Aryeh Kontorovich

135 papers A* 17A 5B 13Misc 3Journal 86Unranked 11

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Bounded Variation Separates Weak and Strong Average Lipschitz. Entropy Ariel Elperin, Aryeh Kontorovich
2025	J	`jnl`	Distribution Estimation under the Infinity Norm. J. Mach. Learn. Res. Aryeh Kontorovich, Amichai Painsky
2025	J	`jnl`	ParallelTime: Dynamically Weighting the Balance of Short- and Long-Term Temporal Dependencies. CoRR Itay Katav, Aryeh Kontorovich
2025	B	`conf`	Sharp bounds on aggregate expert error. ALT Aryeh Kontorovich, Ariel Avital
2025	A*	`conf`	The Empirical Mean is Minimax Optimal for Local Glivenko-Cantelli. ICML Doron Cohen, Aryeh Kontorovich, Roi Weiss
2024	J	`jnl`	Aggregation of expert advice, revisited. CoRR Aryeh Kontorovich
2024	A*	`conf`	Agnostic Sample Compression Schemes for Regression. ICML Idan Attias, Steve Hanneke, Aryeh Kontorovich, Menachem Sadigurschi
2024	J	`jnl`	Correction: Efficient Kirszbraun extension with applications to regression. Math. Program. Hananel Zaichyk, Armin Biess, Aryeh Kontorovich, Yury Makarychev
2024	A*	`conf`	Correlated Binomial Process. COLT Moïse Blanchard, Doron Cohen, Aryeh Kontorovich
2024	J	`jnl`	Distribution Estimation under the Infinity Norm. CoRR Aryeh Kontorovich, Amichai Painsky
2024	B	`conf`	Efficient Agnostic Learning with Average Smoothness. ALT Steve Hanneke, Aryeh Kontorovich, Guy Kornowski
2024	J	`jnl`	Efficient Kirszbraun extension with applications to regression. Math. Program. Hananel Zaichyk, Armin Biess, Aryeh Kontorovich, Yury Makarychev
2024	J	`jnl`	Fat-Shattering Dimension of k-fold Aggregations. J. Mach. Learn. Res. Idan Attias, Aryeh Kontorovich
2024	J	`jnl`	Functions with average smoothness: structure, algorithms, and learning. J. Mach. Learn. Res. Yair Ashlagi, Lee-Ad Gottlieb, Aryeh Kontorovich
2024	J	`jnl`	Nested barycentric coordinate system as an explicit feature map for polyhedra approximation and learning tasks. Mach. Learn. Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch, Ofir Pele
2024	A*	`conf`	Splitting the Difference on Adversarial Training. USENIX Security Symposium Matan Levi, Aryeh Kontorovich
2024	—	`conf`	Super-Teaching in Machine Learning. CSCML Dina Barak-Pelleg, Daniel Berend, Aryeh Kontorovich
2024	J	`jnl`	The MLE is minimax optimal for LGC. CoRR Doron Cohen, Aryeh Kontorovich, Roi Weiss
2023	J	`jnl`	Dimension-Free Empirical Entropy Estimation. IEEE Trans. Inf. Theory Doron Cohen, Aryeh Kontorovich, Aaron Koolyk, Geoffrey Wolfer
2023	J	`jnl`	Efficient Agnostic Learning with Average Smoothness. CoRR Steve Hanneke, Aryeh Kontorovich, Guy Kornowski
2023	A*	`conf`	Local Glivenko-Cantelli. COLT Doron Cohen, Aryeh Kontorovich
2023	A*	`conf`	Near-optimal learning with average Hölder smoothness. NeurIPS Guy Kornowski, Steve Hanneke, Aryeh Kontorovich
2023	J	`jnl`	Near-optimal learning with average Hölder smoothness. CoRR Steve Hanneke, Aryeh Kontorovich, Guy Kornowski
2023	A*	`conf`	Open problem: log(n) factor in "Local Glivenko-Cantelli. COLT Doron Cohen, Aryeh Kontorovich
2023	J	`jnl`	Splitting the Difference on Adversarial Training. CoRR Matan Levi, Aryeh Kontorovich
2023	J	`jnl`	Tree Density Estimation. IEEE Trans. Inf. Theory László Györfi, Aryeh Kontorovich, Roi Weiss
2022	A*	`conf`	Adaptive Data Analysis with Correlated Observations. ICML Aryeh Kontorovich, Menachem Sadigurschi, Uri Stemmer
2022	J	`jnl`	Adaptive Data Analysis with Correlated Observations. CoRR Aryeh Kontorovich, Menachem Sadigurschi, Uri Stemmer
2022	J	`jnl`	Differentially-Private Bayes Consistency. CoRR Olivier Bousquet, Haim Kaplan, Aryeh Kontorovich, Yishay Mansour, Shay Moran, Menachem Sadigurschi, Uri Stemmer
2022	J	`jnl`	Domain Invariant Adversarial Learning. Trans. Mach. Learn. Res. Matan Levi, Idan Attias, Aryeh Kontorovich
2022	J	`jnl`	Improved Generalization Bounds for Adversarially Robust Learning. J. Mach. Learn. Res. Idan Attias, Aryeh Kontorovich, Yishay Mansour
2022	J	`jnl`	Learning Convex Polyhedra With Margin. IEEE Trans. Inf. Theory Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch
2022	A*	`conf`	Learning with metric losses. COLT Dan Tsir Cohen, Aryeh Kontorovich
2022	J	`jnl`	Metric-valued regression. CoRR Dan Tsir Cohen, Aryeh Kontorovich
2022	J	`jnl`	Non-uniform packings. Inf. Process. Lett. Lee-Ad Gottlieb, Aryeh Kontorovich
2021	J	`jnl`	Apportioned margin approach for cost sensitive large margin classifiers. Ann. Math. Artif. Intell. Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich
2021	J	`jnl`	Dimension-Free Empirical Entropy Estimation. CoRR Doron Cohen, Aryeh Kontorovich, Aaron Koolyk, Geoffrey Wolfer
2021	A*	`conf`	Dimension-free empirical entropy estimation. NeurIPS Doron Cohen, Aryeh Kontorovich, Aaron Koolyk, Geoffrey Wolfer
2021	J	`jnl`	Domain Invariant Adversarial Learning. CoRR Matan Levi, Idan Attias, Aryeh Kontorovich
2021	J	`jnl`	Fat-shattering dimension of k-fold maxima. CoRR Aryeh Kontorovich, Idan Attias
2021	A*	`conf`	Functions with average smoothness: structure, algorithms, and learning. COLT Yair Ashlagi, Lee-Ad Gottlieb, Aryeh Kontorovich
2021	A	`conf`	Nested Barycentric Coordinate System as an Explicit Feature Map. AISTATS Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch, Ofir Pele
2021	B	`conf`	Stable Sample Compression Schemes: New Applications and an Optimal SVM Margin Bound. ALT Steve Hanneke, Aryeh Kontorovich
2021	J	`jnl`	Tree density estimation. CoRR László Györfi, Aryeh Kontorovich, Roi Weiss
2020	B	`conf`	Algorithmic Learning Theory 2020: Preface. ALT Aryeh Kontorovich, Gergely Neu
2020	B	`ed.`	Algorithmic Learning Theory, ALT 2020, 8-11 February 2020, San Diego, CA, USA. ALT Aryeh Kontorovich, Gergely Neu
2020	J	`jnl`	Apportioned Margin Approach for Cost Sensitive Large Margin Classifiers. CoRR Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich
2020	A	`conf`	Fast and Bayes-consistent nearest neighbors. AISTATS Klim Efremenko, Aryeh Kontorovich, Moshe Noivirt
2020	J	`jnl`	Functions with average smoothness: structure, algorithms, and learning. CoRR Yair Ashlagi, Lee-Ad Gottlieb, Aryeh Kontorovich
2020	A*	`conf`	Learning discrete distributions with infinite support. NeurIPS Doron Cohen, Aryeh Kontorovich, Geoffrey Wolfer
2020	A	`conf`	Minimax Testing of Identity to a Reference Ergodic Markov Chain. AISTATS Geoffrey Wolfer, Aryeh Kontorovich
2020	J	`jnl`	Nested Barycentric Coordinate System as an Explicit Feature Map. CoRR Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch, Ofir Pele
2020	J	`jnl`	Non-parametric Binary regression in metric spaces with KL loss. CoRR Ariel Avital, Klim Efremenko, Aryeh Kontorovich, David Toplin, Bo Waggoner
2020	J	`jnl`	On Biased Random Walks, Corrupted Intervals, and Learning Under Adversarial Design. CoRR Daniel Berend, Aryeh Kontorovich, Lev Reyzin, Thomas J. Robinson
2020	J	`jnl`	On biased random walks, corrupted intervals, and learning under adversarial design. Ann. Math. Artif. Intell. Daniel Berend, Aryeh Kontorovich, Lev Reyzin, Thomas J. Robinson
2020	J	`jnl`	Stable Sample Compression Schemes: New Applications and an Optimal SVM Margin Bound. CoRR Steve Hanneke, Aryeh Kontorovich
2020	Misc	`conf`	Universal Bayes Consistency in Metric Spaces. ITA Steve Hanneke, Aryeh Kontorovich, Sivan Sabato, Roi Weiss
2019	B	`conf`	A Sharp Lower Bound for Agnostic Learning with Sample Compression Schemes. ALT Steve Hanneke, Aryeh Kontorovich
2019	A*	`conf`	Estimating the Mixing Time of Ergodic Markov Chains. COLT Geoffrey Wolfer, Aryeh Kontorovich
2019	J	`jnl`	Estimating the Mixing Time of Ergodic Markov Chains. CoRR Geoffrey Wolfer, Aryeh Kontorovich
2019	J	`jnl`	Fast and Bayes-consistent nearest neighbors. CoRR Klim Efremenko, Aryeh Kontorovich, Moshe Noivirt
2019	B	`conf`	Improved Generalization Bounds for Robust Learning. ALT Idan Attias, Aryeh Kontorovich, Yishay Mansour
2019	B	`conf`	Minimax Learning of Ergodic Markov Chains. ALT Geoffrey Wolfer, Aryeh Kontorovich
2019	J	`jnl`	Optimality of SVM: Novel proofs and tighter bounds. Theor. Comput. Sci. Steve Hanneke, Aryeh Kontorovich
2019	J	`jnl`	Regression via Kirszbraun Extension with Applications to Imitation Learning. CoRR Armin Biess, Aryeh Kontorovich, Yury Makarychev, Hanan Zaichyk
2019	B	`conf`	Sample Compression for Real-Valued Learners. ALT Steve Hanneke, Aryeh Kontorovich, Menachem Sadigurschi
2019	A*	`conf`	Temporal Anomaly Detection: Calibrating the Surprise. AAAI Eyal Gutflaish, Aryeh Kontorovich, Sivan Sabato, Ofer Biller, Oded Sofer
2019	J	`jnl`	Universal Bayes consistency in metric spaces. CoRR Steve Hanneke, Aryeh Kontorovich, Sivan Sabato, Roi Weiss
2018	J	`jnl`	A New Lower Bound for Agnostic Learning with Sample Compression Schemes. CoRR Steve Hanneke, Aryeh Kontorovich
2018	—	`conf`	Advanced Analytics for Connected Car Cybersecurity. VTC Spring Matan Levi, Yair Allouche, Aryeh Kontorovich
2018	J	`jnl`	Agnostic Sample Compression for Linear Regression. CoRR Steve Hanneke, Aryeh Kontorovich, Menachem Sadigurschi
2018	J	`jnl`	Improved generalization bounds for robust learning. CoRR Idan Attias, Aryeh Kontorovich, Yishay Mansour
2018	A*	`conf`	Learning convex polytopes with margin. NeurIPS Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch
2018	J	`jnl`	Learning convex polytopes with margin. CoRR Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch
2018	J	`jnl`	Minimax Learning of Ergodic Markov Chains. CoRR Geoffrey Wolfer, Aryeh Kontorovich
2018	J	`jnl`	Near-Optimal Sample Compression for Nearest Neighbors. IEEE Trans. Inf. Theory Lee-Ad Gottlieb, Aryeh Kontorovich, Pinhas Nisnevitch
2018	J	`jnl`	Sample Compression for Real-Valued Learners. CoRR Steve Hanneke, Aryeh Kontorovich, Menachem Sadigurschi
2017	J	`jnl`	Active Nearest-Neighbor Learning in Metric Spaces. J. Mach. Learn. Res. Aryeh Kontorovich, Sivan Sabato, Ruth Urner
2017	J	`jnl`	Advanced Analytics for Connected Cars Cyber Security. CoRR Matan Levi, Yair Allouche, Aryeh Kontorovich
2017	J	`jnl`	Boosting conditional probability estimators. Ann. Math. Artif. Intell. Dan Gutfreund, Aryeh Kontorovich, Ran Levy, Michal Rosen-Zvi
2017	J	`jnl`	Efficient Regression in Metric Spaces via Approximate Lipschitz Extension. IEEE Trans. Inf. Theory Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer
2017	J	`jnl`	Mixing time estimation in reversible Markov chains from a single sample path. CoRR Daniel J. Hsu, Aryeh Kontorovich, David A. Levin, Yuval Peres, Csaba Szepesvári
2017	—	`conf`	Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions. NIPS Aryeh Kontorovich, Sivan Sabato, Roi Weiss
2017	J	`jnl`	Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions. CoRR Aryeh Kontorovich, Sivan Sabato, Roi Weiss
2017	J	`jnl`	Nearly optimal classification for semimetrics. J. Mach. Learn. Res. Lee-Ad Gottlieb, Aryeh Kontorovich, Pinhas Nisnevitch
2017	J	`jnl`	Temporal anomaly detection: calibrating the surprise. CoRR Eyal Gutflaish, Aryeh Kontorovich, Sivan Sabato, Ofer Biller, Oded Sofer
2017	J	`jnl`	The Expected Missing Mass under an Entropy Constraint. Entropy Daniel Berend, Aryeh Kontorovich, Gil Zagdanski
2016	—	`conf`	Active Nearest-Neighbor Learning in Metric Spaces. NIPS Aryeh Kontorovich, Sivan Sabato, Ruth Urner
2016	J	`jnl`	Active Nearest-Neighbor Learning in Metric Spaces. CoRR Aryeh Kontorovich, Sivan Sabato, Ruth Urner
2016	J	`jnl`	Adaptive metric dimensionality reduction. Theor. Comput. Sci. Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer
2016	J	`jnl`	Concentration of measure without independence: a unified approach via the martingale method. CoRR Aryeh Kontorovich, Maxim Raginsky
2016	J	`jnl`	Exact Lower Bounds for the Agnostic Probably-Approximately-Correct (PAC) Machine Learning Model. CoRR Aryeh Kontorovich, Iosif Pinelis
2016	A	`conf`	Nearly Optimal Classification for Semimetrics. AISTATS Lee-Ad Gottlieb, Aryeh Kontorovich, Pinhas Nisnevitch
2016	J	`jnl`	The state complexity of random DFAs. Theor. Comput. Sci. Daniel Berend, Aryeh Kontorovich
2015	A	`conf`	A Bayes consistent 1-NN classifier. AISTATS Aryeh Kontorovich, Roi Weiss
2015	J	`jnl`	A finite sample analysis of the Naive Bayes classifier. J. Mach. Learn. Res. Daniel Berend, Aryeh Kontorovich
2015	J	`jnl`	Local-shapelets for fast classification of spectrographic measurements. Expert Syst. Appl. Daniel Gordon, Danny Hendler, Aryeh Kontorovich, Lior Rokach
2015	—	`conf`	Mixing Time Estimation in Reversible Markov Chains from a Single Sample Path. NIPS Daniel J. Hsu, Aryeh Kontorovich, Csaba Szepesvári
2015	J	`jnl`	Mixing Time Estimation in Reversible Markov Chains from a Single Sample Path. CoRR Daniel J. Hsu, Aryeh Kontorovich, Csaba Szepesvári
2015	J	`jnl`	Nearly optimal classification for semimetrics. CoRR Lee-Ad Gottlieb, Aryeh Kontorovich
2014	J	`jnl`	A Bayes consistent 1-NN classifier. CoRR Aryeh Kontorovich, Roi Weiss
2014	Misc	`conf`	Boosting Conditional Probability Estimators. ISAIM Dan Gutfreund, Aryeh Kontorovich, Ran Levy, Michal Rosen-Zvi
2014	A*	`conf`	Concentration in unbounded metric spaces and algorithmic stability. ICML Aryeh Kontorovich
2014	—	`conf`	Consistency of weighted majority votes. NIPS Daniel Berend, Aryeh Kontorovich
2014	J	`jnl`	Deciding unique decodability of bigram counts via finite automata. J. Comput. Syst. Sci. Aryeh Kontorovich, Ari Trachtenberg
2014	J	`jnl`	Efficient Classification for Metric Data. IEEE Trans. Inf. Theory Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer
2014	A*	`conf`	Maximum Margin Multiclass Nearest Neighbors. ICML Aryeh Kontorovich, Roi Weiss
2014	J	`jnl`	Maximum Margin Multiclass Nearest Neighbors. CoRR Aryeh Kontorovich, Roi Weiss
2014	J	`jnl`	Minimum KL-Divergence on Complements of $L_{1}$ Balls. IEEE Trans. Inf. Theory Daniel Berend, Peter Harremoës, Aryeh Kontorovich
2014	—	`conf`	Near-optimal sample compression for nearest neighbors. NIPS Lee-Ad Gottlieb, Aryeh Kontorovich, Pinhas Nisnevitch
2014	J	`jnl`	Near-optimal sample compression for nearest neighbors. CoRR Lee-Ad Gottlieb, Aryeh Kontorovich
2014	J	`jnl`	On the Additive Properties of the Fat-Shattering Dimension. IEEE Trans. Neural Networks Learn. Syst. Ohad Asor, Hubert Haoyang Duan, Aryeh Kontorovich
2014	J	`jnl`	Uniform Chernoff and Dvoretzky-Kiefer-Wolfowitz-Type Inequalities for Markov Chains and Related Processes. J. Appl. Probab. Aryeh Kontorovich, Roi Weiss
2013	J	`jnl`	Adaptive Metric Dimensionality Reduction CoRR Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer
2013	B	`conf`	Adaptive Metric Dimensionality Reduction. ALT Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer
2013	J	`jnl`	Concentration in unbounded metric spaces and algorithmic stability. CoRR Aryeh Kontorovich
2013	J	`jnl`	Consistency of weighted majority votes. CoRR Daniel Berend, Aryeh Kontorovich
2013	Misc	`conf`	Determining the unique decodability of a string in linear time. ITA Jiaxi Jin, Aryeh Kontorovich, Ari Trachtenberg
2013	J	`jnl`	Efficient Classification for Metric Data. CoRR Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer
2013	—	`conf`	Efficient Regression in Metric Spaces via Approximate Lipschitz Extension. SIMBAD Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer
2013	B	`conf`	Efficient determination of the unique decodability of a string. ISIT Arnold Filtser, Jiaxi Jin, Aryeh Kontorovich, Ari Trachtenberg
2013	J	`jnl`	Exploiting label dependencies for improved sample complexity. Mach. Learn. Lena Chekina, Dan Gutfreund, Aryeh Kontorovich, Lior Rokach, Bracha Shapira
2013	J	`jnl`	On learning parametric-output HMMs CoRR Aryeh Kontorovich, Boaz Nadler, Roi Weiss
2013	—	`conf`	On learning parametric-output HMMs. ICML (3) Aryeh Kontorovich, Boaz Nadler, Roi Weiss
2013	J	`jnl`	On the learnability of shuffle ideals. J. Mach. Learn. Res. Dana Angluin, James Aspnes, Sarah Eisenstat, Aryeh Kontorovich
2013	—	`conf`	Predictive PAC Learning and Process Decompositions. NIPS Cosma Rohilla Shalizi, Aryeh Kontorovich
2013	J	`jnl`	The state complexity of random DFAs. CoRR Daniel Berend, Aryeh Kontorovich
2012	J	`jnl`	A Reverse Pinsker Inequality CoRR Daniel Berend, Aryeh Kontorovich
2012	J	`jnl`	Efficiently decoding strings from their shingles CoRR Aryeh Kontorovich, Ari Trachtenberg
2012	B	`conf`	On the Learnability of Shuffle Ideals. ALT Dana Angluin, James Aspnes, Aryeh Kontorovich
2012	B	`conf`	String reconciliation with unknown edit distance. ISIT Aryeh Kontorovich, Ari Trachtenberg
2012	J	`jnl`	VC bounds on the cardinality of nearly orthogonal function classes. Discret. Math. Lee-Ad Gottlieb, Aryeh Kontorovich, Elchanan Mossel
2011	J	`jnl`	Efficient Regression in Metric Spaces via Approximate Lipschitz Extension CoRR Lee-Ad Gottlieb, Aryeh Kontorovich, Robert Krauthgamer
2011	—	`conf`	Metric Anomaly Detection via Asymmetric Risk Minimization. SIMBAD Aryeh Kontorovich, Danny Hendler, Eitan Menahem
2011	J	`jnl`	Unique decodability of bigram counts by finite automata CoRR Aryeh Kontorovich, Ari Trachtenberg