Year |
Citation |
Score |
2022 |
Amir N, Tishby N, Nelken I. A simple model of the attentional blink and its modulation by mental training. Plos Computational Biology. 18: e1010398. PMID 36037219 DOI: 10.1371/journal.pcbi.1010398 |
0.748 |
|
2021 |
Levi-Aharoni H, Tishby N. The value-complexity trade-off for reinforcement learning based brain-computer interfaces. Journal of Neural Engineering. 17: 066011. PMID 33586668 DOI: 10.1088/1741-2552/abc8d8 |
0.753 |
|
2020 |
Amir N, Suliman R, Tal M, Shifman S, Tishby N, Nelken I. Value-complexity tradeoff explains mouse navigational learning. Plos Computational Biology. 16: e1008497. PMID 33306669 DOI: 10.1371/journal.pcbi.1008497 |
0.76 |
|
2020 |
Levi-Aharoni H, Shriki O, Tishby N. Surprise response as a probe for compressed memory states. Plos Computational Biology. 16: e1007065. PMID 32012146 DOI: 10.1371/Journal.Pcbi.1007065 |
0.748 |
|
2020 |
Painsky A, Feder M, Tishby N. Nonlinear Canonical Correlation Analysis:A Compressed Representation Approach Entropy. 22: 208. DOI: 10.3390/e22020208 |
0.383 |
|
2017 |
Wang S, Borst A, Zaslavsky N, Tishby N, Segev I. Efficient encoding of motion is mediated by gap junctions in the fly visual system. Plos Computational Biology. 13: e1005846. PMID 29206224 DOI: 10.1371/journal.pcbi.1005846 |
0.577 |
|
2016 |
Rubin J, Ulanovsky N, Nelken I, Tishby N. The Representation of Prediction Error in Auditory Cortex. Plos Computational Biology. 12: e1005058. PMID 27490251 DOI: 10.1371/Journal.Pcbi.1005058 |
0.756 |
|
2015 |
Jacoby N, Tishby N, Repp BH, Ahissar M, Keller PE. Parameter Estimation of Linear Sensorimotor Synchronization Models: Phase Correction, Period Correction, and Ensemble Synchronization Timing & Time Perception. 3: 52-87. DOI: 10.1163/22134468-00002048 |
0.77 |
|
2015 |
Jacoby N, Keller PE, Repp BH, Ahissar M, Tishby N. Lower Bound on the Accuracy of Parameter Estimation Methods for Linear Sensorimotor Synchronization Models Timing & Time Perception. 3: 32-51. DOI: 10.1163/22134468-00002047 |
0.769 |
|
2015 |
Jacoby N, Tishby N, Tymoczko D. An Information Theoretic Approach to Chord Categorization and Functional Harmony Journal of New Music Research. 44: 219-244. DOI: 10.1080/09298215.2015.1036888 |
0.662 |
|
2013 |
Hecht RM, Noor E, Dobry G, Zigel Y, Bar-Hillel A, Tishby N. Effective model representation by information bottleneck principle Ieee Transactions On Audio, Speech and Language Processing. 21: 1755-1759. DOI: 10.1109/TASL.2013.2253097 |
0.38 |
|
2013 |
Sabato S, Srebro N, Tishby N. Distribution-dependent sample complexity of large margin learning Journal of Machine Learning Research. 14: 2119-2149. |
0.607 |
|
2012 |
Rubin J, Shamir O, Tishby N. Trading value and information in MDPs Intelligent Systems Reference Library. 28: 57-74. DOI: 10.1007/978-3-642-24647-0_3 |
0.689 |
|
2011 |
Parush N, Tishby N, Bergman H. Dopaminergic Balance between Reward Maximization and Policy Complexity. Frontiers in Systems Neuroscience. 5: 22. PMID 21603228 DOI: 10.3389/Fnsys.2011.00022 |
0.757 |
|
2011 |
Shamir O, Tishby N. Spectral clustering on a budget Journal of Machine Learning Research. 15: 661-669. |
0.559 |
|
2010 |
Shamir O, Sabato S, Tishby N. Learning and generalization with the information bottleneck Theoretical Computer Science. 411: 2696-2711. DOI: 10.1016/J.Tcs.2010.04.006 |
0.791 |
|
2010 |
Shamir O, Tishby N. Stability and model selection in k-means clustering Machine Learning. 80: 213-243. DOI: 10.1007/S10994-010-5177-8 |
0.621 |
|
2010 |
Sabato S, Srebro N, Tishby N. Reducing label complexity by learning from bags Journal of Machine Learning Research. 9: 685-692. |
0.603 |
|
2010 |
Sabato S, Srebro N, Tishby N. Tight sample complexity of large-margin learning Advances in Neural Information Processing Systems 23: 24th Annual Conference On Neural Information Processing Systems 2010, Nips 2010. |
0.606 |
|
2009 |
Creutzig F, Globerson A, Tishby N. Past-future information bottleneck in dynamical systems. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 79: 041925. PMID 19518274 DOI: 10.1103/Physreve.79.041925 |
0.726 |
|
2009 |
Globerson A, Stark E, Vaadia E, Tishby N. The minimum information principle and its application to neural code analysis. Proceedings of the National Academy of Sciences of the United States of America. 106: 3490-5. PMID 19218435 DOI: 10.1073/Pnas.0806782106 |
0.732 |
|
2009 |
Globerson A, Stark E, Vaadia E, Tishby N. The minimum information principle and its application to neural code analysis (Proceeding of the National Academy of Sciences of the United States of America (2009) 106, 9, (3490-3495) doi: 10.1073/pnas.0806782106) Proceedings of the National Academy of Sciences of the United States of America. 106: 4061. DOI: 10.1073/pnas.0901850106 |
0.684 |
|
2009 |
Shamir O, Tishby N. On the reliability of clustering stability in the large sample regime - Supplementary material Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference. 1465-1472. |
0.562 |
|
2009 |
Shamir O, Tishby N. Cluster stability for finite samples Advances in Neural Information Processing Systems 20 - Proceedings of the 2007 Conference. |
0.561 |
|
2008 |
Parush N, Arkadir D, Nevet A, Morris G, Tishby N, Nelken I, Bergman H. Encoding by response duration in the basal ganglia. Journal of Neurophysiology. 100: 3244-52. PMID 18842956 DOI: 10.1152/Jn.90400.2008 |
0.76 |
|
2008 |
Shamir O, Tishby N. Model selection and stability in k-means clustering 21st Annual Conference On Learning Theory, Colt 2008. 367-378. |
0.569 |
|
2007 |
Seldin Y, Slonim N, Tishby N. Information bottleneck for non co-occurrence data Advances in Neural Information Processing Systems. 1241-1248. |
0.665 |
|
2007 |
Globerson A, Chechik G, Pereira F, Tishby N. Euclidean embedding of co-occurrence data Journal of Machine Learning Research. 8: 2265-2295. |
0.676 |
|
2007 |
Globerson A, Chechik G, Pereira F, Tishby N. Euclidean embedding of co-occurrence data Journal of Machine Learning Research. 8: 2265-2295. |
0.676 |
|
2006 |
Chechik G, Anderson MJ, Bar-Yosef O, Young ED, Tishby N, Nelken I. Reduction of information redundancy in the ascending auditory pathway. Neuron. 51: 359-68. PMID 16880130 DOI: 10.1016/j.neuron.2006.06.030 |
0.779 |
|
2006 |
Slonim N, Friedman N, Tishby N. Multivariate information bottleneck. Neural Computation. 18: 1739-89. PMID 16771652 DOI: 10.1162/Neco.2006.18.8.1739 |
0.706 |
|
2006 |
Bialek W, De Ruyter Van Steveninck RR, Tishby N. Efficient representation as a design principle for neural coding and computation Ieee International Symposium On Information Theory - Proceedings. 659-663. DOI: 10.1109/ISIT.2006.261867 |
0.763 |
|
2006 |
Globerson A, Chechik G, Pereira F, Tishby N. Embedding heterogeneous data using statistical models Proceedings of the National Conference On Artificial Intelligence. 2: 1605-1608. |
0.696 |
|
2005 |
Chechik G, Globerson A, Tishby N, Weiss Y. Information bottleneck for Gaussian variables Journal of Machine Learning Research. 6. |
0.716 |
|
2005 |
Chechik G, Globerson A, Tishby N, Weiss Y. Information bottleneck for Gaussian variables Journal of Machine Learning Research. 6. |
0.716 |
|
2005 |
Navot A, Shpigelman L, Tishby N, Vaadia E. Nearest neighbor based feature selection for regression and its application to neural activity Advances in Neural Information Processing Systems. 995-1002. |
0.551 |
|
2004 |
Bejerano G, Friedman N, Tishby N. Efficient exact p-value computation for small sample, sparse, and surprising categorical data. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. 11: 867-86. PMID 15700407 DOI: 10.1089/Cmb.2004.11.867 |
0.616 |
|
2003 |
Slonim N, Bejerano G, Fine S, Tishby N. Discriminative feature selection via multiclass variable memory Markov model Eurasip Journal On Applied Signal Processing. 2003: 93-102. DOI: 10.1155/S111086570321115X |
0.741 |
|
2003 |
Globerson A, Tishby N. Sufficient dimensionality reduction Journal of Machine Learning Research. 3: 1307-1331. |
0.425 |
|
2003 |
Chechik G, Tishby N. Extracting relevant structures with side information Advances in Neural Information Processing Systems. |
0.618 |
|
2002 |
Dubnov S, El-Yaniv R, Gdalyahu Y, Schneidman E, Tishby N, Yona G. A new nonparametric pairwise clustering algorithm based on iterative estimation of distance profiles Machine Learning. 47: 35-61. DOI: 10.1023/A:1013631728342 |
0.751 |
|
2002 |
Globerson A, Tishby N. Most informative dimension reduction Proceedings of the National Conference On Artificial Intelligence. 1024-1029. |
0.511 |
|
2002 |
Chechik G, Globerson A, Tishby N, Anderson MJ, Young ED, Nelken T. Group redundancy measures reveal redundancy reduction in the auditory pathway Advances in Neural Information Processing Systems. |
0.67 |
|
2002 |
Slonim N, Friedman N, Tishby N. Agglomerative multivariate information bottleneck Advances in Neural Information Processing Systems. |
0.668 |
|
2002 |
Slonim N, Friedman N, Tishby N. Unsupervised document classification using sequential information maximization Sigir Forum (Acm Special Interest Group On Information Retrieval). 129-136. |
0.67 |
|
2001 |
Gat I, Tishby N. Spotting neural spike patterns using an adversary background model. Neural Computation. 13: 2681-708. PMID 11705407 DOI: 10.1162/089976601317098493 |
0.69 |
|
2001 |
Bialek W, Nemenman I, Tishby N. Predictability, complexity, and learning. Neural Computation. 13: 2409-63. PMID 11674845 DOI: 10.1162/089976601753195969 |
0.781 |
|
2001 |
Bejerano G, Seldin Y, Margalit H, Tishby N. Markovian domain fingerprinting: statistical segmentation of protein sequences. Bioinformatics (Oxford, England). 17: 927-34. PMID 11673237 |
0.548 |
|
2001 |
Slonim N, Somerville R, Tishby N, Lahav O. Objective classification of galaxy spectra using the information bottleneck method Monthly Notices of the Royal Astronomical Society. 323: 270-284. DOI: 10.1046/J.1365-8711.2001.04125.X |
0.675 |
|
2001 |
Bialek W, Nemenman I, Tishby N. Complexity through nonextensivity Physica a: Statistical Mechanics and Its Applications. 302: 89-99. DOI: 10.1016/S0378-4371(01)00444-7 |
0.77 |
|
2001 |
Chechik G, Tishby N. Temporally dependent plasticity: An information theoretic account Advances in Neural Information Processing Systems. |
0.638 |
|
2001 |
Tishby N, Slonim N. Data clustering by Markovian relaxation and the Information Bottleneck Method Advances in Neural Information Processing Systems. |
0.655 |
|
2001 |
Schneidman E, Brenner N, Tishby N, De Ruyter Van Steveninck RR, Bialek W. Universality and individuality in a neural code Advances in Neural Information Processing Systems. |
0.751 |
|
2000 |
Schneidman E, Segev I, Tishby N. Information capacity and robustness of stochastic neuron models Advances in Neural Information Processing Systems. 178-184. |
0.743 |
|
2000 |
Slonim N, Tishby N. Agglomerative information bottleneck Advances in Neural Information Processing Systems. 617-623. |
0.665 |
|
1999 |
Beeri C, Elber G, Milo T, Sagiv Y, Shmueli O, Tishby N, Kogan Y, Konopnicki D, Mogilevski P, Slonim N. Websuite—a tool suite for harnessing web data Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1590: 152-171. |
0.612 |
|
1998 |
Fine S, Singer Y, Tishby N. Hierarchical Hidden Markov Model: Analysis and applications Machine Learning. 32: 41-62. DOI: 10.1023/A:1007469218079 |
0.709 |
|
1998 |
Ron D, Singer Y, Tishby N. On the Learnability and Usage of Acyclic Probabilistic Finite Automata Journal of Computer and System Sciences. 56: 133-152. |
0.476 |
|
1997 |
Gat I, Tishby N, Abeles M. Hidden Markov modelling of simultaneously recorded cells in the associative cortex of behaving monkeys Network: Computation in Neural Systems. 8: 297-322. DOI: 10.1088/0954-898X_8_3_005 |
0.752 |
|
1997 |
Dubnov S, Tishby N, Cohen D. Polyspectra as measures of sound texture and timbre* Journal of New Music Research. 26: 277-314. DOI: 10.1080/09298219708570732 |
0.638 |
|
1997 |
Freund Y, Seung HS, Shamir E, Tishby N. Selective Sampling Using the Query by Committee Algorithm Machine Learning. 28: 133-168. DOI: 10.1023/A:1007330508534 |
0.551 |
|
1997 |
Gat I, Tishby N, Abeles M. Comparative study of supervised detection methods of simultaneously recorded spike trains Neuroscience Letters. 237: S17-S18. DOI: 10.1016/S0304-3940(97)90071-9 |
0.623 |
|
1997 |
Haussler D, Kearns M, Seung HS, Tishby N. Rigorous learning curve bounds from statistical mechanics Machine Learning. 25: 195-236. DOI: 10.1007/BF00114010 |
0.48 |
|
1997 |
Dubnov S, Tishby N. Analysis of sound textures in musical and machine sounds by means of higher order statistical features Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 5: 3845-3848. |
0.578 |
|
1996 |
Ron D, Singer Y, Tishby N. The power of amnesia: Learning probabilistic automata with variable memory length Machine Learning. 25: 117-149. |
0.514 |
|
1995 |
Abeles M, Bergman H, Gat I, Meilijson I, Seidemann E, Tishby N, Vaadia E. Cortical activity flips among quasi-stationary states. Proceedings of the National Academy of Sciences of the United States of America. 92: 8616-20. PMID 7567985 DOI: 10.1073/Pnas.92.19.8616 |
0.772 |
|
1995 |
Dubnov S, Tishby N, Cohen D. Hearing beyond the spectrum Journal of New Music Research. 24: 342-368. DOI: 10.1080/09298219508570690 |
0.651 |
|
1994 |
Singer Y, Tishby N. Dynamical encoding of cursive handwriting. Biological Cybernetics. 71: 227-37. PMID 7918801 DOI: 10.1007/Bf00202762 |
0.561 |
|
1994 |
Singer Y, Tishby N. Inferring probabilistic acyclic automata using the minimum description length principle Ieee International Symposium On Information Theory - Proceedings. 392. DOI: 10.1109/ISIT.1994.394627 |
0.513 |
|
1992 |
Seung HS, Sompolinsky H, Tishby N. Statistical mechanics of learning from examples. Physical Review. A. 45: 6056-6091. PMID 9907706 DOI: 10.1103/PhysRevA.45.6056 |
0.68 |
|
1990 |
Sompolinsky H, Tishby N, Seung HS. Learning from examples in large neural networks. Physical Review Letters. 65: 1683-1686. PMID 10042332 DOI: 10.1103/PhysRevLett.65.1683 |
0.64 |
|
1990 |
Sompolinsky H, Tishby N. Learning in a two-layer neural network of edge detectors Epl. 13: 567-572. DOI: 10.1209/0295-5075/13/6/016 |
0.57 |
|
1985 |
Tikochinsky Y, Tishby NZ, Levine RD. Tikochinsky, Tishby, and Levine respond. Physical Review Letters. 55: 1031. PMID 10032513 DOI: 10.1103/Physrevlett.55.1031 |
0.405 |
|
1985 |
Tikochinsky Y, Tishby NZ, Levine RD. Tikochinsky, Tishby, and Levine respond. Physical Review Letters. 55: 337. PMID 10032323 |
0.323 |
|
1984 |
Tikochinsky Y, Tishby NZ, Levine RD. Consistent inference of probabilities for reproducible experiments Physical Review Letters. 52: 1357-1360. DOI: 10.1103/Physrevlett.52.1357 |
0.374 |
|
1984 |
Tikochinsky Y, Tishby NZ, Levine RD. Alternative approach to maximum-entropy inference Physical Review A. 30: 2638-2644. DOI: 10.1103/Physreva.30.2638 |
0.415 |
|
1984 |
Tishby NZ, Levine RD. Time evolution via a self-consistent maximal-entropy propagation: The reversible case Physical Review A. 30: 1477-1490. DOI: 10.1103/Physreva.30.1477 |
0.326 |
|
1984 |
Tishby NZ, Levine RD. A self-consistent field procedure for stationary states using an algebraic approach and the maximum entropy formalism Chemical Physics Letters. 104: 4-8. DOI: 10.1016/0009-2614(84)85293-8 |
0.345 |
|
1983 |
Tishby NZ, Levine RD. Surprisal analysis derived from a variational principle for mechanical systems Chemical Physics Letters. 98: 310-314. DOI: 10.1016/0009-2614(83)80213-9 |
0.37 |
|
Show low-probability matches. |