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ORCIDAryeh Kontorovich
Leonid Kontorovich
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- affiliation: Ben-Gurion University, Beersheba, Israel
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2020 – today
- 2024
[j37]Yair Ashlagi, Lee-Ad Gottlieb, Aryeh Kontorovich:
Functions with average smoothness: structure, algorithms, and learning. J. Mach. Learn. Res. 25: 117:1-117:54 (2024)- [j36]Idan Attias, Aryeh Kontorovich:
Fat-Shattering Dimension of k-fold Aggregations. J. Mach. Learn. Res. 25: 144:1-144:29 (2024) - [j35]Lee-Ad Gottlieb
, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch, Ofir Pele:
Nested barycentric coordinate system as an explicit feature map for polyhedra approximation and learning tasks. Mach. Learn. 113(10): 7807-7840 (2024) - [j34]Hananel Zaichyk, Armin Biess, Aryeh Kontorovich, Yury Makarychev:
Efficient Kirszbraun extension with applications to regression. Math. Program. 207(1): 617-642 (2024) - [j33]Hananel Zaichyk, Armin Biess, Aryeh Kontorovich, Yury Makarychev:
Correction: Efficient Kirszbraun extension with applications to regression. Math. Program. 207(1): 643 (2024) - [c51]Steve Hanneke, Aryeh Kontorovich, Guy Kornowski:
Efficient Agnostic Learning with Average Smoothness. ALT 2024: 719-731 - [c50]Moïse Blanchard, Doron Cohen, Aryeh Kontorovich:
Correlated Binomial Process. COLT 2024: 551-595 - [c49]Dina Barak-Pelleg, Daniel Berend, Aryeh Kontorovich:
Super-Teaching in Machine Learning. CSCML 2024: 335-342 - [c48]Idan Attias, Steve Hanneke, Aryeh Kontorovich, Menachem Sadigurschi:
Agnostic Sample Compression Schemes for Regression. ICML 2024 - [c47]Matan Levi, Aryeh Kontorovich:
Splitting the Difference on Adversarial Training. USENIX Security Symposium 2024 - [i52]Aryeh Kontorovich, Amichai Painsky:
Distribution Estimation under the Infinity Norm. CoRR abs/2402.08422 (2024) - [i51]Aryeh Kontorovich:
Aggregation of expert advice, revisited. CoRR abs/2407.16642 (2024) - [i50]Doron Cohen, Aryeh Kontorovich, Roi Weiss:
The MLE is minimax optimal for LGC. CoRR abs/2410.02835 (2024) - 2023
- [j32]László Györfi, Aryeh Kontorovich, Roi Weiss:
Tree Density Estimation. IEEE Trans. Inf. Theory 69(2): 1168-1176 (2023) - [j31]Doron Cohen, Aryeh Kontorovich, Aaron Koolyk, Geoffrey Wolfer:
Dimension-Free Empirical Entropy Estimation. IEEE Trans. Inf. Theory 69(5): 3190-3202 (2023) - [c46]Doron Cohen, Aryeh Kontorovich:
Local Glivenko-Cantelli. COLT 2023: 715 - [c45]Doron Cohen, Aryeh Kontorovich:
Open problem: log(n) factor in "Local Glivenko-Cantelli. COLT 2023: 5934-5936 - [c44]Guy Kornowski, Steve Hanneke, Aryeh Kontorovich:
Near-optimal learning with average Hölder smoothness. NeurIPS 2023 - [i49]Steve Hanneke, Aryeh Kontorovich, Guy Kornowski:
Near-optimal learning with average Hölder smoothness. CoRR abs/2302.06005 (2023) - [i48]Steve Hanneke, Aryeh Kontorovich, Guy Kornowski:
Efficient Agnostic Learning with Average Smoothness. CoRR abs/2309.17016 (2023) - [i47]Matan Levi, Aryeh Kontorovich:
Splitting the Difference on Adversarial Training. CoRR abs/2310.02480 (2023) - 2022
- [j30]Lee-Ad Gottlieb, Aryeh Kontorovich:
Non-uniform packings. Inf. Process. Lett. 174: 106179 (2022) - [j29]Idan Attias, Aryeh Kontorovich, Yishay Mansour:
Improved Generalization Bounds for Adversarially Robust Learning. J. Mach. Learn. Res. 23: 175:1-175:31 (2022) - [j28]Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch:
Learning Convex Polyhedra With Margin. IEEE Trans. Inf. Theory 68(3): 1976-1984 (2022) - [j27]Matan Levi, Idan Attias, Aryeh Kontorovich:
Domain Invariant Adversarial Learning. Trans. Mach. Learn. Res. 2022 (2022) - [c43]Dan Tsir Cohen, Aryeh Kontorovich:
Learning with metric losses. COLT 2022: 662-700 - [c42]Aryeh Kontorovich, Menachem Sadigurschi, Uri Stemmer:
Adaptive Data Analysis with Correlated Observations. ICML 2022: 11483-11498 - [i46]Aryeh Kontorovich, Menachem Sadigurschi, Uri Stemmer:
Adaptive Data Analysis with Correlated Observations. CoRR abs/2201.08704 (2022) - [i45]Dan Tsir Cohen, Aryeh Kontorovich:
Metric-valued regression. CoRR abs/2202.03045 (2022) - [i44]Olivier Bousquet, Haim Kaplan, Aryeh Kontorovich, Yishay Mansour, Shay Moran, Menachem Sadigurschi, Uri Stemmer:
Differentially-Private Bayes Consistency. CoRR abs/2212.04216 (2022) - 2021
- [j26]Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich:
Apportioned margin approach for cost sensitive large margin classifiers. Ann. Math. Artif. Intell. 89(12): 1215-1235 (2021) - [c41]Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch, Ofir Pele:
Nested Barycentric Coordinate System as an Explicit Feature Map. AISTATS 2021: 766-774 - [c40]Steve Hanneke, Aryeh Kontorovich:
Stable Sample Compression Schemes: New Applications and an Optimal SVM Margin Bound. ALT 2021: 697-721 - [c39]Yair Ashlagi, Lee-Ad Gottlieb, Aryeh Kontorovich:
Functions with average smoothness: structure, algorithms, and learning. COLT 2021: 186-236 - [c38]Doron Cohen, Aryeh Kontorovich, Aaron Koolyk, Geoffrey Wolfer:
Dimension-free empirical entropy estimation. NeurIPS 2021: 13911-13923 - [i43]Matan Levi, Idan Attias, Aryeh Kontorovich:
Domain Invariant Adversarial Learning. CoRR abs/2104.00322 (2021) - [i42]Doron Cohen, Aryeh Kontorovich, Aaron Koolyk, Geoffrey Wolfer:
Dimension-Free Empirical Entropy Estimation. CoRR abs/2105.07408 (2021) - [i41]Aryeh Kontorovich, Idan Attias:
Fat-shattering dimension of k-fold maxima. CoRR abs/2110.04763 (2021) - [i40]László Györfi, Aryeh Kontorovich, Roi Weiss:
Tree density estimation. CoRR abs/2111.11971 (2021) - 2020
- [j25]Daniel Berend, Aryeh Kontorovich, Lev Reyzin, Thomas J. Robinson:
On biased random walks, corrupted intervals, and learning under adversarial design. Ann. Math. Artif. Intell. 88(8): 887-905 (2020) - [c37]Geoffrey Wolfer, Aryeh Kontorovich:
Minimax Testing of Identity to a Reference Ergodic Markov Chain. AISTATS 2020: 191-201 - [c36]Klim Efremenko, Aryeh Kontorovich, Moshe Noivirt:
Fast and Bayes-consistent nearest neighbors. AISTATS 2020: 1276-1286 - [c35]Aryeh Kontorovich, Gergely Neu:
Algorithmic Learning Theory 2020: Preface. ALT 2020: 1-2 - [c34]Steve Hanneke, Aryeh Kontorovich, Sivan Sabato, Roi Weiss:
Universal Bayes Consistency in Metric Spaces. ITA 2020: 1-33 - [c33]Doron Cohen, Aryeh Kontorovich, Geoffrey Wolfer:
Learning discrete distributions with infinite support. NeurIPS 2020 - [e1]Aryeh Kontorovich, Gergely Neu:
Algorithmic Learning Theory, ALT 2020, 8-11 February 2020, San Diego, CA, USA. Proceedings of Machine Learning Research 117, PMLR 2020 [contents] - [i39]Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich:
Apportioned Margin Approach for Cost Sensitive Large Margin Classifiers. CoRR abs/2002.01408 (2020) - [i38]Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch, Ofir Pele:
Nested Barycentric Coordinate System as an Explicit Feature Map. CoRR abs/2002.01999 (2020) - [i37]Daniel Berend, Aryeh Kontorovich, Lev Reyzin, Thomas J. Robinson:
On Biased Random Walks, Corrupted Intervals, and Learning Under Adversarial Design. CoRR abs/2003.13561 (2020) - [i36]Yair Ashlagi, Lee-Ad Gottlieb, Aryeh Kontorovich:
Functions with average smoothness: structure, algorithms, and learning. CoRR abs/2007.06283 (2020) - [i35]Ariel Avital, Klim Efremenko, Aryeh Kontorovich, David Toplin, Bo Waggoner:
Non-parametric Binary regression in metric spaces with KL loss. CoRR abs/2010.09886 (2020) - [i34]Steve Hanneke, Aryeh Kontorovich:
Stable Sample Compression Schemes: New Applications and an Optimal SVM Margin Bound. CoRR abs/2011.04586 (2020)
2010 – 2019
- 2019
- [j24]Steve Hanneke, Aryeh Kontorovich:
Optimality of SVM: Novel proofs and tighter bounds. Theor. Comput. Sci. 796: 99-113 (2019) - [c32]Eyal Gutflaish, Aryeh Kontorovich, Sivan Sabato, Ofer Biller, Oded Sofer:
Temporal Anomaly Detection: Calibrating the Surprise. AAAI 2019: 3755-3762 - [c31]Idan Attias, Aryeh Kontorovich, Yishay Mansour:
Improved Generalization Bounds for Robust Learning. ALT 2019: 162-183 - [c30]Steve Hanneke, Aryeh Kontorovich, Menachem Sadigurschi:
Sample Compression for Real-Valued Learners. ALT 2019: 466-488 - [c29]Steve Hanneke, Aryeh Kontorovich:
A Sharp Lower Bound for Agnostic Learning with Sample Compression Schemes. ALT 2019: 489-505 - [c28]Geoffrey Wolfer, Aryeh Kontorovich:
Minimax Learning of Ergodic Markov Chains. ALT 2019: 903-929 - [c27]Geoffrey Wolfer, Aryeh Kontorovich:
Estimating the Mixing Time of Ergodic Markov Chains. COLT 2019: 3120-3159 - [i33]Geoffrey Wolfer, Aryeh Kontorovich:
Estimating the Mixing Time of Ergodic Markov Chains. CoRR abs/1902.01224 (2019) - [i32]Armin Biess, Aryeh Kontorovich, Yury Makarychev, Hanan Zaichyk:
Regression via Kirszbraun Extension with Applications to Imitation Learning. CoRR abs/1905.11930 (2019) - [i31]Steve Hanneke, Aryeh Kontorovich, Sivan Sabato, Roi Weiss:
Universal Bayes consistency in metric spaces. CoRR abs/1906.09855 (2019) - [i30]Klim Efremenko, Aryeh Kontorovich, Moshe Noivirt:
Fast and Bayes-consistent nearest neighbors. CoRR abs/1910.05270 (2019) - 2018
- [j23]Lee-Ad Gottlieb, Aryeh Kontorovich, Pinhas Nisnevitch:
Near-Optimal Sample Compression for Nearest Neighbors. IEEE Trans. Inf. Theory 64(6): 4120-4128 (2018) - [c26]Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch:
Learning convex polytopes with margin. NeurIPS 2018: 5711-5721 - [c25]Matan Levi, Yair Allouche, Aryeh Kontorovich:
Advanced Analytics for Connected Car Cybersecurity. VTC Spring 2018: 1-7 - [i29]Steve Hanneke, Aryeh Kontorovich:
A New Lower Bound for Agnostic Learning with Sample Compression Schemes. CoRR abs/1805.08140 (2018) - [i28]Steve Hanneke, Aryeh Kontorovich, Menachem Sadigurschi:
Sample Compression for Real-Valued Learners. CoRR abs/1805.08254 (2018) - [i27]Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch:
Learning convex polytopes with margin. CoRR abs/1805.09719 (2018) - [i26]Geoffrey Wolfer, Aryeh Kontorovich:
Minimax Learning of Ergodic Markov Chains. CoRR abs/1809.05014 (2018) - [i25]Steve Hanneke, Aryeh Kontorovich, Menachem Sadigurschi:
Agnostic Sample Compression for Linear Regression. CoRR abs/1810.01864 (2018) - [i24]Idan Attias, Aryeh Kontorovich, Yishay Mansour:
Improved generalization bounds for robust learning. CoRR abs/1810.02180 (2018) - 2017
- [j22]Dan Gutfreund, Aryeh Kontorovich, Ran Levy, Michal Rosen-Zvi:
Boosting conditional probability estimators. Ann. Math. Artif. Intell. 79(1-3): 129-144 (2017) - [j21]Daniel Berend, Aryeh Kontorovich, Gil Zagdanski:
The Expected Missing Mass under an Entropy Constraint. Entropy 19(7): 315 (2017) - [j20]Lee-Ad Gottlieb, Aryeh Kontorovich, Pinhas Nisnevitch:
Nearly optimal classification for semimetrics. J. Mach. Learn. Res. 18: 37:1-37:22 (2017) - [j19]Aryeh Kontorovich, Sivan Sabato, Ruth Urner:
Active Nearest-Neighbor Learning in Metric Spaces. J. Mach. Learn. Res. 18: 195:1-195:38 (2017) - [j18]Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer:
Efficient Regression in Metric Spaces via Approximate Lipschitz Extension. IEEE Trans. Inf. Theory 63(8): 4838-4849 (2017) - [c24]Aryeh Kontorovich, Sivan Sabato, Roi Weiss:
Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions. NIPS 2017: 1573-1583 - [i23]Aryeh Kontorovich, Sivan Sabato, Roi Weiss:
Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions. CoRR abs/1705.08184 (2017) - [i22]Eyal Gutflaish, Aryeh Kontorovich, Sivan Sabato, Ofer Biller, Oded Sofer:
Temporal anomaly detection: calibrating the surprise. CoRR abs/1705.10085 (2017) - [i21]Daniel J. Hsu, Aryeh Kontorovich, David A. Levin, Yuval Peres, Csaba Szepesvári:
Mixing time estimation in reversible Markov chains from a single sample path. CoRR abs/1708.07367 (2017) - [i20]Matan Levi, Yair Allouche, Aryeh Kontorovich:
Advanced Analytics for Connected Cars Cyber Security. CoRR abs/1711.01939 (2017) - 2016
- [j17]Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer:
Adaptive metric dimensionality reduction. Theor. Comput. Sci. 620: 105-118 (2016) - [j16]Daniel Berend, Aryeh Kontorovich:
The state complexity of random DFAs. Theor. Comput. Sci. 652: 102-108 (2016) - [c23]Lee-Ad Gottlieb, Aryeh Kontorovich, Pinhas Nisnevitch:
Nearly Optimal Classification for Semimetrics. AISTATS 2016: 379-388 - [c22]Aryeh Kontorovich, Sivan Sabato, Ruth Urner:
Active Nearest-Neighbor Learning in Metric Spaces. NIPS 2016: 856-864 - [i19]Aryeh Kontorovich, Maxim Raginsky:
Concentration of measure without independence: a unified approach via the martingale method. CoRR abs/1602.00721 (2016) - [i18]Aryeh Kontorovich, Sivan Sabato, Ruth Urner:
Active Nearest-Neighbor Learning in Metric Spaces. CoRR abs/1605.06792 (2016) - [i17]Aryeh Kontorovich, Iosif Pinelis:
Exact Lower Bounds for the Agnostic Probably-Approximately-Correct (PAC) Machine Learning Model. CoRR abs/1606.08920 (2016) - 2015
- [j15]Daniel Gordon, Danny Hendler, Aryeh Kontorovich, Lior Rokach:
Local-shapelets for fast classification of spectrographic measurements. Expert Syst. Appl. 42(6): 3150-3158 (2015) - [j14]Daniel Berend, Aryeh Kontorovich:
A finite sample analysis of the Naive Bayes classifier. J. Mach. Learn. Res. 16: 1519-1545 (2015) - [c21]Aryeh Kontorovich, Roi Weiss:
A Bayes consistent 1-NN classifier. AISTATS 2015 - [c20]Daniel J. Hsu, Aryeh Kontorovich, Csaba Szepesvári:
Mixing Time Estimation in Reversible Markov Chains from a Single Sample Path. NIPS 2015: 1459-1467 - [i16]Lee-Ad Gottlieb, Aryeh Kontorovich:
Nearly optimal classification for semimetrics. CoRR abs/1502.06208 (2015) - [i15]Daniel J. Hsu, Aryeh Kontorovich, Csaba Szepesvári:
Mixing Time Estimation in Reversible Markov Chains from a Single Sample Path. CoRR abs/1506.02903 (2015) - 2014
- [j13]Aryeh Kontorovich, Roi Weiss:
Uniform Chernoff and Dvoretzky-Kiefer-Wolfowitz-Type Inequalities for Markov Chains and Related Processes. J. Appl. Probab. 51(4): 1100-1113 (2014) - [j12]Aryeh Kontorovich, Ari Trachtenberg:
Deciding unique decodability of bigram counts via finite automata. J. Comput. Syst. Sci. 80(2): 450-456 (2014) - [j11]Daniel Berend, Peter Harremoës, Aryeh Kontorovich:
Minimum KL-Divergence on Complements of $L_{1}$ Balls. IEEE Trans. Inf. Theory 60(6): 3172-3177 (2014) - [j10]Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer:
Efficient Classification for Metric Data. IEEE Trans. Inf. Theory 60(9): 5750-5759 (2014) - [j9]Ohad Asor, Hubert Haoyang Duan, Aryeh Kontorovich:
On the Additive Properties of the Fat-Shattering Dimension. IEEE Trans. Neural Networks Learn. Syst. 25(12): 2309-2312 (2014) - [c19]Aryeh Kontorovich:
Concentration in unbounded metric spaces and algorithmic stability. ICML 2014: 28-36 - [c18]Aryeh Kontorovich, Roi Weiss:
Maximum Margin Multiclass Nearest Neighbors. ICML 2014: 892-900 - [c17]Dan Gutfreund, Aryeh Kontorovich, Ran Levy, Michal Rosen-Zvi:
Boosting Conditional Probability Estimators. ISAIM 2014 - [c16]Lee-Ad Gottlieb, Aryeh Kontorovich, Pinhas Nisnevitch:
Near-optimal sample compression for nearest neighbors. NIPS 2014: 370-378 - [c15]Daniel Berend, Aryeh Kontorovich:
Consistency of weighted majority votes. NIPS 2014: 3446-3454 - [i14]Aryeh Kontorovich, Roi Weiss:
Maximum Margin Multiclass Nearest Neighbors. CoRR abs/1401.7898 (2014) - [i13]Lee-Ad Gottlieb, Aryeh Kontorovich:
Near-optimal sample compression for nearest neighbors. CoRR abs/1404.3368 (2014) - [i12]Aryeh Kontorovich, Roi Weiss:
A Bayes consistent 1-NN classifier. CoRR abs/1407.0208 (2014) - 2013
- [j8]Dana Angluin, James Aspnes, Sarah Eisenstat, Aryeh Kontorovich:
On the learnability of shuffle ideals. J. Mach. Learn. Res. 14(1): 1513-1531 (2013) - [j7]Lena Chekina, Dan Gutfreund, Aryeh Kontorovich, Lior Rokach, Bracha Shapira:
Exploiting label dependencies for improved sample complexity. Mach. Learn. 91(1): 1-42 (2013) - [c14]Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer:
Adaptive Metric Dimensionality Reduction. ALT 2013: 279-293 - [c13]Aryeh Kontorovich, Boaz Nadler, Roi Weiss:
On learning parametric-output HMMs. ICML (3) 2013: 702-710 - [c12]Arnold Filtser, Jiaxi Jin, Aryeh Kontorovich, Ari Trachtenberg:
Efficient determination of the unique decodability of a string. ISIT 2013: 1411-1415 - [c11]Jiaxi Jin, Aryeh Kontorovich, Ari Trachtenberg:
Determining the unique decodability of a string in linear time. ITA 2013: 1-11 - [c10]Cosma Rohilla Shalizi, Aryeh Kontorovich:
Predictive PAC Learning and Process Decompositions. NIPS 2013: 1619-1627 - [c9]Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer:
Efficient Regression in Metric Spaces via Approximate Lipschitz Extension. SIMBAD 2013: 43-58 - [i11]Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer:
Adaptive Metric Dimensionality Reduction. CoRR abs/1302.2752 (2013) - [i10]Aryeh Kontorovich, Boaz Nadler, Roi Weiss:
On learning parametric-output HMMs. CoRR abs/1302.6009 (2013) - [i9]Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer:
Efficient Classification for Metric Data. CoRR abs/1306.2547 (2013) - [i8]Daniel Berend, Aryeh Kontorovich:
The state complexity of random DFAs. CoRR abs/1307.0720 (2013) - [i7]Aryeh Kontorovich:
Concentration in unbounded metric spaces and algorithmic stability. CoRR abs/1309.1007 (2013) - [i6]Daniel Berend, Aryeh Kontorovich:
Consistency of weighted majority votes. CoRR abs/1312.0451 (2013) - 2012
- [j6]Lee-Ad Gottlieb, Aryeh Kontorovich, Elchanan Mossel:
VC bounds on the cardinality of nearly orthogonal function classes. Discret. Math. 312(10): 1766-1775 (2012) - [j5]Leonid Kontorovich:
Statistical estimation with bounded memory. Stat. Comput. 22(5): 1155-1164 (2012) - [c8]Dana Angluin, James Aspnes, Aryeh Kontorovich:
On the Learnability of Shuffle Ideals. ALT 2012: 111-123 - [c7]Aryeh Kontorovich, Ari Trachtenberg:
String reconciliation with unknown edit distance. ISIT 2012: 2751-2755 - [i5]Aryeh Kontorovich, Ari Trachtenberg:
Efficiently decoding strings from their shingles. CoRR abs/1204.3293 (2012) - [i4]Daniel Berend, Aryeh Kontorovich:
A Reverse Pinsker Inequality. CoRR abs/1206.6544 (2012) - 2011
- [j4]Boaz Nadler, Leonid Kontorovich:
Model Selection for Sinusoids in Noise: Statistical Analysis and a New Penalty Term. IEEE Trans. Signal Process. 59(4): 1333-1345 (2011) - [c6]Aryeh Kontorovich, Danny Hendler, Eitan Menahem:
Metric Anomaly Detection via Asymmetric Risk Minimization. SIMBAD 2011: 17-30 - [i3]Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer:
Efficient Regression in Metric Spaces via Approximate Lipschitz Extension. CoRR abs/1111.4470 (2011) - [i2]Aryeh Kontorovich, Ari Trachtenberg:
Unique decodability of bigram counts by finite automata. CoRR abs/1111.6431 (2011) - 2010
- [c5]Dana Angluin, David Eisenstat, Leonid Kontorovich, Lev Reyzin:
Lower Bounds on Learning Random Structures with Statistical Queries. ALT 2010: 194-208 - [c4]Lee-Ad Gottlieb, Leonid Kontorovich, Robert Krauthgamer:
Efficient Classification for Metric Data. COLT 2010: 433-440
2000 – 2009
- 2009
- [j3]Leonid Kontorovich, Boaz Nadler:
Universal Kernel-Based Learning with Applications to Regular Languages. J. Mach. Learn. Res. 10: 1095-1129 (2009) - 2008
- [j2]Leonid Kontorovich, Corinna Cortes, Mehryar Mohri:
Kernel methods for learning languages. Theor. Comput. Sci. 405(3): 223-236 (2008) - 2007
- [c3]Corinna Cortes, Leonid Kontorovich, Mehryar Mohri:
Learning Languages with Rational Kernels. COLT 2007: 349-364 - [c2]Leonid Kontorovich:
A Universal Kernel for Learning Regular Languages. MLG 2007 - [i1]Leonid Kontorovich:
A Universal Kernel for Learning Regular Languages. CoRR abs/0712.0840 (2007) - 2006
- [c1]Leonid Kontorovich, Corinna Cortes, Mehryar Mohri:
Learning Linearly Separable Languages. ALT 2006: 288-303 - 2004
- [j1]Leonid Kontorovich:
Uniquely decodable n-gram embeddings. Theor. Comput. Sci. 329(1-3): 271-284 (2004)
Coauthor Index
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