Table of Contents

• Relative Loss Bounds, the Minimum Relative Entropy Principle, and EMManfred K. Warmuth.
• DNA:::2:::DNA Computation: A Potential Killer Application?Richard J. Lipton.
• Psychological Studies of Visual PerceptionKen Nakayama.
• Odor Encoding by the Olfactory System - from Biology to a Receptorless Artificial NoseJohn Kauer.
• Learning in Rational AgentsStuart J. Russell.
• Inferring Sparse, Overcomplete Image Codes Using an Efficient Coding FrameworkMichael S. Lewicki, Bruno A. Olshausen.
• Synchronized Auditory and Cognitive 40 Hz Attentional Streams, and the Impact of Rhythmic Expectation on Auditory Scene AnalysisBill Baird. 3-9
• On Parallel versus Serial Processing: A Computational Study of Visual SearchEyal Cohen, Eytan Ruppin. 10-16
• Task and Spatial Frequency Effects on Face SpecializationMatthew N. Dailey, Garrison W. Cottrell. 17-23
• Neural Basis of Object-Centered RepresentationsSophie Deneve, Alexandre Pouget. 24-30
• A Neural Network Model of Naive Preference and Filial Imprinting in the Domestic ChickLucy E. Hadden. 31-37
• Adaptation in Speech Motor ControlJohn F. Houde, Michael I. Jordan. 38-44
• Learning Human-like Knowledge by Singular Value Decomposition: A Progress ReportThomas K. Landauer, Darrell Laham, Peter W. Foltz. 45-51
• Multi-modular Associative MemoryNir Levy, David Horn, Eytan Ruppin. 52-58
• Serial Order in Reading Aloud: Connectionist Models and Neighborhood StructureJeanne C. Milostan, Garrison W. Cottrell. 59-65
• A Superadditive-Impairment Theory of Optic AphasiaMichael Mozer, Mark Sitton, Martha J. Farah. 66-72
• A Hippocampal Model of Recognition MemoryRandall C. O Reilly, Kenneth A. Norman, James L. McClelland. 73-79
• Correlates of Attention in a Model of Dynamic Visual RecognitionRajesh P. N. Rao. 80-86
• Recurrent Neural Networks Can Learn to Implement Symbol-Sensitive CountingPaul Rodriguez, Janet Wiles. 87-93
• Comparison of Human and Machine Word RecognitionMarkus Schenkel, Cyril Latimer, Marwan A. Jabri. 94-100
• Coding of Naturalistic Stimuli by Auditory Midbrain NeuronsHagai Attias, Christoph E. Schreiner. 103-109
• Refractoriness and Neural PrecisionMichael J. Berry II, Markus Meister. 110-116
• Statistical Models of ConditioningPeter Dayan, Theresa Long. 117-123
• Characterizing Neurons in the Primary Auditory Cortex of the Awake Primate Using Reverse CorrelationR. Christopher DeCharms, Michael Merzenich. 124-130
• Using Helmholtz Machines to Analyze Multi-channel Neuronal RecordingsVirginia R. de Sa, R. Christopher DeCharms, Michael Merzenich. 131-137
• Instabilities in Eye Movement Control: A Model of Periodic Alternating NystagmusErnst R. Dow, Thomas J. Anastasio. 138-144
• Hippocampal Model of Rat Spatial Abilities Using Temporal Difference LearningDavid J. Foster, Richard G. M. Morris, Peter Dayan. 145-151
• Gradients for Retinotectal MappingGeoffrey J. Goodhill. 152-158
• A Mathematical Model of Axon Guidance by Diffusible FactorsGeoffrey J. Goodhill. 159-165
• Computing with Action PotentialsJohn J. Hopfield, Carlos D. Brody, Sam T. Roweis. 166-172
• A Model of Early Visual ProcessingLaurent Itti, Jochen Braun, Dale K. Lee, Christof Koch. 173-179
• Perturbative M-Sequences for Auditory Systems IdentificationMark Kvale, Christoph E. Schreiner. 180-186
• Effects of Spike Timing Underlying Binocular Integration and Rivalry in a Neural Model of Early Visual CortexErik D. Lumer. 187-193
• Dynamic Stochastic Synapses as Computational UnitsWolfgang Maass, Anthony M. Zador. 194-200
• Synaptic Transmission: An Information-Theoretic PerspectiveAmit Manwani, Christof Koch. 201-207
• Toward a Single-Cell Account for Binocular Disparity Tuning: An Energy Model May Be Hiding in Your DendritesBartlett W. Mel, Daniel L. Ruderman, Kevin A. Archie. 208-214
• Just One View: Invariances in Inferotemporal Cell TuningMaximilian Riesenhuber, Tomaso Poggio. 215-221
• On the Separation of Signals from Neighboring Cells in Tetrode RecordingsManeesh Sahani, John S. Pezaris, Richard A. Andersen. 222-228
• Independent Component Analysis for Identification of Artifacts in Magnetoencephalographic RecordingsRicardo Vigário, Veikko Jousmäki, Matti Hämäläinen, Riitta Hari, Erkki Oja. 229-235
• Modeling Complex Cells in an Awake Macaque during Natural Image ViewingWilliam E. Vinje, Jack L. Gallant. 236-242
• The Canonical Distortion Measure in Feature Space and 1-NN ClassificationJonathan Baxter, Peter L. Bartlett. 245-251
• Multiple Threshold Neural LogicVasken Bohossian, Jehoshua Bruck. 252-258
• Generalization in Decision Trees and DNF: Does Size Matter?Mostefa Golea, Peter L. Bartlett, Wee Sun Lee, Llew Mason. 259-265
• Selecting Weighting Factors in Logarithmic Opinion PoolsTom Heskes. 266-272
• New Approximations of Differential Entropy for Independent Component Analysis and Projection PursuitAapo Hyvärinen. 273-279
• Boltzmann Machine Learning Using Mean Field Theory and Linear Response CorrectionHilbert J. Kappen, Francisco de Borja Rodríguez Ortiz. 280-286
• Relative Loss Bounds for Multidimensional Regression ProblemsJyrki Kivinen, Manfred K. Warmuth. 287-293
• Asymptotic Theory for Regularization: One-Dimensional Linear CasePetri Koistinen. 294-300
• Two Approaches to Optimal AnnealingTodd K. Leen, Bernhard Schottky, David Saad. 301-307
• Structural Risk Minimization for Nonparametric Time Series PredictionRon Meir. 308-314
• Analytical Study of the Interplay between Architecture and PredictabilityAvner Priel, Ido Kanter, David A. Kessler. 315-321
• Globally Optimal On-line Learning RulesMagnus Rattray, David Saad. 322-328
• Minimax and Hamiltonian Dynamics of Excitatory-Inhibitory NetworksH. Sebastian Seung, Tom J. Richardson, J. C. Lagarias, John J. Hopfield. 329-335
• Data-Dependent Structural Risk Minimization for Perceptron Decision TreesJohn Shawe-Taylor, Nello Cristianini. 336-342
• From Regularization Operators to Support Vector KernelsAlex J. Smola, Bernhard Schölkopf. 343-349
• The Rectified Gaussian DistributionNicholas D. Socci, Daniel D. Lee, H. Sebastian Seung. 350-356
• On-line Learning from Finite Training Sets in Nonlinear NetworksPeter Sollich, David Barber. 357-363
• Competitive On-line Linear RegressionVolodya Vovk. 364-370
• On the Infeasibility of Training Neural Networks with Small Squared ErrorsVan H. Vu. 371-377
• The Storage Capacity of a Fully-Connected Committee MachineYuansheng Xiong, Chulan Kwon, Jong-Hoon Oh. 378-384
• The Efficiency and the Robustness of Natural Gradient Descent Learning RuleHoward Hua Yang, Shun-ichi Amari. 385-391
• Ensemble Learning for Multi-Layer NetworksDavid Barber, Christopher M. Bishop. 395-401
• Radial Basis Functions: A Bayesian TreatmentDavid Barber, Bernhard Schottky. 402-408
• Shared Context Probabilistic TransducersYoshua Bengio, Samy Bengio, Jean-Franc Isabelle, Yoram Singer. 409-415
• Approximating Posterior Distributions in Belief Networks Using MixturesChristopher M. Bishop, Neil D. Lawrence, Tommi Jaakkola, Michael I. Jordan. 416-422
• Receptive Field Formation in Natural Scene Environments: Comparison of Single Cell Learning RulesBrian S. Blais, Nathan Intrator, Harel Z. Shouval, Leon N. Cooper. 423-429
• An Annealed Self-Organizing Map for Source Channel CodingMatthias Burger, Thore Graepel, Klaus Obermayer. 430-436
• Incorporating Test Inputs into LearningZehra Cataltepe, Malik Magdon-Ismail. 437-443
• On Efficient Heuristic Ranking of HypothesesSteve A. Chien, Andre Stechert, Darren Mutz. 444-450
• Learning to Order ThingsWilliam W. Cohen, Robert E. Schapire, Yoram Singer. 451-457
• Regularisation in Sequential Learning AlgorithmsJoão F. G. de Freitas, Mahesan Niranjan, Andrew H. Gee. 458-464
• Agnostic Classification of Markovian SequencesRan El-Yaniv, Shai Fine, Naftali Tishby. 465-471
• Ensemble and Modular Approaches for Face Detection: A ComparisonRaphaël Feraud, Olivier Bernier. 472-478
• A Revolution: Belief Propagation in Graphs with CyclesBrendan J. Frey, David J. C. MacKay. 479-485
• Hierarchical Non-linear Factor Analysis and Topographic MapsZoubin Ghahramani, Geoffrey E. Hinton. 486-492
• Regression with Input-dependent Noise: A Gaussian Process TreatmentPaul W. Goldberg, Christopher K. I. Williams, Christopher M. Bishop. 493-499
• Linear Concepts and Hidden Variables: An Empirical StudyAdam J. Grove, Dan Roth. 500-506
• Classification by Pairwise CouplingTrevor Hastie, Robert Tibshirani. 507-513
• Unsupervised On-line Learning of Decision Trees for Hierarchical Data AnalysisMarcus Held, Joachim M. Buhmann. 514-520
• Nonlinear Markov Networks for Continuous VariablesReimar Hofmann, Volker Tresp. 521-527
• Active Data ClusteringThomas Hofmann, Joachim M. Buhmann. 528-534
• Function Approximation with the Sweeping Hinge AlgorithmDon R. Hush, Fernando Lozano, Bill G. Horne. 535-541
• The Error Coding and Substitution PaCTsGareth James, Trevor Hastie. 542-548
• S-Map: A Network with a Simple Self-Organization Algorithm for Generative Topographic MappingsKimmo Kiviluoto, Erkki Oja. 549-555
• Learning Nonlinear Overcomplete Representations for Efficient CodingMichael S. Lewicki, Terrence J. Sejnowski. 556-562
• Factorizing Multivariate Function ClassesJuan K. Lin. 563-569
• A Framework for Multiple-Instance LearningOded Maron, Tomás Lozano-Pérez. 570-576
• An Application of Reversible-Jump MCMC to Multivariate Spherical Gaussian MixturesAlan D. Marrs. 577-583
• Estimating Dependency Structure as a Hidden VariableMarina Meila, Michael I. Jordan. 584-590
• Combining Classifiers Using Correspondence AnalysisChristopher J. Merz. 591-597
• Learning Path Distributions Using Nonequilibrium Diffusion NetworksPaul Mineiro, Javier R. Movellan, Ruth J. Williams. 598-604
• Learning Generative Models with the Up-Propagation AlgorithmJong-Hoon Oh, H. Sebastian Seung. 605-611
• An Incremental Nearest Neighbor Algorithm with QueriesJoel Ratsaby. 612-618
• RCC Cannot Compute Certain FSA, Even with Arbitrary Transfer FunctionsMark Ring. 619-625
• EM Algorithms for PCA and SPCASam T. Roweis. 626-632
• Local Dimensionality ReductionStefan Schaal, Sethu Vijayakumar, Christopher G. Atkeson. 633-639
• Prior Knowledge in Support Vector KernelsBernhard Schölkopf, Patrice Simard, Alex J. Smola, Vladimir Vapnik. 640-646
• Training Methods for Adaptive Boosting of Neural NetworksHolger Schwenk, Yoshua Bengio. 647-653
• Learning Continuous Attractors in Recurrent NetworksH. Sebastian Seung. 654-660
• Monotonic NetworksJoseph Sill. 661-667
• Stacked Density EstimationPadhraic Smyth, David Wolpert. 668-674
• Bidirectional Retrieval from Associative MemoryFriedrich T. Sommer, Günther Palm. 675-681
• Mapping a Manifold of Perceptual ObservationsJoshua B. Tenenbaum. 682-688
• Graph Matching with Hierarchical Discrete RelaxationRichard C. Wilson, Edwin R. Hancock. 689-695
• Multiplicative Updating Rule for Blind Separation Derived from the Method of ScoringHoward Hua Yang. 696-702
• A 1, 000-Neuron System with One Million 7-bit Physical InterconnectionsYuzo Hirai. 705-711
• Silicon Retina with Adaptive Filtering PropertiesShih-Chii Liu. 712-718
• Analog VLSI Model of Intersegmental Coordination with Nearest-Neighbor CouplingGirish N. Patel, Jeremy H. Holleman, Stephen P. DeWeerth. 719-725
• An Analog VLSI Neural Network for Phase-based Machine VisionBertram Emil Shi, Kwok Fai Hui. 726-732
• Analysis of Drifting Dynamics with Neural Network Hidden Markov ModelsJens Kohlmorgen, Klaus-Robert Müller, Klaus Pawelzik. 735-741
• Bayesian Robustification for Audio Visual FusionJavier R. Movellan, Paul Mineiro. 742-748
• Modeling Acoustic Correlations by Factor AnalysisLawrence K. Saul, Mazin G. Rahim. 749-755
• Blind Separation of Radio Signals in Fading ChannelsKari Torkkola. 756-762
• Hybrid NN/HMM-Based Speech Recognition with a Discriminant Neural Feature ExtractionDaniel Willett, Gerhard Rigoll. 763-769
• A Non-Parametric Multi-Scale Statistical Model for Natural ImagesJeremy S. De Bonet, Paul A. Viola. 773-779
• Recovering Perspective Pose with a Dual Step EM AlgorithmAndrew D. J. Cross, Edwin R. Hancock. 780-786
• Bayesian Model of Surface PerceptionWilliam T. Freeman, Paul A. Viola. 787-793
• Features as Sufficient StatisticsDavi Geiger, Archisman Rudra, Laurance T. Maloney. 794-800
• Detection of First and Second Order MotionAlexander Grunewald, Heiko Neumann. 801-807
• A Simple and Fast Neural Network Approach to StereovisionRolf D. Henkel. 808-814
• Visual Navigation in a Robot Using Zig-Zag BehaviorM. Anthony Lewis. 822-828
• 2D Observers for Human 3D Object Recognition?Zili Liu, Daniel Kersten. 829-835
• Self-similarity Properties of Natural ImagesAntonio Turiel, Germán Mato, Néstor Parga, Jean-Pierre Nadal. 836-842
• Multiresolution Tangent Distance for Affine-invariant ClassificationNuno Vasconcelos, Andrew Lippman. 843-849
• Phase Transitions and the Perceptual Organization of Video SequencesYair Weiss. 850-856
• Using Expectation to Guide Processing: A Study of Three Real-World ApplicationsShumeet Baluja. 859-865
• Structure Driven Image Database RetrievalJeremy S. De Bonet, Paul A. Viola. 866-872
• A General Purpose Image Processing Chip: Orientation DetectionRalph Etienne-Cummings, Donghui Cai. 873-879
• An Analog VLSI Model of the Fly Elementary Motion DetectorReid R. Harrison, Christof Koch. 880-886
• MELONET I: Neural Nets for Inventing Baroque-Style Chorale VariationsDominik Hörnel. 887-893
• Extended ICA Removes Artifacts from Electroencephalographic RecordingsTzyy-Ping Jung, Colin Humphries, Te-Won Lee, Scott Makeig, Martin J. McKeown, Vicente Iragui, Terrence J. Sejnowski. 894-900
• A Generic Approach for Identification of Event Related Brain Potentials via a Competitive Neural Network StructureDaniel H. Lange, Hava T. Siegelmann, Hillel Pratt, Gideon F. Inbar. 901-907
• A Neural Network Based Head Tracking SystemDaniel D. Lee, H. Sebastian Seung. 908-914
• Wavelet Models for Video Time-SeriesSheng Ma, Chuanyi Ji. 915-921
• Reinforcement Learning for Call Admission Control and Routing in Integrated Service NetworksPeter Marbach, Oliver Mihatsch, Miriam Schulte, John N. Tsitsiklis. 922-928
• Learning to Schedule Straight-Line CodeJ. Eliot B. Moss, Paul E. Utgoff, John Cavazos, Doina Precup, Darko Stefanovic, Carla E. Brodley, David Scheeff. 929-935
• Enhancing Q-Learning for Optimal Asset AllocationRalph Neuneier. 936-942
• Intrusion Detection with Neural NetworksJake Ryan, Meng-Jang Lin, Risto Miikkulainen. 943-949
• Incorporating Contextual Information in White Blood Cell IdentificationXubo B. Song, Yaser S. Abu-Mostafa, Joseph Sill, Harvey Kasdan. 950-956
• Bach in a Box - Real-Time HarmonyRandall R. Spangler, Rodney M. Goodman, Jim Hawkins. 957-963
• Experiences with Bayesian Learning in a Real World ApplicationPeter Sykacek, Georg Dorffner, Peter Rappelsberger, Josef Zeitlhofer. 964-970
• A Solution for Missing Data in Recurrent Neural Networks with an Application to Blood Glucose PredictionVolker Tresp, Thomas Briegel. 971-977
• Use of a Multi-Layer Perceptron to Predict Malignancy in Ovarian TumorsHerman Verrelst, Yves Moreau, Joos Vandewalle, Dirk Timmerman. 978-984
• Modelling Seasonality and Trends in Daily Rainfall DataPeter M. Williams. 985-991
• The Observer-Observation Dilemma in Neuro-ForecastingHans-Georg Zimmermann, Ralph Neuneier. 992-998
• Generalized Prioritized SweepingDavid Andre, Nir Friedman, Ronald Parr. 1001-1007
• Nonparametric Model-Based Reinforcement LearningChristopher G. Atkeson. 1008-1014
• An Improved Policy Iteration Algorithm for Partially Observable MDPsEric A. Hansen. 1015-1021
• Automated Aircraft Recovery via Reinforcement Learning: Initial ExperimentsJeffrey F. Monaco, David G. Ward, Andrew G. Barto. 1022-1028
• Reinforcement Learning for Continuous Stochastic Control ProblemsRémi Munos, Paul Bourgine. 1029-1035
• Adaptive Choice of Grid and Time in Reinforcement LearningStephan Pareigis. 1036-1042
• Reinforcement Learning with Hierarchies of MachinesRonald Parr, Stuart J. Russell. 1043-1049
• Multi-time Models for Temporally Abstract PlanningDoina Precup, Richard S. Sutton. 1050-1056
• How to Dynamically Merge Markov Decision ProcessesSatinder P. Singh, David Cohn. 1057-1063
• The Asymptotic Convergence-Rate of Q-learningCsaba Szepesvári. 1064-1070
• Hybrid Reinforcement Learning and Its Application to Biped Robot ControlSatoshi Yamada, Akira Watanabe, Michio Nakashima. 1071-1077