Mohri, Mehryar

159 publications

ICML 2025 Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data Corinna Cortes, Anqi Mao, Mehryar Mohri, Yutao Zhong

ALT 2025 Enhanced $h$-Consistency Bounds Anqi Mao, Mehryar Mohri, Yutao Zhong

NeurIPS 2025 High-Dimensional Calibration from Swap Regret Maxwell Fishelson, Noah Golowich, Mehryar Mohri, Jon Schneider

NeurIPS 2025 Improved Balanced Classification with Theoretically Grounded Loss Functions Corinna Cortes, Mehryar Mohri, Yutao Zhong

ICML 2025 Mastering Multiple-Expert Routing: Realizable $h$-Consistency and Strong Guarantees for Learning to Defer Anqi Mao, Mehryar Mohri, Yutao Zhong

ICML 2025 Principled Algorithms for Optimizing Generalized Metrics in Binary Classification Anqi Mao, Mehryar Mohri, Yutao Zhong

NeurIPS 2025 Principled Model Routing for Unknown Mixtures of Source Domains Christoph Dann, Yishay Mansour, Teodor Vanislavov Marinov, Mehryar Mohri

COLT 2025 Rate-Preserving Reductions for Blackwell Approachability Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan

ICML 2024 $h$-Consistency Guarantees for Regression Anqi Mao, Mehryar Mohri, Yutao Zhong

NeurIPS 2024 A Universal Growth Rate for Learning with Smooth Surrogate Losses Anqi Mao, Mehryar Mohri, Yutao Zhong

NeurIPS 2024 Cardinality-Aware Set Prediction and Top-$k$ Classification Corinna Cortes, Anqi Mao, Christopher Mohri, Mehryar Mohri, Yutao Zhong

ICML 2024 Differentially Private Domain Adaptation with Theoretical Guarantees Raef Bassily, Corinna Cortes, Anqi Mao, Mehryar Mohri

NeurIPSW 2024 Domain Adaptation for Robust Model Routing Christoph Dann, Yishay Mansour, Teodor Vanislavov Marinov, Mehryar Mohri

NeurIPS 2024 Multi-Label Learning with Stronger Consistency Guarantees Anqi Mao, Mehryar Mohri, Yutao Zhong

ALT 2024 Predictor-Rejector Multi-Class Abstention: Theoretical Analysis and Algorithms Anqi Mao, Mehryar Mohri, Yutao Zhong

NeurIPS 2024 Realizable $h$-Consistent and Bayes-Consistent Loss Functions for Learning to Defer Anqi Mao, Mehryar Mohri, Yutao Zhong

ICML 2024 Regression with Multi-Expert Deferral Anqi Mao, Mehryar Mohri, Yutao Zhong

AISTATS 2024 Theoretically Grounded Loss Functions and Algorithms for Score-Based Multi-Class Abstention Anqi Mao, Mehryar Mohri, Yutao Zhong

ICML 2023 $h$-Consistency Bounds for Pairwise Misranking Loss Surrogates Anqi Mao, Mehryar Mohri, Yutao Zhong

NeurIPS 2023 $h$-Consistency Bounds: Characterization and Extensions Anqi Mao, Mehryar Mohri, Yutao Zhong

ICML 2023 Cross-Entropy Loss Functions: Theoretical Analysis and Applications Anqi Mao, Mehryar Mohri, Yutao Zhong

AISTATS 2023 Principled Approaches for Private Adaptation from a Public Source Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh

ALT 2023 Pseudonorm Approachability and Applications to Regret Minimization Christoph Dann, Yishay Mansour, Mehryar Mohri, Jon Schneider, Balubramanian Sivan

ICMLW 2023 Ranking with Abstention Anqi Mao, Mehryar Mohri, Yutao Zhong

ICML 2023 Reinforcement Learning Can Be More Efficient with Multiple Rewards Christoph Dann, Yishay Mansour, Mehryar Mohri

NeurIPS 2023 Structured Prediction with Stronger Consistency Guarantees Anqi Mao, Mehryar Mohri, Yutao Zhong

AISTATS 2023 Theoretically Grounded Loss Functions and Algorithms for Adversarial Robustness Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong

NeurIPS 2023 Two-Stage Learning to Defer with Multiple Experts Anqi Mao, Christopher Mohri, Mehryar Mohri, Yutao Zhong

NeurIPSW 2022 A Theory of Learning with Competing Objectives and User Feedback Pranjal Awasthi, Corinna Cortes, Yishay Mansour, Mehryar Mohri

NeurIPSW 2022 AdaME: Adaptive Learning of Multisource Adaptationensembles Scott Yak, Javier Gonzalvo, Mehryar Mohri, Corinna Cortes

NeurIPS 2022 Differentially Private Learning with Margin Guarantees Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh

ICML 2022 Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation Chris Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan

ICML 2022 H-Consistency Bounds for Surrogate Loss Minimizers Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong

NeurIPS 2022 Multi-Class $h$-Consistency Bounds Pranjal Awasthi, Anqi Mao, Mehryar Mohri, Yutao Zhong

COLT 2022 Open Problem: Better Differentially Private Learning Algorithms with Margin Guarantees Raef Bassily, Mehryar Mohri, Ananda Theertha Suresh

COLT 2022 Open Problem: Finite-Time Instance Dependent Optimality for Stochastic Online Learning with Feedback Graphs Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert

NeurIPS 2022 Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert

COLT 2022 Strategizing Against Learners in Bayesian Games Yishay Mansour, Mehryar Mohri, Jon Schneider, Balasubramanian Sivan

AISTATS 2021 A Theory of Multiple-Source Adaptation with Limited Target Labeled Data Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh, Ke Wu

AISTATS 2021 Corralling Stochastic Bandit Algorithms Raman Arora, Teodor Vanislavov Marinov, Mehryar Mohri

ICML 2021 A Discriminative Technique for Multiple-Source Adaptation Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh, Ningshan Zhang

NeurIPS 2021 A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning Christoph Dann, Mehryar Mohri, Tong Zhang, Julian Zimmert

FnTML 2021 Advances and Open Problems in Federated Learning Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao

NeurIPS 2021 Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations Ayush Sekhari, Christoph Dann, Mehryar Mohri, Yishay Mansour, Karthik Sridharan

NeurIPS 2021 Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning Christoph Dann, Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert

NeurIPS 2021 Boosting with Multiple Sources Corinna Cortes, Mehryar Mohri, Dmitry Storcheus, Ananda Theertha Suresh

NeurIPS 2021 Breaking the Centralized Barrier for Cross-Device Federated Learning Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale, Mehryar Mohri, Sashank Reddi, Sebastian U Stich, Ananda Theertha Suresh

NeurIPS 2021 Calibration and Consistency of Adversarial Surrogate Losses Pranjal Awasthi, Natalie Frank, Anqi Mao, Mehryar Mohri, Yutao Zhong

NeurIPS 2021 Learning with User-Level Privacy Daniel Levy, Ziteng Sun, Kareem Amin, Satyen Kale, Alex Kulesza, Mehryar Mohri, Ananda Theertha Suresh

NeurIPS 2021 On the Existence of the Adversarial Bayes Classifier Pranjal Awasthi, Natalie Frank, Mehryar Mohri

ICML 2021 Relative Deviation Margin Bounds Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh

NeurIPS 2020 Adapting to Misspecification in Contextual Bandits Dylan J Foster, Claudio Gentile, Mehryar Mohri, Julian Zimmert

ICML 2020 Adaptive Region-Based Active Learning Corinna Cortes, Giulia Desalvo, Claudio Gentile, Mehryar Mohri, Ningshan Zhang

ICML 2020 Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks Pranjal Awasthi, Natalie Frank, Mehryar Mohri

NeurIPS 2020 Agnostic Learning with Multiple Objectives Corinna Cortes, Mehryar Mohri, Javier Gonzalvo, Dmitry Storcheus

ICML 2020 FedBoost: A Communication-Efficient Algorithm for Federated Learning Jenny Hamer, Mehryar Mohri, Ananda Theertha Suresh

ICML 2020 Online Learning with Dependent Stochastic Feedback Graphs Corinna Cortes, Giulia Desalvo, Claudio Gentile, Mehryar Mohri, Ningshan Zhang

NeurIPS 2020 PAC-Bayes Learning Bounds for Sample-Dependent Priors Pranjal Awasthi, Satyen Kale, Stefani Karp, Mehryar Mohri

NeurIPS 2020 Reinforcement Learning with Feedback Graphs Christoph Dann, Yishay Mansour, Mehryar Mohri, Ayush Sekhari, Karthik Sridharan

ICML 2020 SCAFFOLD: Stochastic Controlled Averaging for Federated Learning Sai Praneeth Karimireddy, Satyen Kale, Mehryar Mohri, Sashank Reddi, Sebastian Stich, Ananda Theertha Suresh

ICML 2019 Active Learning with Disagreement Graphs Corinna Cortes, Giulia Desalvo, Mehryar Mohri, Ningshan Zhang, Claudio Gentile

JMLR 2019 Adaptation Based on Generalized Discrepancy Corinna Cortes, Mehryar Mohri, Andrés Muñoz Medina

ICML 2019 Agnostic Federated Learning Mehryar Mohri, Gary Sivek, Ananda Theertha Suresh

NeurIPS 2019 Bandits with Feedback Graphs and Switching Costs Raman Arora, Teodor Vanislavov Marinov, Mehryar Mohri

NeurIPS 2019 Hypothesis Set Stability and Generalization Dylan J Foster, Spencer Greenberg, Satyen Kale, Haipeng Luo, Mehryar Mohri, Karthik Sridharan

NeurIPS 2019 Learning GANs and Ensembles Using Discrepancy Ben Adlam, Corinna Cortes, Mehryar Mohri, Ningshan Zhang

ICML 2019 Online Learning with Sleeping Experts and Feedback Graphs Corinna Cortes, Giulia Desalvo, Claudio Gentile, Mehryar Mohri, Scott Yang

ALT 2019 Online Non-Additive Path Learning Under Full and Partial Information Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, Holakou Rahmanian, Manfred Warmuth

AISTATS 2019 Region-Based Active Learning Corinna Cortes, Giulia DeSalvo, Claudio Gentile, Mehryar Mohri, Ningshan Zhang

NeurIPS 2019 Regularized Gradient Boosting Corinna Cortes, Mehryar Mohri, Dmitry Storcheus

ALT 2018 Algorithmic Learning Theory ALT 2018: Preface Mehryar Mohri, Karthik Sridharan

NeurIPS 2018 Algorithms and Theory for Multiple-Source Adaptation Judy Hoffman, Mehryar Mohri, Ningshan Zhang

AISTATS 2018 Competing with Automata-Based Expert Sequences Mehryar Mohri, Scott Yang

NeurIPS 2018 Efficient Gradient Computation for Structured Output Learning with Rational and Tropical Losses Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, Dmitry Storcheus, Scott Yang

COLT 2018 Logistic Regression: The Importance of Being Improper Dylan J. Foster, Satyen Kale, Haipeng Luo, Mehryar Mohri, Karthik Sridharan

ICML 2018 Online Learning with Abstention Corinna Cortes, Giulia DeSalvo, Claudio Gentile, Mehryar Mohri, Scott Yang

NeurIPS 2018 Policy Regret in Repeated Games Raman Arora, Michael Dinitz, Teodor Vanislavov Marinov, Mehryar Mohri

ICML 2017 AdaNet: Adaptive Structural Learning of Artificial Neural Networks Corinna Cortes, Xavier Gonzalvo, Vitaly Kuznetsov, Mehryar Mohri, Scott Yang

NeurIPS 2017 Discriminative State Space Models Vitaly Kuznetsov, Mehryar Mohri

MLJ 2017 Generalization Bounds for Non-Stationary Mixing Processes Vitaly Kuznetsov, Mehryar Mohri

NeurIPS 2017 Online Learning with Transductive Regret Mehryar Mohri, Scott Yang

NeurIPS 2017 Parameter-Free Online Learning via Model Selection Dylan J Foster, Satyen Kale, Mehryar Mohri, Karthik Sridharan

AISTATS 2016 Accelerating Online Convex Optimization via Adaptive Prediction Mehryar Mohri, Scott Yang

UAI 2016 Adaptive Algorithms and Data-Dependent Guarantees for Bandit Convex Optimization Scott Yang, Mehryar Mohri

NeurIPS 2016 Boosting with Abstention Corinna Cortes, Giulia DeSalvo, Mehryar Mohri

JMLR 2016 Learning Algorithms for Second-Price Auctions with Reserve Mehryar Mohri, Andres Munoz Medina

ALT 2016 Learning with Rejection Corinna Cortes, Giulia DeSalvo, Mehryar Mohri

NeurIPS 2016 Optimistic Bandit Convex Optimization Scott Yang, Mehryar Mohri

AAAI 2016 Random Composite Forests Giulia DeSalvo, Mehryar Mohri

ALT 2016 Structural Online Learning Mehryar Mohri, Scott Yang

NeurIPS 2016 Structured Prediction Theory Based on Factor Graph Complexity Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, Scott Yang

COLT 2016 Time Series Prediction and Online Learning Vitaly Kuznetsov, Mehryar Mohri

NeurIPS 2015 Learning Theory and Algorithms for Forecasting Non-Stationary Time Series Vitaly Kuznetsov, Mehryar Mohri

ALT 2015 Learning with Deep Cascades Giulia DeSalvo, Mehryar Mohri, Umar Syed

UAI 2015 Non-Parametric Revenue Optimization for Generalized Second Price Auctions Mehryar Mohri, Andres Muñoz Medina

ALT 2015 On the Rademacher Complexity of Weighted Automata Borja Balle, Mehryar Mohri

COLT 2015 On-Line Learning Algorithms for Path Experts with Non-Additive Losses Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, Manfred K. Warmuth

NeurIPS 2015 Revenue Optimization Against Strategic Buyers Mehryar Mohri, Andres Munoz

ICML 2015 Structural Maxent Models Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri, Umar Syed

NeurIPS 2014 Conditional Swap Regret and Conditional Correlated Equilibrium Mehryar Mohri, Scott Yang

ICML 2014 Deep Boosting Corinna Cortes, Mehryar Mohri, Umar Syed

ICML 2014 Ensemble Methods for Structured Prediction Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri

ALT 2014 Generalization Bounds for Time Series Prediction with Non-Stationary Processes Vitaly Kuznetsov, Mehryar Mohri

ICML 2014 Learning Theory and Algorithms for Revenue Optimization in Second Price Auctions with Reserve Mehryar Mohri, Andres Munoz Medina

NeurIPS 2014 Multi-Class Deep Boosting Vitaly Kuznetsov, Mehryar Mohri, Umar Syed

NeurIPS 2014 Optimal Regret Minimization in Posted-Price Auctions with Strategic Buyers Mehryar Mohri, Andres Munoz

JMLR 2013 Large-Scale SVD and Manifold Learning Ameet Talwalkar, Sanjiv Kumar, Mehryar Mohri, Henry Rowley

NeurIPS 2013 Learning Kernels Using Local Rademacher Complexity Corinna Cortes, Marius Kloft, Mehryar Mohri

ICML 2013 Multi-Class Classification with Maximum Margin Multiple Kernel Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh

NeurIPS 2012 Accuracy at the Top Stephen Boyd, Corinna Cortes, Mehryar Mohri, Ana Radovanovic

JMLR 2012 Algorithms for Learning Kernels Based on Centered Alignment Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh

ALT 2012 New Analysis and Algorithm for Learning with Drifting Distributions Mehryar Mohri, Andres Muñoz Medina

JMLR 2012 Sampling Methods for the Nystr M Method Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar

NeurIPS 2012 Spectral Learning of General Weighted Automata via Constrained Matrix Completion Borja Balle, Mehryar Mohri

AISTATS 2011 Can Matrix Coherence Be Efficiently and Accurately Estimated? Mehryar Mohri, Ameet Talwalkar

ALT 2011 Domain Adaptation in Regression Corinna Cortes, Mehryar Mohri

UAI 2011 Ensembles of Kernel Predictors Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh

COLT 2010 COLT 2010 - The 23rd Conference on Learning Theory, Haifa, Israel, June 27-29, 2010 Adam Tauman Kalai, Mehryar Mohri

AISTATS 2010 Discriminative Topic Segmentation of Text and Speech Mehryar Mohri, Pedro Moreno, Eugene Weinstein

ICML 2010 Generalization Bounds for Learning Kernels Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh

AISTATS 2010 Half Transductive Ranking Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Corinna Cortes, Mehryar Mohri

NeurIPS 2010 Learning Bounds for Importance Weighting Corinna Cortes, Yishay Mansour, Mehryar Mohri

AISTATS 2010 On the Impact of Kernel Approximation on Learning Accuracy Corinna Cortes, Mehryar Mohri, Ameet Talwalkar

MLJ 2010 Preference-Based Learning to Rank Nir Ailon, Mehryar Mohri

JMLR 2010 Stability Bounds for Stationary -mixing and -mixing Processes Mehryar Mohri, Afshin Rostamizadeh

ICML 2010 Two-Stage Learning Kernel Algorithms Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh

COLT 2009 Domain Adaptation: Learning Bounds and Algorithms Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh

NeurIPS 2009 Efficient Large-Scale Distributed Training of Conditional Maximum Entropy Models Ryan Mcdonald, Mehryar Mohri, Nathan Silberman, Dan Walker, Gideon S. Mann

NeurIPS 2009 Ensemble Nystrom Method Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar

AISTATS 2009 Gaussian Margin Machines Koby Crammer, Mehryar Mohri, Fernando Pereira

UAI 2009 L2 Regularization for Learning Kernels Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh

NeurIPS 2009 Learning Non-Linear Combinations of Kernels Corinna Cortes, Mehryar Mohri, Afshin Rostamizadeh

UAI 2009 Multiple Source Adaptation and the Rényi Divergence Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh

ICML 2009 On Sampling-Based Approximate Spectral Decomposition Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar

NeurIPS 2009 Polynomial Semantic Indexing Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Corinna Cortes, Mehryar Mohri

AISTATS 2009 Sampling Techniques for the Nystrom Method Sanjiv Kumar, Mehryar Mohri, Ameet Talwalkar

COLT 2008 An Efficient Reduction of Ranking to Classification Nir Ailon, Mehryar Mohri

NeurIPS 2008 Domain Adaptation with Multiple Sources Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh

NeurIPS 2008 Rademacher Complexity Bounds for Non-I.I.D. Processes Mehryar Mohri, Afshin Rostamizadeh

ALT 2008 Sample Selection Bias Correction Theory Corinna Cortes, Mehryar Mohri, Michael Riley, Afshin Rostamizadeh

ICML 2008 Sequence Kernels for Predicting Protein Essentiality Cyril Allauzen, Mehryar Mohri, Ameet Talwalkar

ICML 2008 Stability of Transductive Regression Algorithms Corinna Cortes, Mehryar Mohri, Dmitry Pechyony, Ashish Rastogi

COLT 2007 Learning Languages with Rational Kernels Corinna Cortes, Leonid Kontorovich, Mehryar Mohri

ICML 2007 Magnitude-Preserving Ranking Algorithms Corinna Cortes, Mehryar Mohri, Ashish Rastogi

NeurIPS 2007 Stability Bounds for Non-I.i.d. Processes Mehryar Mohri, Afshin Rostamizadeh

ALT 2006 Learning Linearly Separable Languages Leonid Kontorovich, Corinna Cortes, Mehryar Mohri

NeurIPS 2006 On Transductive Regression Corinna Cortes, Mehryar Mohri

ICML 2005 A General Regression Technique for Learning Transductions Corinna Cortes, Mehryar Mohri, Jason Weston

COLT 2005 Margin-Based Ranking Meets Boosting in the Middle Cynthia Rudin, Corinna Cortes, Mehryar Mohri, Robert E. Schapire

MLJ 2005 Moment Kernels for Regular Distributions Corinna Cortes, Mehryar Mohri

ECML-PKDD 2005 Multi-Armed Bandit Algorithms and Empirical Evaluation Joannès Vermorel, Mehryar Mohri

NeurIPS 2004 Confidence Intervals for the Area Under the ROC Curve Corinna Cortes, Mehryar Mohri

ICML 2004 Distribution Kernels Based on Moments of Counts Corinna Cortes, Mehryar Mohri

JMLR 2004 Rational Kernels: Theory and Algorithms (Special Topic on Learning Theory) Corinna Cortes, Patrick Haffner, Mehryar Mohri

NeurIPS 2003 AUC Optimization vs. Error Rate Minimization Corinna Cortes, Mehryar Mohri

COLT 2003 Learning from Uncertain Data Mehryar Mohri

COLT 2003 Positive Definite Rational Kernels Corinna Cortes, Patrick Haffner, Mehryar Mohri

NeurIPS 2002 Rational Kernels Corinna Cortes, Patrick Haffner, Mehryar Mohri