NIPS 2002: Vancouver, British Columbia, Canada
Suzanna Becker, Sebastian Thrun, Klaus Obermayer (Eds.): Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, NIPS 2002, December 9-14, 2002, Vancouver, British Columbia, Canada]. MIT Press 2003 ISBN 0-262-02550-7- Dan Klein, Christopher D. Manning: Fast Exact Inference with a Factored Model for Natural Language Parsing. 3-10
- Emanuel Todorov, Michael I. Jordan: A Minimal Intervention Principle for Coordinated Movement. 27-34
- David Fass, Jacob Feldman: Categorization Under Complexity: A Unified MDL Account of Human Learning of Regular and Irregular Categories. 35-34
- Willem H. Zuidema: How the Poverty of the Stimulus Solves the Poverty of the Stimulus. 43-50
- Daniel J. Navarro, Michael D. Lee: Combining Dimensions and Features in Similarity-Based Representations. 59-66
- Kenneth J. Malmberg, René Zeelenberg, Richard M. Shiffrin: Modeling Midazolam's Effect on the Hippocampus and Recognition Memory. 67-66
- Robert A. Jacobs, Melissa Dominguez: Visual Development Aids the Acquisition of Motion Velocity Sensitivities. 75-82
- Nathaniel D. Daw, Aaron C. Courville, David S. Touretzky: Timing and Partial Observability in the Dopamine System. 83-90
- Zach Solan, Eytan Ruppin, David Horn, Shimon Edelman: Automatic Acquisition and Efficient Representation of Syntactic Structures. 91-98
- Wei Wu, Michael J. Black, Yun Gao, Elie Bienenstock, Mijail Serruya, A. Shaikhouni, John P. Donoghue: Neural Decoding of Cursor Motion Using a Kalman Filter. 117-124
- Lavi Shpigelman, Yoram Singer, Rony Paz, Eilon Vaadia: Spikernels: Embedding Spiking Neurons in Inner-Product Spaces. 125-132
- Christian K. Machens, Michael Wehr, Anthony M. Zador: Spectro-Temporal Receptive Fields of Subthreshold Responses in Auditory Cortex. 133-140
- Jarmo Hurri, Aapo Hyvärinen: Temporal Coherence, Natural Image Sequences, and the Visual Cortex. 141-148
- David Barber: Learning in Spiking Neural Assemblies. 149-156
- Angela J. Yu, Peter Dayan: Expected and Unexpected Uncertainty: ACh and NE in the Neocortex. 157-164
- Aaron J. Gruber, Sara A. Solla, James C. Houk: Dopamine Induced Bistability Enhances Signal Processing in Spiny Neurons. 165-172
- Liam Paninski: Convergence Properties of Some Spike-Triggered Analysis Techniques. 173-180
- Matthias Bethge, David Rotermund, Klaus Pawelzik: Binary Tuning is Optimal for Neural Rate Coding with High Temporal Resolution. 189-196
- Elad Schneidman, William Bialek, Michael J. Berry II: An Information Theoretic Approach to the Functional Classification of Neurons. 197-204
- Javier R. Movellan, Thomas Wachtler, Thomas D. Albright, Terrence J. Sejnowski: Factorial Coding of Color in Primary Visual Cortex. 205-212
- Wolfgang Maass, Thomas Natschläger, Henry Markram: A Model for Real-Time Computation in Generic Neural Microcircuits. 213-220
- Alex Holub, Gilles Laurent, Pietro Perona: A Digital Antennal Lobe for Pattern Equalization: Analysis and Design. 229-236
- Michael Eisele, Kenneth D. Miller: Hidden Markov Model of Cortical Synaptic Plasticity: Derivation of the Learning Rule. 237-244
- Luk-Chong Yeung, Brian S. Blais, Leon N. Cooper, Harel Z. Shouval: Selectivity and Metaplasticity in a Unified Calcium-Dependent Model. 245-252
- Alistair Bray, Dominique Martinez: Kernel-Based Extraction of Slow Features: Complex Cells Learn Disparity and Translation Invariance from Natural Images. 253-260
- Tatyana Sharpee, Nicole C. Rust, William Bialek: Maximally Informative Dimensions: Analyzing Neural Responses to Natural Signals. 261-268
- Arunava Banerjee, Alexandre Pouget: Dynamical Constraints on Computing with Spike Timing in the Cortex. 269-276
- Patrik O. Hoyer, Aapo Hyvärinen: Interpreting Neural Response Variability as Monte Carlo Sampling of the Posterior. 277-284
- Alon Fishbach, Bradford J. May: A Neural Edge-Detection Model for Enhanced Auditory Sensitivity in Modulated Noise. 285-292
- Christian W. Eurich: An Estimation-Theoretic Framework for the Presentation of Multiple Stimuli. 293-300
- Maneesh Sahani, Jennifer F. Linden: Evidence Optimization Techniques for Estimating Stimulus-Response Functions. 301-308
- Duane Q. Nykamp: Reconstructing Stimulus-Driven Neural Networks from Spike Times. 309-316
- Dörthe Malzahn, Manfred Opper: A Statistical Mechanics Approach to Approximate Analytical Bootstrap Averages. 327-334
- Tom Heskes: Stable Fixed Points of Loopy Belief Propagation Are Local Minima of the Bethe Free Energy. 343-350
- David A. McAllester, Luis E. Ortiz: Concentration Inequalities for the Missing Mass and for Histogram Rule Error. 351-358
- John Shawe-Taylor, Christopher K. I. Williams: The Stability of Kernel Principal Components Analysis and its Relation to the Process Eigenspectrum. 367-374
- Jonathan L. Shapiro: Scaling of Probability-Based Optimization Algorithms. 383-390
- Sumio Watanabe, Shun-ichi Amari: The Effect of Singularities in a Learning Machine when the True Parameters Do Not Lie on such Singularities. 391-398
- Tatsuto Murayama, Masato Okada: Rate Distortion Function in the Spin Glass State: A Toy Model. 407-414
- Eric Allender, Sanjeev Arora, Michael Kearns, Cristopher Moore, Alexander Russell: A Note on the Representational Incompatibility of Function Approximation and Factored Dynamics. 431-437
- Jon M. Kleinberg: An Impossibility Theorem for Clustering. 446-453
- Tong Zhang: Effective Dimension and Generalization of Kernel Learning. 454-461
- Koby Crammer, Ran Gilad-Bachrach, Amir Navot, Naftali Tishby: Margin Analysis of the LVQ Algorithm. 462-469
- Nicolò Cesa-Bianchi, Alex Conconi, Claudio Gentile: Margin-Based Algorithms for Information Filtering. 470-477
- Bin Wu, K. Y. Michael Wong, David Bodoff: Mean Field Approach to a Probabilistic Model in Information Retrieval. 497-504
- Eric P. Xing, Andrew Y. Ng, Michael I. Jordan, Stuart J. Russell: Distance Metric Learning with Application to Clustering with Side-Information. 505-512
- Gunnar Rätsch, Alexander J. Smola, Sebastian Mika: Adapting Codes and Embeddings for Polychotomies. 513-520
- Glenn Fung, Olvi L. Mangasarian, Jude W. Shavlik: Knowledge-Based Support Vector Machine Classifiers. 521-528
- Agathe Girard, Carl Edward Rasmussen, Joaquin Quiñonero Candela, Roderick Murray-Smith: Gaussian Process Priors with Uncertain Inputs - Application to Multiple-Step Ahead Time Series Forecasting. 529-536
- Sepp Hochreiter, Michael Mozer, Klaus Obermayer: Coulomb Classifiers: Generalizing Support Vector Machines via an Analogy to Electrostatic Systems. 545-552
- Stuart Andrews, Ioannis Tsochantaridis, Thomas Hofmann: Support Vector Machines for Multiple-Instance Learning. 561-568
- Geoffrey J. Gordon: Generalized2 Linear2 Models. 577-584
- Olivier Chapelle, Jason Weston, Bernhard Schölkopf: Cluster Kernels for Semi-Supervised Learning. 585-592
- Herbert Jaeger: Adaptive Nonlinear System Identification with Echo State Networks. 593-600
- Neil D. Lawrence, Matthias Seeger, Ralf Herbrich: Fast Sparse Gaussian Process Methods: The Informative Vector Machine. 609-616
- Tilman Lange, Mikio L. Braun, Volker Roth, Joachim M. Buhmann: Stability-Based Model Selection. 617-624
- Martin H. C. Law, Anil K. Jain, Mário A. T. Figueiredo: Feature Selection in Mixture-Based Clustering. 625-632
- Craig Saunders, John Shawe-Taylor, Alexei Vinokourov: String Kernels, Fisher Kernels and Finite State Automata. 633-640
- Trevor Hastie, Robert Tibshirani: Independent Components Analysis through Product Density Estimation. 649-656
- Alexander G. Gray, Bernd Fischer, Johann Schumann, Wray L. Buntine: Automatic Derivation of Statistical Algorithms: The EM Family and Beyond. 673-680
- Balázs Kégl: Intrinsic Dimension Estimation Using Packing Numbers. 681-688
- Vin de Silva, Joshua B. Tenenbaum: Global Versus Local Methods in Nonlinear Dimensionality Reduction. 705-712
- David Barber: Dynamic Bayesian Networks with Deterministic Latent Tables. 713-720
- Elzbieta Pekalska, David M. J. Tax, Robert P. W. Duin: One-Class LP Classifiers for Dissimilarity Representations. 761-768
- Thomas Strohmann, Gregory Z. Grudic: A Formulation for Minimax Probability Machine Regression. 769-776
- Christopher M. Bishop, David J. Spiegelhalter, John M. Winn: VIBES: A Variational Inference Engine for Bayesian Networks. 777-784
- Sariel Har-Peled, Dan Roth, Dav Zimak: Constraint Classification for Multiclass Classification and Ranking. 785-792
- Martin J. Wainwright, Tommi Jaakkola, Alan S. Willsky: Exact MAP Estimates by (Hyper)tree Agreement. 809-816
- Volker Roth, Julian Laub, Joachim M. Buhmann, Klaus-Robert Müller: Going Metric: Denoising Pairwise Data. 817-824
- David Cohn: Informed Projections. 849-856
- Kenji Fukumizu, Shotaro Akaho, Shun-ichi Amari: Critical Lines in Symmetry of Mixture Models and its Application to Component Splitting. 865-872
- Jason Weston, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf, Vladimir Vapnik: Kernel Dependency Estimation. 873-880
- Kwokleung Chan, Te-Won Lee, Terrence J. Sejnowski: Handling Missing Data with Variational Bayesian Learning of ICA. 881-888
- Sepp Hochreiter, Klaus Obermayer: Feature Selection and Classification on Matrix Data: From Large Margins to Small Covering Numbers. 889-896
- Gert R. G. Lanckriet, Laurent El Ghaoui, Michael I. Jordan: Robust Novelty Detection with Single-Class MPM. 905-912
- Nicholas P. Hughes, David Lowe: Artefactual Structure from Least-Squares Multidimensional Scaling. 913-920
- Marina Sokolova, Mario Marchand, Nathalie Japkowicz, John Shawe-Taylor: The Decision List Machine. 921-928
- Mikhail Belkin, Partha Niyogi: Using Manifold Stucture for Partially Labeled Classification. 929-936
- Anton Schwaighofer, Volker Tresp: Transductive and Inductive Methods for Approximate Gaussian Process Regression. 953-960
- Matthew Brand: Charting a Manifold. 961-968
- Albert E. Parker, Tomás Gedeon, Alexander Dimitrov: Annealing and the Rate Distortion Problem. 969-976
- Yasemin Altun, Thomas Hofmann, Mark Johnson: Discriminative Learning for Label Sequences via Boosting. 977-984
- Peter Meinicke, Thorsten Twellmann, Helge Ritter: Discriminative Densities from Maximum Contrast Estimation. 985-992
- Stan Z. Li, ZhenQiu Zhang, Heung-Yeung Shum, HongJiang Zhang: FloatBoost Learning for Classification. 993-1000
- E. Solak, Roderick Murray-Smith, William E. Leithead, Douglas J. Leith, Carl Edward Rasmussen: Derivative Observations in Gaussian Process Models of Dynamic Systems. 1033-1040
- Fei Sha, Lawrence K. Saul, Daniel D. Lee: Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines. 1041-1048
- Alexandre R. S. Romariz, Kelvin Wagner: Optoelectronic Implementation of a FitzHugh-Nagumo Neural Model. 1067-1074
- Shih-Chii Liu, Malte Boegershausen, Pascal Suter: Circuit Model of Short-Term Synaptic Dynamics. 1075-1082
- David Hsu, Seth Bridges, Miguel Figueroa, Chris Diorio: Adaptive Quantization and Density Estimation in Silicon. 1083-1090
- Giacomo Indiveri: Neuromorphic Bistable VLSI Synapses with Spike-Timing-Dependent Plasticity. 1091-1098
- Ricardo Carmona-Galán, Francisco Jiménez-Garrido, Rafael Domínguez-Castro, Servando Espejo-Meana, Ángel Rodríguez-Vázquez: Retinal Processing Emulation in a Programmable 2-Layer Analog Array Processor CMOS Chip. 1099-1106
- Peter Meinicke, Matthias Kaper, Florian Hoppe, Manfred Heumann, Helge Ritter: Improving Transfer Rates in Brain Computer Interfacing: A Case Study. 1107-1114
- Guido Dornhege, Benjamin Blankertz, Gabriel Curio, Klaus-Robert Müller: Combining Features for BCI. 1115-1122
- Jakob Heinzle, Alan Stocker: Classifying Patterns of Visual Motion - a Neuromorphic Approach. 1123-1130
- Terry Elliott, Jörg Kramer: Developing Topography and Ocular Dominance Using Two aVLSI Vision Sensors and a Neurotrophic Model of Plasticity. 1131-1138
- R. Jacob Vogelstein, Francesco Tenore, Ralf Philipp, Miriam S. Adlerstein, David H. Goldberg, Gert Cauwenberghs: Spike Timing-Dependent Plasticity in the Address Domain. 1147-1154
- Seth Bridges, Miguel Figueroa, David Hsu, Chris Diorio: Field-Programmable Learning Arrays. 1155-1162
- Shantanu Chakrabartty, Gert Cauwenberghs: Forward-Decoding Kernel-Based Phone Recognition. 1165-1172
- Gil-Jin Jang, Te-Won Lee: A Probabilistic Approach to Single Channel Blind Signal Separation. 1173-1180
- Lawrence K. Saul, Daniel D. Lee, Charles L. Isbell, Yann LeCun: Real Time Voice Processing with Audiovisual Feedback: Toward Autonomous Agents with Perfect Pitch. 1181-1188
- Patrick J. Wolfe, Simon J. Godsill: Bayesian Estimation of Time-Frequency Coefficients for Audio Signal Enhancement. 1197-1204
- Hagai Attias: Source Separation with a Sensor Array Using Graphical Models and Subband Filtering. 1205-1212
- Samy Bengio: An Asynchronous Hidden Markov Model for Audio-Visual Speech Recognition. 1213-1220
- Shinji Watanabe, Yasuhiro Minami, Atsushi Nakamura, Naonori Ueda: Application of Variational Bayesian Approach to Speech Recognition. 1237-1244
- Anat Levin, Assaf Zomet, Yair Weiss: Learning to Perceive Transparency from the Statistics of Natural Scenes. 1247-1254
- David R. Martin, Charless Fowlkes, Jitendra Malik: Learning to Detect Natural Image Boundaries Using Brightness and Texture. 1255-1262
- Anitha Kannan, Nebojsa Jojic, Brendan J. Frey: Fast Transformation-Invariant Factor Analysis. 1263-1270
- Marian Stewart Bartlett, Gwen Littlewort, Bjorn Braathen, Terrence J. Sejnowski, Javier R. Movellan: A Prototype for Automatic Recognition of Spontaneous Facial Actions. 1271-1278
- Amos J. Storkey: Dynamic Structure Super-Resolution. 1295-1302
- Leonid Taycher, John W. Fisher III, Trevor Darrell: Recovering Articulated Model Topology from Observed Rigid Motion. 1311-1318
- Matthias O. Franz, Javaan S. Chahl: Linear Combinations of Optic Flow Vectors for Estimating Self-Motion - a Real-World Test of a Neural Model. 1319-1326
- William T. Freeman, Antonio Torralba: Shape Recipes: Scene Representations that Refer to the Image. 1335-1342
- Marshall F. Tappen, William T. Freeman, Edward H. Adelson: Recovering Intrinsic Images from a Single Image. 1343-1350
- Nuno Vasconcelos: Feature Selection by Maximum Marginal Diversity. 1351-1358
- Max Welling, Geoffrey E. Hinton, Simon Osindero: Learning Sparse Topographic Representations with Products of Student-t Distributions. 1359-1366
- Yan Karklin, Michael S. Lewicki: A Model for Learning Variance Components of Natural Images. 1367-1374
- Barbara Caputo, Gyuri Dorkó: How to Combine Color and Shape Information for 3D Object Recognition: Kernels do the Trick. 1375-1382
- Stella X. Yu, Ralph Gross, Jianbo Shi: Concurrent Object Recognition and Segmentation by Graph Partitioning. 1383-1390
- Christopher K. I. Williams, Michalis K. Titsias: Learning About Multiple Objects in Images: Factorial Learning without Factorial Search. 1391-1398
- Hanna Pasula, Bhaskara Marthi, Brian Milch, Stuart J. Russell, Ilya Shpitser: Identity Uncertainty and Citation Matching. 1401-1408
- Anton Schwaighofer, Volker Tresp, Peter Mayer, Alexander K. Scheel, Gerhard A. Müller: The RA Scanner: Prediction of Rheumatoid Joint Inflammation Based on Laser Imaging. 1409-1416
- Christina S. Leslie, Eleazar Eskin, Jason Weston, William Stafford Noble: Mismatch String Kernels for SVM Protein Classification. 1417-1424
- Jean-Philippe Vert, Minoru Kanehisa: Graph-Driven Feature Extraction From Microarray Data Using Diffusion Kernels and Kernel CCA. 1425-1432
- Rubén Morales-Menéndez, Nando de Freitas, David Poole: Real-Time Monitoring of Complex Industrial Processes with Particle Filters. 1433-1440
- Dmitry Pavlov, David M. Pennock: A Maximum Entropy Approach to Collaborative Filtering in Dynamic, Sparse, High-Dimensional Domains. 1441-1448
- Gianluca Pollastri, Pierre Baldi, Alessandro Vullo, Paolo Frasconi: Prediction of Protein Topologies Using Generalized IOHMMS and RNNs. 1449-1456
- Robert B. Gramacy, Manfred K. Warmuth, Scott A. Brandt, Ismail Ari: Adaptive Caching by Refetching. 1465-1472
- Alexei Vinokourov, John Shawe-Taylor, Nello Cristianini: Inferring a Semantic Representation of Text via Cross-Language Correlation Analysis. 1473-1480
- William W. Cohen: Improving a Page Classifier with Anchor Extraction and Link Analysis. 1481-1488
- Eric P. Xing, Michael I. Jordan, Richard M. Karp, Stuart J. Russell: A Hierarchical Bayesian Markovian Model for Motifs in Biopolymer Sequences. 1489-1496
- Sergey Kirshner, Igor V. Cadez, Padhraic Smyth, Chandrika Kamath: Learning to Classify Galaxy Shapes Using the EM Algorithm. 1497-1504
- Eric Brochu, Nando de Freitas: "Name That Song!" A Probabilistic Approach to Querying on Music and Text. 1505-1512
- Matthew G. Snover, Michael R. Brent: A Probabilistic Model for Learning Concatenative Morphology. 1513-1520
- Auke Jan Ijspeert, Jun Nakanishi, Stefan Schaal: Learning Attractor Landscapes for Learning Motor Primitives. 1523-1530
- Jun Morimoto, Christopher G. Atkeson: Minimax Differential Dynamic Programming: An Application to Robust Biped Walking. 1539-1546
- Jürgen Schmidhuber: Bias-Optimal Incremental Problem Solving. 1547-1546
- Ralf Schoknecht: Optimality of Reinforcement Learning Algorithms with Linear Function Approximation. 1555-1562
- Xiaofeng Wang, Tuomas Sandholm: Reinforcement Learning to Play an Optimal Nash Equilibrium in Team Markov Games. 1571-1578
- Ralf Schoknecht, Artur Merke: Convergent Combinations of Reinforcement Learning with Linear Function Approximation. 1579-1586
- Daniela Pucci de Farias, Benjamin Van Roy: Approximate Linear Programming for Average-Cost Dynamic Programming. 1587-1594
- Christopher G. Atkeson, Jun Morimoto: Nonparametric Representation of Policies and Value Functions: A Trajectory-Based Approach. 1611-1618
- Michail G. Lagoudakis, Ronald Parr: Learning in Zero-Sum Team Markov Games Using Factored Value Functions. 1627-1634
- Nicholas Roy, Geoffrey J. Gordon: Exponential Family PCA for Belief Compression in POMDPs. 1635-1642
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last updated on 2013-06-19T201401 by the dblp team