Uniquely decodable n-gram embeddings. - Leonid Kontorovich (Theor. Comput. Sci., 2004)

Learning Linearly Separable Languages. - Leonid Kontorovich; Corinna Cortes; Mehryar Mohri (ALT, 2006)

Learning Languages with Rational Kernels. - Corinna Cortes; Leonid Kontorovich; Mehryar Mohri (COLT, 2007)

A Universal Kernel for Learning Regular Languages. - Leonid Kontorovich (MLG, 2007)

Kernel methods for learning languages. - Leonid Kontorovich; Corinna Cortes; Mehryar Mohri (Theor. Comput. Sci., 2008)

Universal Kernel-Based Learning with Applications to Regular Languages. - Leonid Kontorovich; Boaz Nadler (J. Mach. Learn. Res., 2009)

Lower Bounds on Learning Random Structures with Statistical Queries. - Dana Angluin; David Eisenstat; Leonid Kontorovich; Lev Reyzin (ALT, 2010)

Efficient Classification for Metric Data. - Lee-Ad Gottlieb; Leonid Kontorovich; Robert Krauthgamer (COLT, 2010)

Metric Anomaly Detection via Asymmetric Risk Minimization. - Aryeh Kontorovich; Danny Hendler; Eitan Menahem (SIMBAD, 2011)

Unique decodability of bigram counts by finite automata - Aryeh Kontorovich; Ari Trachtenberg (CoRR, 2011)

Model Selection for Sinusoids in Noise: Statistical Analysis and a New Penalty Term. - Boaz Nadler; Leonid Kontorovich (IEEE Trans. Signal Process., 2011)

On the Learnability of Shuffle Ideals. - Dana Angluin; James Aspnes; Aryeh Kontorovich (ALT, 2012)

String reconciliation with unknown edit distance. - Aryeh Kontorovich; Ari Trachtenberg (ISIT, 2012)

Efficiently decoding strings from their shingles - Aryeh Kontorovich; Ari Trachtenberg (CoRR, 2012)

A Reverse Pinsker Inequality - Daniel Berend; Aryeh Kontorovich (CoRR, 2012)

VC bounds on the cardinality of nearly orthogonal function classes. - Lee-Ad Gottlieb; Aryeh Kontorovich; Elchanan Mossel (Discret. Math., 2012)

Statistical estimation with bounded memory. - Leonid Kontorovich (Stat. Comput., 2012)

Adaptive Metric Dimensionality Reduction. - Lee-Ad Gottlieb; Aryeh Kontorovich; Robert Krauthgamer (ALT, 2013)

On learning parametric-output HMMs. - Aryeh Kontorovich; Boaz Nadler; Roi Weiss (ICML (3), 2013)

Efficient determination of the unique decodability of a string. - Arnold Filtser; Jiaxi Jin; Aryeh Kontorovich; Ari Trachtenberg (ISIT, 2013)

Determining the unique decodability of a string in linear time. - Jiaxi Jin; Aryeh Kontorovich; Ari Trachtenberg (ITA, 2013)

Predictive PAC Learning and Process Decompositions. - Cosma Rohilla Shalizi; Aryeh Kontorovich (NIPS, 2013)

Efficient Regression in Metric Spaces via Approximate Lipschitz Extension. - Lee-Ad Gottlieb; Aryeh Kontorovich; Robert Krauthgamer (SIMBAD, 2013)

On the learnability of shuffle ideals. - Dana Angluin; James Aspnes; Sarah Eisenstat; Aryeh Kontorovich (J. Mach. Learn. Res., 2013)

Exploiting label dependencies for improved sample complexity. - Lena Chekina; Dan Gutfreund; Aryeh Kontorovich; Lior Rokach; Bracha Shapira (Mach. Learn., 2013)

Concentration in unbounded metric spaces and algorithmic stability. - Aryeh Kontorovich (ICML, 2014)

Maximum Margin Multiclass Nearest Neighbors. - Aryeh Kontorovich; Roi Weiss (ICML, 2014)

Boosting Conditional Probability Estimators. - Dan Gutfreund; Aryeh Kontorovich; Ran Levy 001; Michal Rosen-Zvi (ISAIM, 2014)

Consistency of weighted majority votes. - Daniel Berend; Aryeh Kontorovich (NIPS, 2014)

Near-optimal sample compression for nearest neighbors. - Lee-Ad Gottlieb; Aryeh Kontorovich; Pinhas Nisnevitch (NIPS, 2014)

Near-optimal sample compression for nearest neighbors. - Lee-Ad Gottlieb; Aryeh Kontorovich (CoRR, 2014)

Uniform Chernoff and Dvoretzky-Kiefer-Wolfowitz-Type Inequalities for Markov Chains and Related Processes. - Aryeh Kontorovich; Roi Weiss (J. Appl. Probab., 2014)

Deciding unique decodability of bigram counts via finite automata. - Aryeh Kontorovich; Ari Trachtenberg (J. Comput. Syst. Sci., 2014)

Minimum KL-Divergence on Complements of $L_{1}$ Balls. - Daniel Berend; Peter Harremoës; Aryeh Kontorovich (IEEE Trans. Inf. Theory, 2014)

On the Additive Properties of the Fat-Shattering Dimension. - Ohad Asor; Hubert Haoyang Duan; Aryeh Kontorovich (IEEE Trans. Neural Networks Learn. Syst., 2014)

A Bayes consistent 1-NN classifier. - Aryeh Kontorovich; Roi Weiss (AISTATS, 2015)

Mixing Time Estimation in Reversible Markov Chains from a Single Sample Path. - Daniel J. Hsu; Aryeh Kontorovich; Csaba Szepesvári (NIPS, 2015)

Nearly optimal classification for semimetrics. - Lee-Ad Gottlieb; Aryeh Kontorovich (CoRR, 2015)

Local-shapelets for fast classification of spectrographic measurements. - Daniel Gordon; Danny Hendler; Aryeh Kontorovich; Lior Rokach (Expert Syst. Appl., 2015)

A finite sample analysis of the Naive Bayes classifier. - Daniel Berend; Aryeh Kontorovich (J. Mach. Learn. Res., 2015)

Nearly Optimal Classification for Semimetrics. - Lee-Ad Gottlieb; Aryeh Kontorovich; Pinhas Nisnevitch (AISTATS, 2016)

Active Nearest-Neighbor Learning in Metric Spaces. - Aryeh Kontorovich; Sivan Sabato; Ruth Urner (NIPS, 2016)

Exact Lower Bounds for the Agnostic Probably-Approximately-Correct (PAC) Machine Learning Model. - Aryeh Kontorovich; Iosif Pinelis (CoRR, 2016)

Concentration of measure without independence: a unified approach via the martingale method. - Aryeh Kontorovich; Maxim Raginsky (CoRR, 2016)

The state complexity of random DFAs. - Daniel Berend; Aryeh Kontorovich (Theor. Comput. Sci., 2016)

Nearest-Neighbor Sample Compression: Efficiency, Consistency, Infinite Dimensions. - Aryeh Kontorovich; Sivan Sabato; Roi Weiss (NIPS, 2017)

Mixing time estimation in reversible Markov chains from a single sample path. - Daniel J. Hsu; Aryeh Kontorovich; David A. Levin; Yuval Peres; Csaba Szepesvári (CoRR, 2017)

Advanced Analytics for Connected Cars Cyber Security. - Matan Levi; Yair Allouche; Aryeh Kontorovich (CoRR, 2017)

The Expected Missing Mass under an Entropy Constraint. - Daniel Berend; Aryeh Kontorovich; Gil Zagdanski (Entropy, 2017)

Learning convex polytopes with margin. - Lee-Ad Gottlieb; Eran Kaufman; Aryeh Kontorovich; Gabriel Nivasch (NeurIPS, 2018)

Advanced Analytics for Connected Car Cybersecurity. - Matan Levi; Yair Allouche; Aryeh Kontorovich (VTC Spring, 2018)

A New Lower Bound for Agnostic Learning with Sample Compression Schemes. - Steve Hanneke; Aryeh Kontorovich (CoRR, 2018)

Agnostic Sample Compression for Linear Regression. - Steve Hanneke; Aryeh Kontorovich; Menachem Sadigurschi (CoRR, 2018)

Temporal Anomaly Detection: Calibrating the Surprise. - Eyal Gutflaish; Aryeh Kontorovich; Sivan Sabato; Ofer Biller; Oded Sofer (AAAI, 2019)

Improved Generalization Bounds for Robust Learning. - Idan Attias; Aryeh Kontorovich; Yishay Mansour (ALT, 2019)

A Sharp Lower Bound for Agnostic Learning with Sample Compression Schemes. - Steve Hanneke; Aryeh Kontorovich (ALT, 2019)

Sample Compression for Real-Valued Learners. - Steve Hanneke; Aryeh Kontorovich; Menachem Sadigurschi (ALT, 2019)

Minimax Learning of Ergodic Markov Chains. - Geoffrey Wolfer; Aryeh Kontorovich (ALT, 2019)

Estimating the Mixing Time of Ergodic Markov Chains. - Geoffrey Wolfer; Aryeh Kontorovich (COLT, 2019)

Regression via Kirszbraun Extension with Applications to Imitation Learning. - Armin Biess; Aryeh Kontorovich; Yury Makarychev; Hanan Zaichyk (CoRR, 2019)

Optimality of SVM: Novel proofs and tighter bounds. - Steve Hanneke; Aryeh Kontorovich (Theor. Comput. Sci., 2019)

Fast and Bayes-consistent nearest neighbors. - Klim Efremenko; Aryeh Kontorovich; Moshe Noivirt (AISTATS, 2020)

Minimax Testing of Identity to a Reference Ergodic Markov Chain. - Geoffrey Wolfer; Aryeh Kontorovich (AISTATS, 2020)

Algorithmic Learning Theory 2020: Preface. - Aryeh Kontorovich; Gergely Neu (ALT, 2020)

Universal Bayes Consistency in Metric Spaces. - Steve Hanneke; Aryeh Kontorovich; Sivan Sabato; Roi Weiss (ITA, 2020)

Learning discrete distributions with infinite support. - Doron Cohen 002; Aryeh Kontorovich; Geoffrey Wolfer (NeurIPS, 2020)

On biased random walks, corrupted intervals, and learning under adversarial design. - Daniel Berend; Aryeh Kontorovich; Lev Reyzin; Thomas J. Robinson 001 (Ann. Math. Artif. Intell., 2020)

Non-parametric Binary regression in metric spaces with KL loss. - Ariel Avital; Klim Efremenko; Aryeh Kontorovich; David Toplin; Bo Waggoner (CoRR, 2020)

Nested Barycentric Coordinate System as an Explicit Feature Map. - Lee-Ad Gottlieb; Eran Kaufman; Aryeh Kontorovich; Gabriel Nivasch; Ofir Pele (AISTATS, 2021)

Stable Sample Compression Schemes: New Applications and an Optimal SVM Margin Bound. - Steve Hanneke; Aryeh Kontorovich (ALT, 2021)

Functions with average smoothness: structure, algorithms, and learning. - Yair Ashlagi; Lee-Ad Gottlieb; Aryeh Kontorovich (COLT, 2021)

Dimension-free empirical entropy estimation. - Doron Cohen 002; Aryeh Kontorovich; Aaron Koolyk; Geoffrey Wolfer (NeurIPS, 2021)

Apportioned margin approach for cost sensitive large margin classifiers. - Lee-Ad Gottlieb; Eran Kaufman; Aryeh Kontorovich (Ann. Math. Artif. Intell., 2021)

Fat-shattering dimension of k-fold maxima. - Aryeh Kontorovich; Idan Attias (CoRR, 2021)

Learning with metric losses. - Dan Tsir Cohen; Aryeh Kontorovich (COLT, 2022)

Adaptive Data Analysis with Correlated Observations. - Aryeh Kontorovich; Menachem Sadigurschi; Uri Stemmer (ICML, 2022)

Metric-valued regression. - Dan Tsir Cohen; Aryeh Kontorovich (CoRR, 2022)

Differentially-Private Bayes Consistency. - Olivier Bousquet; Haim Kaplan; Aryeh Kontorovich; Yishay Mansour; Shay Moran; Menachem Sadigurschi; Uri Stemmer (CoRR, 2022)

Non-uniform packings. - Lee-Ad Gottlieb; Aryeh Kontorovich (Inf. Process. Lett., 2022)

Improved Generalization Bounds for Adversarially Robust Learning. - Idan Attias; Aryeh Kontorovich; Yishay Mansour (J. Mach. Learn. Res., 2022)

Learning Convex Polyhedra With Margin. - Lee-Ad Gottlieb; Eran Kaufman; Aryeh Kontorovich; Gabriel Nivasch (IEEE Trans. Inf. Theory, 2022)

Domain Invariant Adversarial Learning. - Matan Levi; Idan Attias; Aryeh Kontorovich (Trans. Mach. Learn. Res., 2022)

Local Glivenko-Cantelli. - Doron Cohen 002; Aryeh Kontorovich (COLT, 2023)

Open problem: log(n) factor in "Local Glivenko-Cantelli. - Doron Cohen 002; Aryeh Kontorovich (COLT, 2023)

Near-optimal learning with average Hölder smoothness. - Guy Kornowski; Steve Hanneke; Aryeh Kontorovich (NeurIPS, 2023)

Tree Density Estimation. - László Györfi; Aryeh Kontorovich; Roi Weiss (IEEE Trans. Inf. Theory, 2023)

Efficient Agnostic Learning with Average Smoothness. - Steve Hanneke; Aryeh Kontorovich; Guy Kornowski (ALT, 2024)

Correlated Binomial Process. - Moïse Blanchard; Doron Cohen 002; Aryeh Kontorovich (COLT, 2024)

Super-Teaching in Machine Learning. - Dina Barak-Pelleg; Daniel Berend; Aryeh Kontorovich (CSCML, 2024)

Agnostic Sample Compression Schemes for Regression. - Idan Attias; Steve Hanneke; Aryeh Kontorovich; Menachem Sadigurschi (ICML, 2024)

Splitting the Difference on Adversarial Training. - Matan Levi; Aryeh Kontorovich (USENIX Security Symposium, 2024)

Distribution Estimation under the Infinity Norm. - Aryeh Kontorovich; Amichai Painsky (CoRR, 2024)

Aggregation of expert advice, revisited. - Aryeh Kontorovich (CoRR, 2024)

The MLE is minimax optimal for LGC. - Doron Cohen 002; Aryeh Kontorovich; Roi Weiss (CoRR, 2024)

Fat-Shattering Dimension of k-fold Aggregations. - Idan Attias; Aryeh Kontorovich (J. Mach. Learn. Res., 2024)

Efficient Kirszbraun extension with applications to regression. - Hananel Zaichyk; Armin Biess; Aryeh Kontorovich; Yury Makarychev (Math. Program., 2024)

Correction: Efficient Kirszbraun extension with applications to regression. - Hananel Zaichyk; Armin Biess; Aryeh Kontorovich; Yury Makarychev (Math. Program., 2024)

Nested barycentric coordinate system as an explicit feature map for polyhedra approximation and learning tasks. - Lee-Ad Gottlieb; Eran Kaufman; Aryeh Kontorovich; Gabriel Nivasch; Ofir Pele (Mach. Learn., 2024)

Sharp bounds on aggregate expert error. - Aryeh Kontorovich; Ariel Avital (ALT, 2025)

Bounded Variation Separates Weak and Strong Average Lipschitz. - Ariel Elperin; Aryeh Kontorovich (Entropy, 2025)

ParallelTime: Dynamically Weighting the Balance of Short- and Long-Term Temporal Dependencies. - Itay Katav; Aryeh Kontorovich (CoRR, 2025)