about
A neural probabilistic language modelAlgorithms for non-negative matrix factorizationComputing with Finite and Infinite NetworksEnsemble Learning and Linear Response Theory for ICAGeneralizable Singular Value Decomposition for Ill-posed DatasetsWho Does What? A Novel Algorithm to Determine Function LocalizationA Productive, Systematic Framework for the Representation of Visual StructureThe Interplay of Symbolic and Subsymbolic Processes in Anagram Problem SolvingHippocampally-Dependent Consolidation in a Hierarchical Model of NeocortexPosition Variance, Recurrence and Perceptual LearningThe Use of MDL to Select among Computational Models of CognitionActive Inference in Concept LearningThe Early Word Catches the WeightsStructure Learning in Human Causal InductionAdaptive Object Representation with Hierarchically-Distributed Memory SitesWhat Can a Single Neuron Compute?Dendritic Compartmentalization Could Underlie Competition and Attentional Biasing of Simultaneous Visual StimuliPlace Cells and Spatial Navigation Based on 2D Visual Feature Extraction, Path Integration, and Reinforcement LearningModelling Spatial Recall, Mental Imagery and NeglectStability and Noise in Biochemical SwitchesTemporally Dependent Plasticity: An Information Theoretic AccountA New Model of Spatial Representation in Multimodal Brain AreasMultiple Timescales of Adaptation in a Neural CodeDopamine BonusesFinding the Key to a SynapseProcessing of Time Series by Neural Circuits with Biologically Realistic Synaptic DynamicsSpike-Timing-Dependent Learning for Oscillatory NetworksUniversality and Individuality in a Neural CodeNatural Sound Statistics and Divisive Normalization in the Auditory SystemWhence Sparseness?Efficient Learning of Linear PerceptronsAlgorithmic Stability and Generalization PerformanceCompetition and Arbors in Ocular DominanceFrom Margin to SparsityPermitted and Forbidden Sets in Symmetric Threshold-Linear NetworksA PAC-Bayesian Margin Bound for Linear Classifiers: Why SVMs workOn Reversing Jensen's InequalitySecond Order Approximations for Probability ModelsSome New Bounds on the Generalization Error of Combined ClassifiersSparsity of Data Representation of Optimal Kernel Machine and Leave-one-out Estimator
P1433
Q33039506-739b7da0-448e-496f-1883-46f0b181caceQ42307043-cec6e505-4043-9123-eecb-c2b998e23cf2Q57746288-25A42B76-C24E-469E-A3CC-7A222B0C84F5Q57746316-039D1D2A-3A54-4CA9-AE4C-DC5CF0314D2DQ76450521-3EBF5E10-DD06-48D4-9CF3-DC0F9281C480Q77694934-8C3FA2DE-3A49-4ABE-9BCF-6195FEAB77C7Q77694939-7FE1199B-E7FB-4DAB-BDF1-A5B921C8CAD9Q77694940-7F2CA783-6C9E-4405-9FB8-827BE61235F6Q77694941-7EA8A789-6E10-4438-A1CF-3DB7642C8866Q77694942-7C5037C5-C106-41BB-BF40-F937B7AADFC4Q77694944-A003F78F-5095-45BC-8153-BF3D605CB44CQ77694945-6C78A45E-6947-4188-B232-C169707E56CFQ77694946-D606BFC2-8188-4E89-8B6E-CEDEBBF9C2F9Q77694947-D15AD34B-4A93-4721-893D-4BFD8A576CE6Q77694948-2EC4467B-5EF9-4BC3-B36A-665B2A95240FQ77694949-05F8F463-1661-4103-AB6D-A312DD667F87Q77694950-545655ED-40C7-4AF5-B0B2-56591F7F9287Q77694951-C5DC3D44-4D19-48AB-8B40-686C97C24BE0Q77694953-D3382497-C27B-44F1-AC15-771F7EC8624FQ77694955-2F99F64B-6CDC-4AD7-87DC-E25F02FE729DQ77694957-35B22BD1-368F-415E-9EE4-D0A6706BBF77Q77694961-997E85C1-9EB3-41B5-B653-88205B0AE18DQ77694962-8BDF68E5-C61F-4C8A-B615-46F2C22BAF7BQ77694963-A25933C5-D2D2-4F4D-A705-771E87EE56C3Q77694966-DCEB73D5-2F35-4BB2-836A-6D3AD8446A7BQ77694970-248A9B71-71C6-4F27-B9AC-201B4307D630Q77694972-EDB7651E-5E0A-4511-8FBB-A12655DC506FQ77694976-72B5377F-84B2-4FF3-B485-E494A1553122Q77694978-58CA6D6F-A4BF-4323-8F8B-07B3C421AAF7Q77694981-AEAD78CE-3870-4F17-B7A8-038A5DAEC9BCQ77694984-21FEB752-19F6-4B0F-8954-626A20171649Q77694986-083E3ED2-0885-4D15-A082-70587AC775ECQ77694990-A5963951-3CE3-43F5-83B9-91732A446EBBQ77694992-F730D925-AF1C-4BC9-8EDA-20A90D1E8941Q77694995-EB352053-6BCE-4E7E-8BE1-6BB3787A9F60Q77694998-BA19AAA7-7887-40F8-85C9-D9817B068DA7Q77695000-BCC11B70-1590-4757-92EF-D58142AF09D5Q77695003-2D045288-9A7A-46E3-AE90-FF719EB9B08BQ77695006-0F65A630-09D2-4F55-8A1E-E8BDD731C08EQ77695010-9030C1D3-DF00-4D80-B121-ECF0FCEFC40A
P1433
description
NIPS 2000 proceedings
@da
proceedings from NIPS 2000
@en
name
Advances in Neural Information Processing Systems 13
@da
Advances in Neural Information Processing Systems 13
@de
Advances in Neural Information Processing Systems 13
@en
Advances in Neural Information Processing Systems 13
@fo
Advances in Neural Information Processing Systems 13
@fr
Advances in Neural Information Processing Systems 13
@is
Advances in Neural Information Processing Systems 13
@kl
Advances in Neural Information Processing Systems 13
@nb
Advances in Neural Information Processing Systems 13
@nl
Advances in Neural Information Processing Systems 13
@nn
type
label
Advances in Neural Information Processing Systems 13
@da
Advances in Neural Information Processing Systems 13
@de
Advances in Neural Information Processing Systems 13
@en
Advances in Neural Information Processing Systems 13
@fo
Advances in Neural Information Processing Systems 13
@fr
Advances in Neural Information Processing Systems 13
@is
Advances in Neural Information Processing Systems 13
@kl
Advances in Neural Information Processing Systems 13
@nb
Advances in Neural Information Processing Systems 13
@nl
Advances in Neural Information Processing Systems 13
@nn
altLabel
NIPS 2000
@da
NIPS 2000
@de
NIPS 2000
@en
prefLabel
Advances in Neural Information Processing Systems 13
@da
Advances in Neural Information Processing Systems 13
@de
Advances in Neural Information Processing Systems 13
@en
Advances in Neural Information Processing Systems 13
@fo
Advances in Neural Information Processing Systems 13
@fr
Advances in Neural Information Processing Systems 13
@is
Advances in Neural Information Processing Systems 13
@kl
Advances in Neural Information Processing Systems 13
@nb
Advances in Neural Information Processing Systems 13
@nl
Advances in Neural Information Processing Systems 13
@nn
P98
P1476
Advances in Neural Information Processing Systems 13
@en
P1813
NIPS 2000
@en
P31
P407
P577
2000-12-01T00:00:00Z