Where Does the Population Vector of Motor Cortical Cells Point during Reaching Movements? (English)
- New search for: Baraduc, P.
- New search for: Guigon, E.
- New search for: Burnod, Y.
- New search for: Baraduc, P.
- New search for: Guigon, E.
- New search for: Burnod, Y.
- New search for: Kearns, M. S.
- New search for: Solla, S. A.
- New search for: Cohn, D. A.
In:
Advances in neural information processing systems
11
;
83-89
;
1999
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ISBN:
-
ISSN:
- Conference paper / Print
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Title:Where Does the Population Vector of Motor Cortical Cells Point during Reaching Movements?
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Contributors:Baraduc, P. ( author ) / Guigon, E. ( author ) / Burnod, Y. ( author ) / Kearns, M. S. / Solla, S. A. / Cohn, D. A.
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Conference:Conference; 11th, Advances in neural information processing systems ; 1998 ; Denver, CO
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Published in:Advances in neural information processing systems , 11 ; 83-89ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS , 11 ; 83-89
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Publisher:
- New search for: MIT Press
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Publication date:1999-01-01
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Size:7 pages
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Remarks:Also known as NIPS
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ISBN:
-
ISSN:
-
Type of media:Conference paper
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Type of material:Print
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Language:English
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Keywords:
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Source:
© Metadata Copyright the British Library Board and other contributors. All rights reserved.
Table of contents conference proceedings
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 3
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Evidence for a Forward Dynamics Model in Human Adaptive Motor ControlBhushan, N. / Shadmehr, R. et al. | 1999
- 10
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Perceiving without Learning: From Spirals to Inside/Outside RelationsChen, K. / Wang, D. L. et al. | 1999
- 17
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A Model for Associative MultiplicationChristianson, G. B. / Becker, S. et al. | 1999
- 24
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Facial Memory Is Kernel Density Estimation (Almost)Dailey, M. N. / Cottrell, G. W. / Busey, T. A. et al. | 1999
- 31
-
Multiple Paired Forward-Inverse Models for Human Motor Learning and ControlHaruno, M. / Wolpert, D. M. / Kawato, M. et al. | 1999
- 38
-
Utilizing Time: Asynchronous BindingLove, B. C. et al. | 1999
- 45
-
Mechanisms of Generalization in Perceptual LearningLiu, Z. / Weinshall, D. et al. | 1999
- 52
-
A Principle for Unsupervised Hierarchical Decomposition of Visual ScenesMozer, M. C. et al. | 1999
- 59
-
Bayesian Modeling of Human Concept LearningTenenbaum, J. B. et al. | 1999
- 69
-
Temporally Asymmetric Hebbian Learning, Spike Timing and Neural Response VariabilityAbbott, L. F. / Song, S. et al. | 1999
- 76
-
Contrast Adaptation in Simple Cells by Changing the Transmitter Release ProbabilityAdorjan, P. / Obermayer, K. et al. | 1999
- 83
-
Where Does the Population Vector of Motor Cortical Cells Point during Reaching Movements?Baraduc, P. / Guigon, E. / Burnod, Y. et al. | 1999
- 90
-
Recurrent Cortical Amplification Produces Complex Cell ResponsesChance, F. S. / Nelson, S. B. / Abbott, L. F. et al. | 1999
- 97
-
Neuronal Regulation Implements Efficient Synaptic PruningChechik, G. / Meilijson, I. / Ruppin, E. et al. | 1999
- 104
-
Divisive Normalization, Line Attractor Networks and Ideal ObserversDeneve, S. / Pouget, A. / Latham, P. E. et al. | 1999
- 111
-
Synergy and Redundancy among Brain Cells of Behaving MonkeysGat, I. / Tishby, N. et al. | 1999
- 118
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Analyzing and Visualizing Single-Trial Event-Related PotentialsJung, T.-P. / Makeig, S. / Westerfield, M. / Townsend, J. / Courchesne, E. / Sejnowski, T. J. et al. | 1999
- 125
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Spike-Based Compared to Rate-Based Hebbian LearningKempter, R. / Gerstner, W. / van Hemmen, J. L. et al. | 1999
- 132
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Signal Detection in Noisy Weakly-Active DendritesManwani, A. / Koch, C. et al. | 1999
- 139
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The Role of Lateral Cortical Competition in Ocular Dominance DevelopmentPiepenbrock, C. / Obermayer, K. et al. | 1999
- 146
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Multi-Electrode Spike Sorting by Clustering Transfer FunctionsRinberg, D. / Davidowitz, H. / Tishby, N. et al. | 1999
- 153
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- 160
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Information Maximization in Single NeuronsStemmler, M. / Koch, C. et al. | 1999
- 167
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The Effect of Correlations on the Fisher Information of Population CodesYoon, H. / Sompolinsky, H. et al. | 1999
- 174
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Distributional Population Codes and Multiple Motion ModelsZemel, R. S. / Dayan, P. et al. | 1999
- 183
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Tractable Variational Structures for Approximating Graphical ModelsBarber, D. / Wiegerinck, W. et al. | 1999
- 190
-
Almost Linear VC Dimension Bounds for Piecewise Polynomial NetworksBartlett, P. L. / Maiorov, V. / Meir, R. et al. | 1999
- 197
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Dynamics of Supervised Learning with Restricted Training SetsCoolen, A. C. C. / Saad, D. et al. | 1999
- 204
-
Dynamically Adapting Kernels in Support Vector MachinesCristianini, N. / Campbell, C. / Shawe-Taylor, J. et al. | 1999
- 211
-
Phase Diagram and Storage Capacity of Sequence-Storing Neural NetworksDuring, A. / Coolen, A. C. C. / Sherrington, D. et al. | 1999
- 218
-
Finite-Dimensional Approximation of Gaussian ProcessesFerrari-Trecate, G. / Williams, C. K. I. / Opper, M. et al. | 1999
- 225
-
Linear Hinge Loss and Average MarginGentile, C. / Warmuth, M. K. et al. | 1999
- 232
-
Unsupervised and Supervised Clustering: The Mutual Information between Parameters and ObservationsHerschkowitz, D. / Nadal, J.-P. et al. | 1999
- 239
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Convergence of the Wake-Sleep AlgorithmIkeda, S. / Amari, S.-i. / Nakahara, H. et al. | 1999
- 246
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The Belief in TAPKabashima, Y. / Saad, D. et al. | 1999
- 253
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Optimizing Classifers for Imbalanced Training SetsKarakoulas, G. / Shawe-Taylor, J. et al. | 1999
- 260
-
Inference in Multilayer Networks via Large Deviation BoundsKearns, M. / Saul, L. et al. | 1999
- 267
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Stationarity and Stability of Autoregressive Neural Network ProcessesLeisch, F. / Trapletti, A. / Hornik, K. et al. | 1999
- 274
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Computational Differences between Asymmetrical and Symmetrical NetworksLi, Z. / Dayan, P. et al. | 1999
- 281
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A Precise Characterization of the Class of Languages Recognized by Neural Nets under Gaussian and Other Common Noise DistributionsMaass, W. / Sontag, E. D. et al. | 1999
- 288
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Direct Optimization of Margins Improves Generalization in Combined ClassifiersMason, L. / Bartlett, P. L. / Baxter, J. et al. | 1999
- 295
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On the Optimality of Incremental Neural Network AlgorithmsMeir, R. / Maiorov, V. et al. | 1999
- 302
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General Bounds on Bayes Errors for Regression with Gaussian ProcessesOpper, M. / Vivarelli, F. et al. | 1999
- 309
-
Mean Field Methods for Classification with Gaussian ProcessesOpper, M. / Winther, O. et al. | 1999
- 316
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On-Line Learning with Restricted Training Sets: Exact Solution as Benchmark for General TheoriesRae, H. C. / Sollich, P. / Coolen, A. C. C. et al. | 1999
- 323
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Tight Bounds for the VC-Dimension of Piecewise Polynomial NetworksSakurai, A. et al. | 1999
- 330
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Shrinking the Tube: A New Support Vector Regression AlgorithmScholkopf, B. / Bartlett, P. L. / Smola, A. J. / Williamson, R. et al. | 1999
- 337
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Discontinuous Recall Transitions Induced by Competition Between Short- and Long-Range Interactions in Recurrent NetworksSkantzos, N. S. / Beckmann, C. F. / Coolen, A. C. C. et al. | 1999
- 344
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Learning Curves for Gaussian ProcessesSollich, P. et al. | 1999
- 351
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A Theory of Mean Field ApproximationTanaka, T. et al. | 1999
- 361
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Learning a Hierarchical Belief Network of Independent Factor AnalyzersAttias, H. et al. | 1999
- 368
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- 375
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- 382
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- 389
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Learning Multi-Class DynamicsBlake, A. / North, B. / Isard, M. et al. | 1999
- 396
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Approximate Learning of Dynamic ModelsBoyen, X. / Koller, D. et al. | 1999
- 403
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Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and Learning in Nonlinear State Space ModelsBriegel, T. / Tresp, V. et al. | 1999
- 410
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Global Optimisation of Neural Network Models via Sequential Samplingde Freitas, J. F. G. / Niranjan, M. / Doucet, A. / Gee, A. H. et al. | 1999
- 417
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Efficient Bayesian Parameter Estimation in Large Discrete DomainsFriedman, N. / Singer, Y. et al. | 1999
- 424
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A Randomized Algorithm for Pairwise ClusteringGdalyahu, Y. / Weinshall, D. / Werman, M. et al. | 1999
- 431
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- 438
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Classification on Pairwise Proximity DataGraepel, T. / Herbrich, R. / Bollmann-Sdorra, P. / Obermayer, K. et al. | 1999
- 445
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Outcomes of the Equivalence of Adaptive Ridge with Least Absolute ShrinkageGrandvalet, Y. / Canu, S. et al. | 1999
- 452
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Visualizing Group StructureHeld, M. / Puzicha, J. / Buhmann, J. M. et al. | 1999
- 459
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Source Separation as a By-Product of RegularizationHochreiter, S. / Schmidhuber, J. et al. | 1999
- 466
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Learning from Dyadic DataHofmann, T. / Puzicha, J. / Jordan, M. I. et al. | 1999
- 473
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- 480
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Restructuring Sparse High Dimensional Data for Effective RetrievalIsbell, C. L. / Viola, P. et al. | 1999
- 487
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Exploiting Generative Models in Discriminative ClassifiersJaakkola, T. S. / Haussler, D. et al. | 1999
- 494
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Maximum Conditional Likelihood via Bound Maximization and the CEM AlgorithmJebara, T. / Pentland, A. et al. | 1999
- 501
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- 508
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Unsupervised Classification with Non-Gaussian Mixture Models Using ICALee, T.-W. / Lewicki, M. S. / Sejnowski, T. J. et al. | 1999
- 515
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Learning a Continuous Hidden Variable Model for Binary DataLee, D. D. / Sompolinsky, H. et al. | 1999
- 522
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Neural Networks for Density EstimationMagdon-Ismail, M. / Atiya, A. et al. | 1999
- 529
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Exploratory Data Analysis Using Radial Basis Function Latent Variable ModelsMarrs, A. D. / Webb, A. R. et al. | 1999
- 536
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Kernel PCA and De-Noising in Feature SpacesMika, S. / Scholkopf, B. / Smola, A. J. / Muller, K.-R. / Scholz, M. / Ratsch, G. et al. | 1999
- 543
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Very Fast EM-Based Mixture Model Clustering Using Multiresolution Kd-TreesMoore, A. W. et al. | 1999
- 550
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Replicator Equations, Maximal Cliques, and Graph IsomorphismPelillo, M. et al. | 1999
- 557
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Using Analytic QP and Sparseness to Speed Training of Support Vector MachinesPlatt, J. C. et al. | 1999
- 564
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Regularizing AdaBoostRatsch, G. / Onoda, T. / Muller, K.-R. et al. | 1999
- 571
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Boxlets: A Fast Convolution Algorithm for Signal Processing and Neural NetworksSimard, P. Y. / Bottou, L. / Haffner, P. / Le Cun, Y. et al. | 1999
- 578
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Batch and On-Line Parameter Estimation of Gaussian Mixtures Based on the Joint EntropySinger, Y. / Warmuth, M. K. et al. | 1999
- 585
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Semiparametric Support Vector and Linear Programming MachinesSmola, A. J. / Friess, T. T. / Scholkopf, B. et al. | 1999
- 592
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Probabilistic Visualisation of High-Dimensional Binary DataTipping, M. E. et al. | 1999
- 599
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SMEM Algorithm for Mixture ModelsUeda, N. / Nakano, R. / Ghahramani, Z. / Hinton, G. E. et al. | 1999
- 606
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Learning Mixture HierarchiesVasconcelos, N. / Lippman, A. et al. | 1999
- 613
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Discovering Hidden Features with Gaussian Processes RegressionVivarelli, F. / Williams, C. K. I. et al. | 1999
- 620
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The Bias-Variance Tradeoff and the Randomized GACVWahba, G. / Lin, X. / Gao, F. / Xiang, D. / Klein, R. / Klein, B. et al. | 1999
- 627
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Basis Selection for Wavelet RegressionWheeler, K. R. / Dhawan, A. P. et al. | 1999
- 634
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DTs: Dynamic TreesWilliams, C. K. I. / Adams, N. J. et al. | 1999
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Convergence Rates of Algorithms for Visual Search: Detecting Visual ContoursYuille, A. L. / Coughlan, J. M. et al. | 1999
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Blind Separation of Filtered Sources Using State-Space ApproachZhang, L. / Cichocki, A. et al. | 1999
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Analog VLSI Cellular Implementation of the Boundary Contour SystemCauwenberghs, G. / Waskiewicz, J. et al. | 1999
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A Micropower CMOS Adaptive Amplitude and Shift Invariant Vector QuantiserCoggins, R. J. / Wang, R. J. W. / Jabri, M. A. et al. | 1999
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A Neuromorphic Monaural Sound LocalizerHarris, J. G. / Pu, C.-J. / Principe, J. C. et al. | 1999
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