Gal Chechik

Gal Chechik joined Google in 2007. Before joining Google he was a research affiliate at the Stanford AI lab with Daphne Koller, where he studied computational biology models of molecular networks. Before that, he earned his PhD from the Hebrew University, working on machine learning approaches to analyze neural coding in the auditory system.

See his Stanford page and list of publications.

Google Publications

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

    G. Chechik

    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

    G. Chechik

    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

    G. Chechik

    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

    Gal Chechik

    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)