel Mixture of SVMs for Very Large Scale Problems. 633-640
- Nello Cristianini, John Shawe-Taylor, Jaz S. Kandola: Spectral Kernel Methods for Clustering. 649-655
- Lehel Csató, Manfred Opper, Ole Winther: TAP Gibbs Free Energy, Belief Propagation and Sparsity. 657-663
- Carlotta Domeniconi, Dimitrios Gunopulos: Adaptive Nearest Neighbor Classification Using Support Vector Machines. 665-672
- Daniela Pucci de Farias, Benjamin Van Roy: Approximate Dynamic Programming via Linear Programming. 689-695
- Mário A. T. Figueiredo: Adaptive Sparseness Using Jeffreys Prior. 697-704
- Shai Fine, Katya Scheinberg: Incremental Learning and Selective Sampling via Parametric Optimization Framework for SVM. 705-711
- Dieter Fox: KLD-Sampling: Adaptive Particle Filters. 713-720
- Brendan J. Frey, Anitha Kannan, Nebojsa Jojic: Product Analysis: Learning to Model Observations as Products of Hidden Variables. 729-735
- Brendan J. Frey, Ralf Koetter, Nemanja Petrovic: Very loopy belief propagation for unwrapping phase images. 737-743
- Polina Golland: Discriminative Direction for Kernel Classifiers. 745-752
- Patrick Haffner: Escaping the Convex Hull with Extrapolated Vector Machines. 753-760
- Stefan Harmeling, Andreas Ziehe, Motoaki Kawanabe, Klaus-Robert Müller: Kernel Feature Spaces and Nonlinear Blind Souce Separation. 761-768
- Gert R. G. Lanckriet, Laurent El Ghaoui, Chiranjib Bhattacharyya, Michael I. Jordan: Minimax Probability Machine. 801-807
- Michael L. Littman, Michael J. Kearns, Satinder P. Singh: An Efficient, Exact Algorithm for Solving Tree-Structured Graphical Games. 817-823
- Andrew Y. Ng, Michael I. Jordan: On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes. 841-848
- Andrew Y. Ng, Michael I. Jordan, Yair Weiss: On Spectral Clustering: Analysis and an algorithm. 849-856
- Alberto Paccanaro, Geoffrey E. Hinton: Learning Hierarchical Structures with Linear Relational Embedding. 857-864
- Marcello Pelillo: Matching Free Trees with Replicator Equations. 865-872
- Anand Rangarajan, Alan L. Yuille: MIME: Mutual Information Minimization and Entropy Maximization for Bayesian Belief Propagation. 873-880
- Sam T. Roweis, Lawrence K. Saul, Geoffrey E. Hinton: Global Coordination of Local Linear Models. 889-896
- Lawrence K. Saul, Daniel D. Lee: Multiplicative Updates for Classification by Mixture Models. 897-904
- Matthias Seeger: Covariance Kernels from Bayesian Generative Models. 905-912
- Hiroshi Shimodaira, Ken-ichi Noma, Mitsuru Nakai, Shigeki Sagayama: Dynamic Time-Alignment Kernel in Support Vector Machine. 921-928
- Noam Slonim, Nir Friedman, Naftali Tishby: Agglomerative Multivariate Information Bottleneck. 929-936
- Kari Torkkola: Learning Discriminative Feature Transforms to Low Dimensions in Low Dimentions. 969-976
- Koji Tsuda, Motoaki Kawanabe, Gunnar Rätsch, Sören Sonnenburg, Klaus-Robert Müller: A New Discriminative Kernel From Probabilistic Models. 977-984
- Pascal Vincent, Yoshua Bengio: K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms. 985-992
- Martin J. Wainwright, Tommi Jaakkola, Alan S. Willsky: Tree-based reparameterization for approximate inference on loopy graphs. 1001-1008
- Heiko Wersing: Learning Lateral Interactions for Feature Binding and Sensory Segmentation. 1009-1016
- Ran El-Yaniv, Oren Souroujon: Iterative Double Clustering for Unsupervised and Semi-Supervised Learning. 1025-1032
- B. Zadrozny: Reducing multiclass to binary by coupling probability estimates. 1041-1048
- Michael Zibulevsky, Pavel Kisilev, Yehoshua Y. Zeevi, Barak A. Pearlmutter: Blind Source Separation via Multinode Sparse Representation. 1049-1056
- Hongyuan Zha, Xiaofeng He, Chris H. Q. Ding, Ming Gu, Horst D. Simon: Spectral Relaxation for K-means Clustering. 1057-1064
- T. Zhang: A General Greedy Approximation Algorithm with Applications. 1065-1072
- A. Bofill, A. F. Murray, D. P. Thompson: Citcuits for VLSI Implementation of Temporally Asymmetric Hebbian Learning. 1091-1098
- Roman Genov, Gert Cauwenberghs: Stochastic Mixed-Signal VLSI Architecture for High-Dimensional Kernel Machines. 1099-1105
- Shih-Chii Liu, Jörg Kramer, Giacomo Indiveri, Tobi Delbrück, Rodney J. Douglas: Orientation-Selective aVLSI Spiking Neurons. 1107-1114
- Takashi Morie, Tomohiro Matsuura, Makoto Nagata, Atsushi Iwata: An Efficient Clustering Algorithm Using Stochastic Association Model and Its Implementation Using Nanostructures. 1115-1122
- Aaron P. Shon, David Hsu, Chris Diorio: Learning Spike-Based Correlations and Conditional Probabilities in Silicon. 1123-1130
- Toshihiko Yamasaki, Tadashi Shibata: Analog Soft-Pattern-Matching Classifier using Floating-Gate MOS Technology. 1131-1138
- Andrew D. Brown, Geoffrey E. Hinton: Relative Density Nets: A New Way to Combine Backpropagation with HMM's. 1149-1156
- William M. Campbell: A Sequence Kernel and its Application to Speaker Recognition. 1157-1163
- Brendan J. Frey, Trausti T. Kristjansson, Li Deng, Alex Acero: ALGONQUIN - Learning Dynamic Noise Models From Noisy Speech for Robust Speech Recognition. 1165-1171
- Frank C. Meinecke, Andreas Ziehe, Motoaki Kawanabe, Klaus-Robert Müller: Estimating the Reliability of ICA Projections. 1181-1188
- Stuart N. Wrigley, Guy J. Brown: A Neural Oscillator Model of Auditory Selective Attention. 1213-1220
- B. T. Backus: Perceptual Metamers in Stereoscopic Vision. 1223-1230
- James M. Coughlan, Alan L. Yuille: The g Factor: Relating Distributions on Features to Distributions on Images. 1231-1238
- Bernd Heisele, Thomas Serre, Massimiliano Pontil, Thomas Vetter, Tomaso Poggio: Categorization by Learning and Combining Object Parts. 1239-1245
- Laurent Itti, Jochen Braun, Christof Koch: Modeling the Modulatory Effect of Attention on Human Spatial Vision. 1247-1254
- Marzia Polito, Pietro Perona: Grouping and dimensionality reduction by locally linear embedding. 1255-1262
- Silvio P. Sabatini, Fabio Solari, G. Andreani, C. Bartolozzi, Giacomo M. Bisio: A Hierarchical Model of Complex Cells in Visual Cortex for the Binocular Perception of Motion-in-Depth. 1271-1278
- Javid Sadr, Sayan Mukherjee, K. Thoresz, Pawan Sinha: The Fidelity of Local Ordinal Encoding. 1279-1286
- Chris Stauffer, Erik G. Miller, Kinh Tieu: Transform-invariant Image Decomposition with Similarity Templates. 1295-1302
- Antonio Torralba: Contextual Modulation of Target Saliency. 1303-1310
- Paul A. Viola, Michael J. Jones: Fast and Robust Classification using Asymmetric AdaBoost and a Detector Cascade. 1311-1318
- Lance R. Williams, John W. Zweck: A Rotation and Translation Invariant Discrete Saliency Network. 1319-1326
- Timothy X. Brown: Switch Packet Arbitration via Queue-Learning. 1337-1344
- Igor V. Cadez, Paul S. Bradley: Model Based Population Tracking and Automatic Detection of Distribution Changes. 1345-1352
- Igor V. Cadez, Padhraic Smyth: Bayesian Predictive Profiles With Applications to Retail Transaction Data. 1353-1360
- Ali Taylan Cemgil, Bert Kappen: Tempo tracking and rhythm quantization by sequential Monte Carlo. 1361-1368
- Nicolas Chapados, Yoshua Bengio, Pascal Vincent, Joumana Ghosn, Charles Dugas, Ichiro Takeuchi, Linyan Meng: Estimating Car Insurance Premia: a Case Study in High-Dimensional Data Inference. 1369-1376
- Judy A. Franklin: Improvisation and Learning. 1377-1384
- Thomas L. Griffiths, Joshua B. Tenenbaum: Using Vocabulary Knowledge in Bayesian Multinomial Estimation. 1385-1392
- Charles Lee Isbell Jr., Christian R. Shelton, Michael J. Kearns, Satinder P. Singh, Peter Stone: Cobot: A Social Reinforcement Learning Agent. 1393-1400
- Neil D. Lawrence, Antony I. T. Rowstron, Christopher M. Bishop, M. J. Taylor: Optimising Synchronisation Times for Mobile Devices. 1401-1408
- Michael C. Mozer, Robert H. Dodier, Michael D. Colagrosso, Cesar Guerra-Salcedo, Richard H. Wolniewicz: Prodding the ROC Curve: Constrained Optimization of Classifier Performance. 1409-1415
- John C. Platt, Christopher J. C. Burges, S. Swenson, C. Weare, A. Zheng: Learning a Gaussian Process Prior for Automatically Generating Music Playlists. 1425-1432
- Christopher Raphael: A Bayesian Network for Real-Time Musical Accompaniment. 1433-1439
- Matthew Richardson, Pedro Domingos: The Intelligent surfer: Probabilistic Combination of Link and Content Information in PageRank. 1441-1448
- Manfred K. Warmuth, Gunnar Rätsch, Michael Mathieson, Jun Liao, Christian Lemmen: Active Learning in the Drug Discovery Process. 1449-1456
- Ming-Hour Yang: Face Recognition Using Kernel Methods. 1457-1464
- Hans-Georg Zimmermann, Ralph Neuneier, Ralph Grothmann: Active Portfolio-Management based on Error Correction Neural Networks. 1465-1472
- Bram Bakker: Reinforcement Learning with Long Short-Term Memory. 1475-1482
- Yu-Han Chang, Leslie Pack Kaelbling: Playing is believing: The role of beliefs in multi-agent learning. 1483-1490
- Evan Greensmith, Peter L. Bartlett, Jonathan Baxter: Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning. 1507-1514
- Gregory Z. Grudic, Lyle H. Ungar: Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning. 1515-1522
- Sham Kakade: A Natural Policy Gradient. 1531-1538
- Michael L. Littman, Richard S. Sutton, Satinder P. Singh: Predictive Representations of State. 1555-1561
- Shie Mannor, Nahum Shimkin: The Steering Approach for Multi-Criteria Reinforcement Learning. 1563-1570
- Rémi Munos: Efficient Resources Allocation for Markov Decision Processes. 1571-1578
- Xin Wang, Thomas G. Dietterich: Stabilizing Value Function Approximation with the BFBP Algorithm. 1587-1594
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last updated on 2013-06-18T211851 by the dblp team