NECO 2010 - PDF Preprint Papers

NECO 2010

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NECO
2010

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Role of Homeostasis in Learning Sparse Representations

13 years 9 months ago

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Neurons in the input layer of primary visual cortex in primates develop edge-like receptive ﬁelds. One approach to understanding the emergence of this response is to state that ...

Laurent U. Perrinet

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Id	Views	Title	Status

1	154	Role of Homeostasis in Learning Sparse Representations	claim
2	147	Connectivity, Dynamics, and Memory in Reservoir Computing with Binary and Analog Neurons	claim
3	136	Learning to Represent Spatial Transformations with Factored Higher-Order Boltzmann Machines	claim
4	129	A Two-Layer Model of Natural Stimuli Estimated with Score Matching	claim
5	120	Supervised Learning in Spiking Neural Networks with ReSuMe: Sequence Learning, Classification, and Spike Shifting	claim
6	103	Posterior Weighted Reinforcement Learning with State Uncertainty	claim
7	103	Population Models of Temporal Differentiation	claim
8	101	Large-Margin Classification in Infinite Neural Networks	claim
9	97	Rademacher Chaos Complexities for Learning the Kernel Problem	claim
10	97	Derivatives of Logarithmic Stationary Distributions for Policy Gradient Reinforcement Learning	claim
11	92	Roles of Inhibitory Neurons in Rewiring-Induced Synchronization in Pulse-Coupled Neural Networks	claim
12	82	Deep Belief Networks Are Compact Universal Approximators	claim
13	79	Tractable Multivariate Binary Density Estimation and the Restricted Boltzmann Forest	claim
14	78	Hebbian Plasticity and Homeostasis in a Model of Hypercolumn of the Visual Cortex	claim
15	75	How to Modify a Neural Network Gradually Without Changing Its Input-Output Functionality	claim
16	73	The Neuronal Replicator Hypothesis	claim
17	72	Reward-Modulated Hebbian Learning of Decision Making	claim
18	71	Independent Vector Analysis for Source Separation Using a Mixture of Gaussians Prior	claim
19	69	Dynamics and Robustness of Familiarity Memory	claim
20	64	Topographic Mapping of Large Dissimilarity Data Sets	claim
21	64	On the Noise-Enhancing Ability of Stochastic Hodgkin-Huxley Neuron Systems	claim
22	61	Window-Based Example Selection in Learning Vector Quantization	claim
23	57	Timescale-Invariant Pattern Recognition by Feedforward Inhibition and Parallel Signal Processing	claim
24	56	On the Effects of Signal Acuity in a Multi-Alternative Model of Decision Making	claim
25	55	Optimal Decision Making on the Basis of Evidence Represented in Spike Trains	claim
26	53	Learning Spike-Based Population Codes by Reward and Population Feedback	claim
27	53	Sound Retrieval and Ranking Using Sparse Auditory Representations	claim
28	52	Hyperbolically Discounted Temporal Difference Learning	claim
29	51	Representation Sharpening Can Explain Perceptual Priming	claim
30	49	Phase Coupling Estimation from Multivariate Phase Statistics	claim
31	48	A Spiking Neuron as Information Bottleneck	claim
32	44	Precise Capacity Analysis in Binary Networks with Multiple Coding Level Inputs	claim

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