- ENFORCING EFFECTIVE SYNAPTIC LEARNING VIA A NEURONAL REGULATION MECHANISM
- )C. Shannon, 1949(, .
- Effective Learning Requires Neuronal Remodeling of Hebbian Synapses
- Efficient Synaptic Pruning with Neuronal Regulation Gal Chechik Isaac Meilijson and Eytan Ruppin \Lambda
- Maxmargin classification of incomplete data Gal Chechik 1 , Geremy Heitz 2 ,
- Gaussian Information Bottleneck Information Bottleneck for Gaussian Variables
- Discrete profile comparison using information bottleneck Sean O'Rourke1
- motor response that leads to the same reinforcement for the mouse. We speculate that there may be an added
- Timing properties of gene expression responses to environmental changes
- Temporally Dependent Plasticity: An Information Theoretic Account
- Sufficient Dimensionality Reduction with Irrelevance Statistics
- This article was originally published in a journal published by Elsevier, and the attached copy is provided by Elsevier for the
- E ective Neuronal Learning with Ine ective Hebbian Learning Rules
- Synaptic Pruning in Development: A Computational account
- E ective And Optimal Storage of Memory Patterns With Variable Coding Levels
- , )stochastic { , }tX t T= X ,
- Euclidean Embedding of Cooccurrence Data Amir Globerson 1 Gal Chechik 2 Fernando Pereira 3 Naftali Tishby 1
- Large-Scale Content-Based Audio Retrieval from Text Queries
- Activity motifs reveal principles of timing in transcriptional control of the yeast metabolic network
- Extracting relevant structures with side information
- Beyond Hebbian plasticity: Effective learning with ineffective Hebbian learning rules
- Gaussian Information Bottleneck Information Bottleneck for Gaussian Variables
- SpikeTiming Dependent Plasticity and Relevant Mutual Information Maximization
- Neuronal Normalization Provides Effective Learning Through
- Tel Aviv University The Raymond and Beverly Sackler
- A Needle in a Haystack: Local OneClass Optimization Koby Crammer KOBICS@CS.HUJI.IL
- Neuronal Regulation: A Mechanism For Synaptic Pruning During Brain Maturation
- Information Bottleneck for Gaussian Variables
- Filling missing components in yeast metabolic pathways using heterogeneous data
- Discrete profile alignment via constrained information bottleneck
- Synaptic Pruning in Development: A Novel Account in Neural Terms
- An Information Theoretic Approach to the Study
- An Information Theoretic Approach to the Study
- Effective And Optimal Storage of Memory Patterns With Variable Coding Levels
- A Needle in a Haystack: Local One-Class Optimization Koby Crammer KOBICS@CS.HUJI.IL
- -p, . ., ( )1 2, ,..., n =
- Embedding Heterogeneous Data using Statistical Models Amir Globerson1
- Extracting relevant structures A key problem in understanding auditory coding is to identify the acoustic features
- )statistical inference( . i j =j =
- The primary goal of this thesis was to identify computational principles that govern information processing and representation in the auditory system.
- Information Theoretic Approach to the Study of Auditory Coding
- Neuronal Regulation Implements Efficient Synaptic Pruning
- Max-margin classification of incomplete data Gal Chechik1
- Are There Representations in Embodied Evolved Agents? Taking Measures
- Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks
- Journal of Machine Learning Research 1 (2009) XX-YY Submitted 2/2009; Published 9/2009 Large Scale Online Learning
- Max-margin classification of data with absent features Gal Chechik gal@cs.stanford.edu
- Spike-Timing Dependent Plasticity and Relevant Mutual Information Maximization
- Effective Neuronal Learning with Ineffective Hebbian Learning Rules
- Discrete profile alignment via constrained information bottleneck
- Information Bottleneck for Gaussian Variables
- Temporally Dependent Plasticity: An Information Theoretic Account
- Introduction 1.1 Computation in the brain
- Extracting Information From Spike Trains
- Chapter 3 January 22, 2004 58 Quantifying Coding
- Information Theory A.1 Entropy
- ., "1" -1/6 ,
- ML , , ) -1922(
- Journal of Machine Learning Research 9 (2008) 1-21 Submitted 3/06; Revised 8/06; Published 1/08 Max-margin Classification of Data with Absent Features
- LETTER Communicated by David Horn Spike-Timing-Dependent Plasticity and Relevant Mutual
- Beyond Hebbian plasticity: Effective learning with ineffective Hebbian learning rules
- Are Scale-Free Networks Functionally Robust? Alon Keinan1
- Optimality, Robustness, and Noise in Metabolic Network Control
- CVPR 2010 Submission #983. CONFIDENTIAL REVIEW COPY. DO NOT DISTRIBUTE. Object Separation in X-Ray Image Sets
- Sucient Dimensionality Reduction with Irrelevance Statistics
- Extracting relevant structures with side information
- Extracting relevant structures with side information
- Extracting relevant structures with side information
- Supplemental Material for the paper: Online Learning in The Manifold of
- Neuron 51, 359368, August 3, 2006 2006 Elsevier Inc. DOI 10.1016/j.neuron.2006.06.030 Reduction of Information Redundancy
- Group Redundancy Measures Reveal Redundancy Reduction in the Auditory
- Neuronal Regulation: A Mechanism For Synaptic Pruning During Brain Maturation
- Online Learning in the Manifold of Low-Rank Matrices
- Maxmargin classification of data with absent features Maxmargin classification of data with absent features
- Euclidean Embedding of Co-occurrence Data Amir Globerson1
