Gal Chechik
- Research Area(s)
- Machine Intelligence
- Machine Perception
- General Science
Co-Authors
See his Stanford page and list of publications.
Google Publications
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Learning Semantic Representations Of Objects And Their Parts.
G Mesnil, Antoine Bordes, Jason Weston, Gal Chechik, Yoshua Bengio
Special Issue on Learning Semantics in Machine Learning Journal (2013) (to appear)
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Online Learning in the Manifold of Low-Rank Matrices
Gal Chechik, Daphna Weinshall, Uri Shalit
Neural Information Processing Systems (NIPS 23), Curran Associates, Inc. (2011), pp. 2128-2136
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Sparse coding of auditory features for machine hearing in interference
Richard F. Lyon, Gal Chechik, Jay Ponte
Proc. ICASSP, IEEE (2011)
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Large Scale Online Learning of Image Similarity Through Ranking
Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio
Journal of Machine Learning Research, JMLR (2010), pp. 1109-1135
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Sound Retrieval and Ranking Using Sparse Auditory Representations
Richard F Lyon, Martin Rehn, Samy Bengio, Thomas C. Walters, Gal Chechik
Neural Computation, vol. 22 (2010), pp. 2390-2416
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An Online Algorithm for Large Scale Image Similarity Learning
Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio
Advances in Neural Information Processing Systems (2009)
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Large Scale Online Learning of Image Similarity Through Ranking: Extended Abstract
Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio
4th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA (2009)
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Sound Ranking Using Auditory Sparse-Code Representations
Martin Rehn, Richard F. Lyon, Samy Bengio, Thomas C. Walters, Gal Chechik
ICML 2009 Workshop on Sparse Method for Music Audio
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Timing properties of gene expression responses to environmental changes
Gal Chechik, Daphne Koller
J. Computational Biology, vol. 9 (2009)
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Gal Chechik, Eugene Oh, Oliver Rando, Jonathan Weissman, Aviv Regev, Daphne Koller
Nature Biotechnology, vol. 26 (11) (2008), pp. 1251-1259
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Large Scale Content-Based Audio Retrieval from Text Queries
Gal Chechik, Eugene Ie, Martin Rehn, Samy Bengio, Richard F. Lyon
ACM International Conference on Multimedia Information Retrieval (MIR), ACM (2008)
Previous Publications
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Max-margin classification of data with absent features
G. Chechik, G. Heitz, G. Elidan, P. Abbeel, D. Koller
Journal of Machine Learning Research, vol. 9 (2008), pp. 1-21
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Euclidean Embedding of Co-occurrence Data
Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby
Journal of Machine Learning Research, vol. 8 (2007), pp. 2265-2295
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Tuned protein variability in yeast metabolism
G. Chechik, M. Chen, D. Koller
8th International Conference on Systems Biology (2007)
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Information theory in auditory research
I. Nelken, G. Chechik
Hearing Research, vol. 229 (2007), pp. 94-105
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Max-margin classification of incomplete data
G. Chechik, G. Heitz, G. Elidan, P. Abbeel, D. Koller
Advances in Neural Information Processing Systems: Proceedings of the 2006 Conference (2007)
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NIPS workshop on New Problems and Methods in Computational Biology
G. Chechik, C. Leslie, W.S. Noble, G. R{\, Q. Morris, K. Tsuda
BMC Bioinformatics, vol. 8 (2007), S1
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Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks
A. Battle, G. Chechik, D. Koller
Advances in Neural Information Processing Systems: Proceedings of the 2006 Conference, MIT Press (2007)
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Discrete profile comparison using information bottleneck
Sean O'rourke, Gal Chechik, Robin Friedman, Elazar Eskin
BMC Bioinformatics, vol. 7 (2006)
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Embedding Heterogeneous Data Using Statistical Models
Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby
AAAI (2006)
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Discrete profile comparison using information bottleneck
O.R. Sean, G. Chechik, R. Friedman, E. Eskin
BMC Bioinformatics, vol. 7 (2006), S8
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Reduction of Information Redundancy in the Ascending Auditory Pathway
G. Chechik, M.J. Anderson, O. Bar-Yosef, E.D. Young, N. Tishby, I. Nelken
Neuron, vol. 51 (2006), pp. 359-368
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Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks
A. Battle, G. Chechik, D. Koller
Human Brain Mapping: Proceedings of the 2006 Conference
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Encoding Stimulus Information by Spike Numbers and Mean Response Time in Primary Auditory Cortex
I. Nelken, G. Chechik, T.D. Mrsic-Flogel, A.J. King, J.W.H. Schnupp
Journal of Computational Neuroscience, vol. 19 (2005), pp. 199-221
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Extracting Continuous Relevant Features
A. Globerson, G. Chechik, N. Tishby
Innovations in Classification, Data Science, and Information Systems: Proceedings of the 27th Annual Conference of the Gesellschaft für Klassifikation e.V., Springer (2005)
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Gaussian information bottleneck
G. Chechik, A. Globerson, N. Tishby, Y. Weiss
Journal of Machine Learning Research, vol. 6 (2005), pp. 165-188
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Information Bottleneck for Gaussian Variables
G. Chechik, A. Globerson, N. Tishby, Y. Weiss
The Journal of Machine Learning Research, vol. 6 (2005), pp. 165-188
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Separation of overlapping subpopulations by mutual information
S. O���Rourke, G. Chechik, E. Eskin
Proc. NIPS Workshop Comput. Biol. Anal. Heterogeneous Data (2005)
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Euclidean Embedding of Co-Occurrence Data
Amir Globerson, Gal Chechik, Fernando C. Pereira, Naftali Tishby
Advances in Neural Information Processing Systems (NIPS), MIT press, Cambridge, MA (2004), pp. 497-504
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Information Bottleneck for Gaussian Variables
Gal Chechik, Amir Globerson, Naftali Tishby, Yair Weiss
Advances in Neural Information Processing Systems 16, MIT Press, Cambridge, MA (2004)
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A needle in a haystack: local one-class optimization
K. Crammer, G. Chechik
Proceedings of the twenty-first international conference on Machine learning, ACM Press New York, NY, USA (2004)
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Sufficient Dimensionality Reduction with Irrelevant Statistics
Amir Globerson, Gal Chechik, Naftali Tishby
Proceedings of the 19th Annual Conference on Uncertainty in Artificial Intelligence (UAI-03), Morgan Kaufmann Publishers, San Francisco, CA (2003), pp. 281-288
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An Information Theoretic Approach to the Study of Auditory Coding
Ph.D. Thesis, Hebrew University (2003)
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Are there representations in embodied evolved agents? taking measures
H. Avraham, G. Chechik, E. Ruppin
Advances in Artificial Life-Proceedings of the 7th European Conference on Artificial Life, Springer (2003)
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Extracting relevant structures with side information
G. Chechik, N. Tishby
Advances in Neural Information Processing Systems 15, MIT Press, Cambridge, MA (2003), pp. 857-864
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Information bottleneck and linear projections of Gaussian processes
G. Chechik, A. Globerson
Technical Report 4, Hebrew University (2003)
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Spike-Timing-Dependent Plasticity and Relevant Mutual Information Maximization
Neural Computation, vol. 15 (2003), pp. 1481-1510
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Sufficient dimensionality reduction with irrelevance statistics
A. Globerson, G. Chechik, N. Tishby
Proceeding of the 19th Conference on Uncertainty in Artificial Intelligence, Acapulco, Mexico (2003)
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Transformation of stimulus representation in the ascending auditory system
I. Nelken, N. Ulanovsky, L. Las, O. Bar-Yosef, M. Anderson, G. Chechik, N. Tishby, E.D. Young
Auditory signal processing: physiology, psychoacoustics and models. Edited by Pressnitzer D, de Cheveigne A, McAdams S, Collet L. New York: Springer Verlag (2003), pp. 358-416
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Types, super-types and the mutual information distribution
Technical Report 4, Hebrew University, May 2003 (2003)
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Group redundancy measures reveal redundancy reduction in the auditory pathway
G. Chechik, A. Globerson, MJ Anderson, ED Young, I. Nelken, N. Tishby
Advances in Neural Information Processing Systems 14: Proceedings of the 2002 Conference, MIT Press, Cambridge, MA, pp. 173-180
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Spike timing dependent plasticity and mutual information in spiking neurons
Neurocomputing, vol. 38-40 (2001), pp. 147-152
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Distributional clustering of movements based on neural responses
A. Globerson, G. Chechik, N. Tishby, O. Steinberg, E. Vaadia
unpublished manuscript (2001)
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Effective Learning Requires Neuronal Remodeling of Hebbian Synapses
G. Chechik, I. Meilijson, E. Ruppin
Proceedings of the 1999 conference on Advances in neural information processing systems II table of contents (2001)
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Effective Neuronal Learning with Ineffective Hebbian Learning Rules
G. Chechik, I. Meilijson, E. Ruppin
Neural Computation, vol. 13 (2001), pp. 817-840
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Neuronal Regulation and Hebbian Learning
G. Chechik, D. Horn, E. Ruppin
The handbook of brain theory and neural networks. 2nd Edition, MIT Press (2000)
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Neuronal normalization provides effective learning through ineffective synaptic learning rules
G. Chechik, I. Meilijson, E. Ruppin
Neurocomputing, vol. 32 (2000), pp. 345-351
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Temporally Dependent Plasticity: An Information Theoretic Account
G. Chechik, N. Tishby
Advances in Neural Information Processing Systems: Proceedings of the 2000 Conference
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Neuronal regulation: A biologically plausible mechanism for efficient syanptic prunning in development
Gal Chechik, Isaac Meilijson, Eyten Ruppin
Neurocomputing, vol. 26-27 (1999), pp. 633-639
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Neuronal Regulation Implements Efficient Synaptic Pruning
G. Chechik, I. Meilijson, E. Ruppin
Proceedings of the 1998 conference on Advances in neural information processing systems II table of contents, MIT Press Cambridge, MA, USA (1999), pp. 97-103
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Neuronal Regulation: A Mechanism for Synaptic Pruning During Brain Maturation
G. Chechik, I. Meilijson, E. Ruppin
Neural Computation, vol. 11 (1999), pp. 2061-2080
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Synaptic Pruning in Development: A Computational Account
G. Chechik, I. Meilijson, E. Ruppin
Neural Computation, vol. 10 (1998), pp. 1759-1777
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Synaptic pruning during development: A novel account in neural terms
G. Chechik, I. Meilijson, E. Ruppin
Sixth Annual Computational Neuroscience Meeting.(CNS97), Big Ski, Montana (1997)





