NIPS 2003: Vancouver, British Columbia, Canada
Sebastian Thrun, Lawrence K. Saul, Bernhard Schölkopf (Eds.): Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, NIPS 2003, December 8-13, 2003, Vancouver and Whistler, British Columbia, Canada]. MIT Press 2004 ISBN 0-262-20152-6- Alexander T. Ihler, Erik B. Sudderth, William T. Freeman, Alan S. Willsky: Efficient Multiscale Sampling from Products of Gaussian Mixtures.
- Mark Girolami, Ata Kabán: Simplicial Mixtures of Markov Chains: Distributed Modelling of Dynamic User Profiles.
- David M. Blei, Thomas L. Griffiths, Michael I. Jordan, Joshua B. Tenenbaum: Hierarchical Topic Models and the Nested Chinese Restaurant Process.
- Kenji Fukumizu, Francis R. Bach, Michael I. Jordan: Kernel Dimensionality Reduction for Supervised Learning.
- Haifeng Li, Tao Jiang, Keshu Zhang: Efficient and Robust Feature Extraction by Maximum Margin Criterion.
- Thomas Strohmann, Andrei Belitski, Gregory Z. Grudic, Dennis DeCoste: Sparse Greedy Minimax Probability Machine Classification.
- Claudio Gentile: Fast Feature Selection from Microarray Expression Data via Multiplicative Large Margin Algorithms.
- Liva Ralaivola, Florence d'Alché-Buc: Dynamical Modeling with Kernels for Nonlinear Time Series Prediction.
- Denis V. Chigirev, William Bialek: Optimal Manifold Representation of Data: An Information Theoretic Approach.
- Dengyong Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, Bernhard Schölkopf: Ranking on Data Manifolds.
- Yoshua Bengio, Jean-François Paiement, Pascal Vincent, Olivier Delalleau, Nicolas Le Roux, Marie Ouimet: Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering.
- David Barber, Felix V. Agakov: The IM Algorithm: A Variational Approach to Information Maximization.
- Eiji Mizutani, James Demmel: Iterative Scaled Trust-Region Learning in Krylov Subspaces via Pearlmutter's Implicit Sparse Hessian-Vector Multiply.
- Yuanqing Li, Andrzej Cichocki, Shun-ichi Amari, Sergei L. Shishkin, Jianting Cao, Fanji Gu: Sparse Representation and Its Applications in Blind Source Separation.
- Charles Kemp, Thomas L. Griffiths, Sean Stromsten, Joshua B. Tenenbaum: Semi-Supervised Learning with Trees.
- Ting Liu, Andrew W. Moore, Alexander G. Gray: Efficient Exact k-NN and Nonparametric Classification in High Dimensions.
- Christopher J. Paciorek, Mark J. Schervish: Nonstationary Covariance Functions for Gaussian Process Regression.
- Jakob J. Verbeek, Sam T. Roweis, Nikos A. Vlassis: Non-linear CCA and PCA by Alignment of Local Models.
- Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal, Jason Weston, Bernhard Schölkopf: Learning with Local and Global Consistency.
- Neil D. Lawrence: Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data.
- Martin J. Wainwright, Michael I. Jordan: Semidefinite Relaxations for Approximate Inference on Graphs with Cycles.
- XuanLong Nguyen, Michael I. Jordan: On the Concentration of Expectation and Approximate Inference in Layered Networks.
- Radford M. Neal, Matthew J. Beal, Sam T. Roweis: Inferring State Sequences for Non-linear Systems with Embedded Hidden Markov Models.
- Pedro F. Felzenszwalb, Daniel P. Huttenlocher, Jon M. Kleinberg: Fast Algorithms for Large-State-Space HMMs with Applications to Web Usage Analysis.
- Mark A. Paskin: Sample Propagation.
- Amos J. Storkey: Generalised Propagation for Fast Fourier Transforms with Partial or Missing Data.
- Thore Graepel, Ralf Herbrich, Andriy Kharechko, John Shawe-Taylor: Semi-Definite Programming by Perceptron Learning.
- Noam Shental, Aharon Bar-Hillel, Tomer Hertz, Daphna Weinshall: Computing Gaussian Mixture Models with EM Using Equivalence Constraints.
- Matthew Brand: Minimax Embeddings.
- Ting-Fan Wu, Chih-Jen Lin, Ruby C. Weng: Probability Estimates for Multi-Class Classification by Pairwise Coupling.
- Rajat Raina, Yirong Shen, Andrew Y. Ng, Andrew McCallum: Classification with Hybrid Generative/Discriminative Models.
- John C. Platt: Fast Embedding of Sparse Similarity Graphs.
- Anton Schwaighofer, Marian Grigoras, Volker Tresp, Clemens Hoffmann: GPPS: A Gaussian Process Positioning System for Cellular Networks.
- David I. Ferguson, Aaron Morris, Dirk Hähnel, Christopher R. Baker, Zachary Omohundro, Carlos F. Reverte, Scott Thayer, Charles Whittaker, William Whittaker, Wolfram Burgard, Sebastian Thrun: An Autonomous Robotic System for Mapping Abandoned Mines.
- Jason Weston, Christina S. Leslie, Dengyong Zhou, André Elisseeff, William Stafford Noble: Semi-supervised Protein Classification Using Cluster Kernels.
- Alice X. Zheng, Michael I. Jordan, Ben Liblit, Alexander Aiken: Statistical Debugging of Sampled Programs.
- Nicholas P. Hughes, Lionel Tarassenko, Stephen J. Roberts: Markov Models for Automated ECG Interval Analysis.
- Cynthia Archer, Todd K. Leen, António M. Baptista: Parameterized Novelty Detectors for Environmental Sensor Monitoring.
- Benjamin M. Marlin: Modeling User Rating Profiles For Collaborative Filtering.
- Michael J. Quinlan, Stephan K. Chalup, Richard H. Middleton: Application of SVMs for Colour Classification and Collision Detection with AIBO Robots.
- Daniel B. Neill, Andrew W. Moore: A Fast Multi-Resolution Method for Detection of Significant Spatial Disease Clusters.
- Andrew Rabinovich, Sameer Agarwal, Casey Laris, Jeffrey H. Price, Serge Belongie: Unsupervised Color Decomposition Of Histologically Stained Tissue Samples.
- Darya Chudova, Christopher E. Hart, Eric Mjolsness, Padhraic Smyth: Gene Expression Clustering with Functional Mixture Models.
- Saori C. Tanaka, Kenji Doya, Go Okada, Kazutaka Ueda, Yasumasa Okamoto, Shigeto Yamawaki: Different Cortico-Basal Ganglia Loops Specialize in Reward Prediction at Different Time Scales.
- Xuerui Wang, Rebecca A. Hutchinson, Tom M. Mitchell: Training fMRI Classifiers to Discriminate Cognitive States across Multiple Subjects.
- Roland Vollgraf, Michael Scholz, Ian A. Meinertzhagen, Klaus Obermayer: Nonlinear Filtering of Electron Micrographs by Means of Support Vector Regression.
- Yu Zhou, Steven G. Mason, Gary E. Birch: Impact of an Energy Normalization Transform on the Performance of the LF-ASD Brain Computer Interface.
- Guido Dornhege, Benjamin Blankertz, Gabriel Curio, Klaus-Robert Müller: Increase Information Transfer Rates in BCI by CSP Extension to Multi-class.
- Sung Chan Jun, Barak A. Pearlmutter: Subject-Independent Magnetoencephalographic Source Localization by a Multilayer Perceptron.
- Maxim Likhachev, Geoffrey J. Gordon, Sebastian Thrun: ARA*: Anytime A* with Provable Bounds on Sub-Optimality.
- Andrew Y. Ng, H. Jin Kim, Michael I. Jordan, Shankar Sastry: Autonomous Helicopter Flight via Reinforcement Learning.
- Yu-Han Chang, Tracey Ho, Leslie Pack Kaelbling: All learning is Local: Multi-agent Learning in Global Reward Games.
- Daniela Pucci de Farias, Nimrod Megiddo: How to Combine Expert (and Novice) Advice when Actions Impact the Environment?
- J. Andrew Bagnell, Sham Kakade, Andrew Y. Ng, Jeff G. Schneider: Policy Search by Dynamic Programming.
- Arnab Nilim, Laurent El Ghaoui: Robustness in Markov Decision Problems with Uncertain Transition Matrices.
- Gerald Tesauro: Extending Q-Learning to General Adaptive Multi-Agent Systems.
- Curt A. Bererton, Geoffrey J. Gordon, Sebastian Thrun: Auction Mechanism Design for Multi-Robot Coordination.
- Milos Hauskrecht, Branislav Kveton: Linear Program Approximations for Factored Continuous-State Markov Decision Processes.
- Arnulf B. A. Graf, Felix A. Wichmann: Insights from Machine Learning Applied to Human Visual Classification.
- Virginia R. de Sa: Sensory Modality Segregation.
- Artur S. d'Avila Garcez, Luís C. Lamb: Reasoning about Time and Knowledge in Neural Symbolic Learning Systems.
- Marc Toussaint: Learning a World Model and Planning with a Self-Organizing, Dynamic Neural System.
- Woojae Kim, Daniel J. Navarro, Mark A. Pitt, In Jae Myung: An MCMC-Based Method of Comparing Connectionist Models in Cognitive Science.
- David Philipona, J. K. O'Regan, Jean-Pierre Nadal, Olivier J. M. D. Coenen: Perception of the Structure of the Physical World Using Unknown Multimodal Sensors and Effectors.
- Zach Solan, David Horn, Eytan Ruppin, Shimon Edelman: Unsupervised Context Sensitive Language Acquisition from a Large Corpus.
- Yuuya Sugita, Jun Tani: A Holistic Approach to Compositional Semantics: A Connectionist Model and Robot Experiments.
- Aaron C. Courville, Nathaniel D. Daw, Geoffrey J. Gordon, David S. Touretzky: Model Uncertainty in Classical Conditioning.
- Reid R. Harrison: A Low-Power Analog VLSI Visual Collision Detector.
- Rock Z. Shi, Timothy K. Horiuchi: A Summating, Exponentially-Decaying CMOS Synapse for Spiking Neural Systems.
- Hsin Chen, Patrice Fleury, Alan F. Murray: Minimising Contrastive Divergence in Noisy, Mixed-mode VLSI Neurons.
- Adria Bofill-i-Petit, Alan F. Murray: Synchrony Detection by Analogue VLSI Neurons with Bimodal STDP Synapses.
- Masakazu Yagi, Hideo Yamasaki, Tadashi Shibata: A Mixed-Signal VLSI for Real-Time Generation of Edge-Based Image Vectors.
- Francesco Tenore, Ralph Etienne-Cummings, M. Anthony Lewis: Entrainment of Silicon Central Pattern Generators for Legged Locomotory Control.
- Eric K. C. Tsang, Bertram Emil Shi: A Neuromorphic Multi-chip Model of a Disparity Selective Complex Cell.
- Ingo Steinwart: Sparseness of Support Vector Machines---Some Asymptotically Sharp Bounds.
- Tong Zhang: An Infinity-sample Theory for Multi-category Large Margin Classification.
- Philip Derbeko, Ran El-Yaniv, Ron Meir: Error Bounds for Transductive Learning via Compression and Clustering.
- David L. Donoho, Victoria Stodden: When Does Non-Negative Matrix Factorization Give a Correct Decomposition into Parts?
- Tong Zhang: Learning Bounds for a Generalized Family of Bayesian Posterior Distributions.
- Susanne Still, William Bialek, Léon Bottou: Geometric Clustering Using the Information Bottleneck Method.
- Peter L. Bartlett, Michael I. Jordan, Jon D. McAuliffe: Large Margin Classifiers: Convex Loss, Low Noise, and Convergence Rates.
- David C. Hoyle, Magnus Rattray: Limiting Form of the Sample Covariance Eigenspectrum in PCA and Kernel PCA.
- Dörthe Malzahn, Manfred Opper: Approximate Analytical Bootstrap Averages for Support Vector Classifiers.
- Justin Werfel, Xiaohui Xie, H. Sebastian Seung: Learning Curves for Stochastic Gradient Descent in Linear Feedforward Networks.
- Gal Chechik, Amir Globerson, Naftali Tishby, Yair Weiss: Information Bottleneck for Gaussian Variables.
- Yuval Aviel, David Horn, Moshe Abeles: The Doubly Balanced Network of Spiking Neurons: A Memory Model with High Capacity.
- Thomas Natschläger, Wolfgang Maass: Information Dynamics and Emergent Computation in Recurrent Circuits of Spiking Neurons.
- Peter J. Thomas, Donald J. Spencer, Sierra K. Hampton, Peter Park, Joseph P. Zurkus: The Diffusion-Limited Biochemical Signal-Relay Channel.
- Aaron J. Gruber, Peter Dayan, Boris S. Gutkin, Sara A. Solla: Dopamine Modulation in a Basal Ganglio-cortical Network Implements Saliency-based Gating of Working Memory.
- Nathan A. Dunn, John S. Conery, Shawn R. Lockery: Circuit Optimization Predicts Dynamic Network for Chemosensory Orientation in the Nematode C. elegans.
- Maneesh Sahani: A Biologically Plausible Algorithm for Reinforcement-shaped Representational Learning.
- Yoichi Miyawaki, Masato Okada: Mechanism of Neural Interference by Transcranial Magnetic Stimulation: Network or Single Neuron?
- Jonathan W. Pillow, Liam Paninski, Eero P. Simoncelli: Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model.
- Liam Paninski: Design of Experiments via Information Theory.
- Kazuyuki Samejima, Kenji Doya, Yasumasa Ueda, Minoru Kimura: Estimating Internal Variables and Paramters of a Learning Agent by a Particle Filter.
- Bernd Porr, Ausra Saudargiene, Florentin Wörgötter: Analytical Solution of Spike-timing Dependent Plasticity Based on Synaptic Biophysics.
- Brian J. Fischer, Charles H. Anderson: A Probabilistic Model of Auditory Space Representation in the Barn Owl.
- Ryan C. Kelly, Tai Sing Lee: Decoding V1 Neuronal Activity using Particle Filtering with Volterra Kernels.
- Jan Eichhorn, Andreas S. Tolias, Alexander Zien, Malte Kuss, Carl Edward Rasmussen, Jason Weston, Nikos K. Logothetis, Bernhard Schölkopf: Prediction on Spike Data Using Kernel Algorithms.
- William M. Campbell, Joseph P. Campbell, Douglas A. Reynolds, Douglas A. Jones, Timothy R. Leek: Phonetic Speaker Recognition with Support Vector Machines.
- Pedro J. Moreno, Purdy Ho, Nuno Vasconcelos: A Kullback-Leibler Divergence Based Kernel for SVM Classification in Multimedia Applications.
- Kannan Achan, Sam T. Roweis, Brendan J. Frey: Probabilistic Inference of Speech Signals from Phaseless Spectrograms.
- Jeff Bondy, Ian C. Bruce, Suzanna Becker, Simon Haykin: Predicting Speech Intelligibility from a Population of Neurons.
- Tomohiro Nakatani, Masato Miyoshi, Keisuke Kinoshita: One Microphone Blind Dereverberation Based on Quasi-periodicity of Speech Signals.
- Scott A. Beardsley, Lucia M. Vaina: A Functional Architecture for Motion Pattern Processing in MSTd.
- Alan L. Yuille, Fang Fang, Paul R. Schrater, Daniel Kersten: Human and Ideal Observers for Detecting Image Curves.
- Matthias H. Hennig, Florentin Wörgötter: Eye Micro-movements Improve Stimulus Detection Beyond the Nyquist Limit in the Peripheral Retina.
- Salvador Ruiz-Correa, Linda G. Shapiro, Marina Meila, Gabriel Berson: Discriminating Deformable Shape Classes.
- Kevin P. Murphy, Antonio Torralba, William T. Freeman: Graphical Model For Recognizing Scenes and Objects.
- Amit Gruber, Yair Weiss: Factorization with Uncertainty and Missing Data: Exploiting Temporal Coherence.
- Jianxin Wu, James M. Rehg, Matthew D. Mullin: Learning a Rare Event Detection Cascade by Direct Feature Selection.
- Sanjiv Kumar, Martial Hebert: Discriminative Fields for Modeling Spatial Dependencies in Natural Images.
- Leonid Sigal, Michael Isard, Benjamin H. Sigelman, Michael J. Black: Attractive People: Assembling Loose-Limbed Models using Non-parametric Belief Propagation.
- Gwen Littlewort, Marian Stewart Bartlett, Ian R. Fasel, Joel Chenu, Takayuki Kanda, Hiroshi Ishiguro, Javier R. Movellan: Towards Social Robots: Automatic Evaluation of Human-robot Interaction by Face Detection and Expression Classification.
- Anuj Srivastava, Xiuwen Liu, Washington Mio, Eric Klassen: A Computational Geometric Approach to Shape Analysis in Images.
- Lyndsey C. Pickup, Stephen J. Roberts, Andrew Zisserman: A Sampled Texture Prior for Image Super-Resolution.
- Charles R. Rosenberg, Thomas P. Minka, Alok Ladsariya: Bayesian Color Constancy with Non-Gaussian Models.
- Claudio Fanti, Marzia Polito, Pietro Perona: An Improved Scheme for Detection and Labelling in Johansson Displays.
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last updated on 2013-06-18T214307 by the dblp team