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 |
0.754 |
|
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 |
0.578 |
|
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 |
0.757 |
|
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 |
0.769 |
|
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 |
0.668 |
|
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 |
0.691 |
|
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. 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 |
|
2010 |
Sabato S, Srebro N, Tishby N. Reducing label complexity by learning from bags Journal of Machine Learning Research. 9: 685-692. |
0.603 |
|
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 |
0.727 |
|
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 |
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 |
|
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 |
|
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 |
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 |
|
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 |
|
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 |
0.782 |
|
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 |
0.772 |
|
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 |
|
2001 |
Tishby N, Slonim N. Data clustering by Markovian relaxation and the Information Bottleneck Method Advances in Neural Information Processing Systems. |
0.655 |
|
2001 |
Chechik G, Tishby N. Temporally dependent plasticity: An information theoretic account Advances in Neural Information Processing Systems. |
0.638 |
|
2000 |
Slonim N, Tishby N. Agglomerative information bottleneck Advances in Neural Information Processing Systems. 617-623. |
0.665 |
|
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 |
|
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 |
0.553 |
|
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 |
0.483 |
|
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 |
0.681 |
|
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 |
0.642 |
|
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 |
0.571 |
|
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 |
|
Low-probability matches (unlikely to be authored by this person) |
1994 |
Tishby N, Gorin A. Algebraic learning of statistical associations for language acquisition Computer Speech and Language. 8: 51-78. DOI: 10.1006/csla.1994.1003 |
0.287 |
|
2019 |
Hecht RM, Hillel AB, Telpaz A, Tsimhoni O, Tishby N. Information Constrained Control Analysis of Eye Gaze Distribution Under Workload Ieee Transactions On Human-Machine Systems. 49: 474-484. DOI: 10.1109/Thms.2019.2930996 |
0.285 |
|
2019 |
Carleo G, Cirac I, Cranmer K, Daudet L, Schuld M, Tishby N, Vogt-Maranto L, Zdeborová L. Machine learning and the physical sciences Reviews of Modern Physics. 91. DOI: 10.1103/Revmodphys.91.045002 |
0.27 |
|
2006 |
Navot A, Gilad-Bachrach R, Navot Y, Tishby N. Is feature selection still necessary? Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3940: 127-138. DOI: 10.1007/11752790_8 |
0.269 |
|
2018 |
Zaslavsky N, Kemp C, Regier T, Tishby N. Efficient compression in color naming and its evolution. Proceedings of the National Academy of Sciences of the United States of America. PMID 30021851 DOI: 10.1073/Pnas.1800521115 |
0.269 |
|
2020 |
Painsky A, Feder M, Tishby N. Nonlinear Canonical Correlation Analysis:A Compressed Representation Approach. Entropy (Basel, Switzerland). 22. PMID 33285982 DOI: 10.3390/e22020208 |
0.261 |
|
2004 |
Adar R, Benenson Y, Linshiz G, Rosner A, Tishby N, Shapiro E. Stochastic computing with biomolecular automata. Proceedings of the National Academy of Sciences of the United States of America. 101: 9960-5. PMID 15215499 DOI: 10.1073/Pnas.0400731101 |
0.26 |
|
1997 |
Linial M, Linial N, Tishby N, Yona G. Global self-organization of all known protein sequences reveals inherent biological signatures. Journal of Molecular Biology. 268: 539-56. PMID 9159489 DOI: 10.1006/jmbi.1997.0948 |
0.26 |
|
2011 |
Calderara S, Heinemann U, Prati A, Cucchiara R, Tishby N. Detecting anomalies in people's trajectories using spectral graph analysis Computer Vision and Image Understanding. 115: 1099-1111. DOI: 10.1016/J.Cviu.2011.03.003 |
0.248 |
|
1989 |
Györgyi G, Tishby N. Path integrals in Hamiltonian systems: Breakup of the last Kolmogorov-Arnold-Moser torus due to random forces. Physical Review Letters. 62: 353-356. PMID 10040211 DOI: 10.1103/PhysRevLett.62.353 |
0.236 |
|
1987 |
Györgyi G, Tishby N. Destabilization of islands in noisy Hamiltonian systems. Physical Review. A. 36: 4957-4967. PMID 9898755 DOI: 10.1103/PhysRevA.36.4957 |
0.23 |
|
1987 |
Györgyi G, Tishby N. Scaling in stochastic Hamiltonian systems: A renormalization approach. Physical Review Letters. 58: 527-530. PMID 10034964 DOI: 10.1103/PhysRevLett.58.527 |
0.229 |
|
2007 |
Neuvirth H, Heinemann U, Birnbaum D, Tishby N, Schreiber G. ProMateus--an open research approach to protein-binding sites analysis. Nucleic Acids Research. 35: W543-8. PMID 17488838 DOI: 10.1093/nar/gkm301 |
0.226 |
|
2005 |
Tishby N. Course 16 The emergence of relevant data representations: An information theoretic approach Les Houches Summer School Proceedings. 80: 787-829. DOI: 10.1016/S0924-8099(05)80022-8 |
0.213 |
|
2003 |
Tishby N. Efficient Data Representations That Preserve Information Lecture Notes in Computer Science. 45. |
0.211 |
|
2015 |
Tishby N, Zaslavsky N. Deep learning and the information bottleneck principle 2015 Ieee Information Theory Workshop, Itw 2015. DOI: 10.1109/ITW.2015.7133169 |
0.209 |
|
2003 |
Gilad-Bachrach R, Navot A, Tishby N. An information theoretic tradeoff between complexity and accuracy Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). 2777: 595-609. |
0.202 |
|
2009 |
Hecht RM, Noor E, Tishby N. Speaker recognition by Gaussian information bottleneck Proceedings of the Annual Conference of the International Speech Communication Association, Interspeech. 1567-1570. |
0.197 |
|
2016 |
Amir N, Tiomkin S, Tishby N. Past-future Information Bottleneck for linear feedback systems Proceedings of the Ieee Conference On Decision and Control. 2016: 5737-5742. DOI: 10.1109/CDC.2015.7403120 |
0.193 |
|
2007 |
Harremoës P, Tishby N. The information bottleneck revisited or how to choose a good distortion measure Ieee International Symposium On Information Theory - Proceedings. 566-570. DOI: 10.1109/ISIT.2007.4557285 |
0.182 |
|
1989 |
Tishby N, Levin E, Solla SA. Consistent inference of probabilities in layered networks: Predictions and generalization Ijcnn Int Jt Conf Neural Network. 403-409. |
0.159 |
|
2005 |
Hecht RM, Tishby N. Extraction of relevant speech features using the information bottleneck method 9th European Conference On Speech Communication and Technology. 353-356. |
0.155 |
|
2009 |
Hecht RM, Hezroni O, Manna A, Dobry G, Zigel Y, Tishby N. Information bottleneck based age verification Proceedings of the Annual Conference of the International Speech Communication Association, Interspeech. 188-191. |
0.15 |
|
2014 |
Moshkovitz M, Tishby N. Control your information for better predictions Ieee International Symposium On Information Theory - Proceedings. 916-920. DOI: 10.1109/ISIT.2014.6874966 |
0.149 |
|
2008 |
Tishby N. Extracting relevant information from samples 10th International Symposium On Artificial Intelligence and Mathematics, Isaim 2008. 60P. |
0.149 |
|
1990 |
Levin E, Tishby N, Solla SA. A Statistical Approach to Learning and Generalization in Layered Neural Networks Proceedings of the Ieee. 78: 1568-1574. DOI: 10.1109/5.58339 |
0.146 |
|
1996 |
Haussler D, Kearns M, Sebastian Seung H, Tishby N. Rigorous learning curve bounds from statistical mechanics Machine Learning. 25: 195-236. |
0.141 |
|
2009 |
Sabato S, Tishby N. Homogeneous multi-instance learning with arbitrary dependence Colt 2009 - the 22nd Conference On Learning Theory. |
0.135 |
|
2007 |
Krupka E, Tishby N. Incorporating prior knowledge on features into learning Journal of Machine Learning Research. 2: 227-234. |
0.128 |
|
2008 |
Krupka E, Navot A, Tishby N. Learning to select features using their properties Journal of Machine Learning Research. 9: 2349-2376. |
0.127 |
|
2012 |
Sabato S, Tishby N. Multi-instance learning with any hypothesis class Journal of Machine Learning Research. 13: 2999-3039. |
0.127 |
|
1987 |
Tishby N. Text‐independent speaker verification using linear predictive hidden Markov models The Journal of the Acoustical Society of America. 81: S94-S94. DOI: 10.1121/1.2024482 |
0.122 |
|
1991 |
Tishby NZ. On the Application of Mixture AR Hidden Markov Models to Text Independent Speaker Recognition Ieee Transactions On Signal Processing. 39: 563-570. DOI: 10.1109/78.80876 |
0.114 |
|
1988 |
Tishby N. Nonlinear dynamical modeling of speech using neural networks Neural Networks. 1: 279. DOI: 10.1016/0893-6080(88)90313-9 |
0.111 |
|
1998 |
Yona G, Linial N, Tishby N, Linial M. A map of the protein space--an automatic hierarchical classification of all protein sequences. Proceedings / ... International Conference On Intelligent Systems For Molecular Biology ; Ismb. International Conference On Intelligent Systems For Molecular Biology. 6: 212-21. PMID 9783227 |
0.106 |
|
2009 |
Seldin Y, Tishby N. PAC-Bayesian generalization bound for density estimation with application to co-clustering Journal of Machine Learning Research. 5: 472-479. |
0.105 |
|
2008 |
Krupka E, Tishby N. Generalization from observed to unobserved features by clustering Journal of Machine Learning Research. 9: 339-370. |
0.091 |
|
2019 |
Zaslavsky N, Kemp C, Tishby N, Regier T. Communicative need in colour naming. Cognitive Neuropsychology. 1-13. PMID 31027459 DOI: 10.1080/02643294.2019.1604502 |
0.091 |
|
2008 |
Seldin Y, Tishby N. Multi-classification by categorical features via clustering Proceedings of the 25th International Conference On Machine Learning. 920-927. |
0.089 |
|
2005 |
Krupka E, Tishby N. Generalization in clustering with unobserved features Advances in Neural Information Processing Systems. 683-690. |
0.089 |
|
2001 |
Bekkerman R, El-Yaniv R, Winter Y, Tishby N. On feature distributional clustering for text categorization Sigir Forum (Acm Special Interest Group On Information Retrieval). 146-153. |
0.086 |
|
2010 |
Seldin Y, Tishby N. PAC-Bayesian analysis of Co-clustering and beyond Journal of Machine Learning Research. 11: 3595-3646. |
0.084 |
|
2004 |
Gilad-Bachrach R, Navot A, Tishby N. Margin based feature selection - Theory and algorithms Proceedings, Twenty-First International Conference On Machine Learning, Icml 2004. 337-344. |
0.078 |
|
2006 |
Gilad-Bachrach R, Navot A, Tishby N. Large margin principles for feature selection Studies in Fuzziness and Soft Computing. 207: 585-606. |
0.072 |
|
1999 |
Rinberg D, Davidowitz H, Tishby N. Multi-electrode spike sorting by clustering transfer functions Advances in Neural Information Processing Systems. 146-152. |
0.069 |
|
2018 |
Zaslavsky N, Kemp C, Tishby N, Regier T. Color Naming Reflects Both Perceptual Structure and Communicative Need. Topics in Cognitive Science. PMID 30457215 DOI: 10.1111/Tops.12395 |
0.06 |
|
1998 |
El-Yaniv R, Fine S, Tishby N. Agnostic classification of markovian sequences Advances in Neural Information Processing Systems. 465-471. |
0.057 |
|
1999 |
Gat I, Tishby N. Synergy and redundancy among brain cells of behaving monkeys Advances in Neural Information Processing Systems. 111-117. |
0.052 |
|
2014 |
Ortega PA, Braun DA, Tishby N. Monte Carlo methods for exact & efficient solution of the generalized optimality equations Proceedings - Ieee International Conference On Robotics and Automation. 4322-4327. DOI: 10.1109/ICRA.2014.6907488 |
0.052 |
|
2003 |
Crammer K, Gilad-Bachrach R, Navot A, Tishby N. Margin analysis of the LVQ algorithm Advances in Neural Information Processing Systems. |
0.051 |
|
2003 |
Bekkerman R, El-Yaniv R, Tishby N, Winter Y. Distributional word clusters vs. words for text categorization Journal of Machine Learning Research. 3: 1183-1208. |
0.05 |
|
2015 |
Hecht RM, Bar-Hillel A, Tiomkin S, Levi H, Tsimhoni O, Tishby N. Cognitive workload and vocabulary sparseness: Theory and practice Proceedings of the Annual Conference of the International Speech Communication Association, Interspeech. 2015: 3394-3398. |
0.035 |
|
2005 |
Gilad-Bachrach R, Navot A, Tishby N. Query by Committee made real Advances in Neural Information Processing Systems. 443-450. |
0.024 |
|
2012 |
Fox R, Tishby N. Bounded planning in passive POMDPs Proceedings of the 29th International Conference On Machine Learning, Icml 2012. 2: 1775-1782. |
0.023 |
|
2004 |
Gilad-Bachrach R, Navot A, Tishby N. Bayes and Tukey meet at the center point Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science). 3120: 549-563. |
0.02 |
|
Hide low-probability matches. |