Alexander Rakhlin

212 papers A* 61A 7B 2C 3Misc 1Journal 115Unranked 21

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Characterizing Online and Private Learnability under Distributional Constraints via Generalized Smoothness. CoRR Moïse Blanchard, Abhishek Shetty, Alexander Rakhlin
2026	J	`jnl`	End-to-End Efficient RL for Linear Bellman Complete MDPs with Deterministic Transitions. CoRR Zakaria Mhammedi, Alexander Rakhlin, Nneka Okolo
2026	J	`jnl`	High-accuracy log-concave sampling with stochastic queries. CoRR Fan Chen, Sinho Chewi, Constantinos Daskalakis, Alexander Rakhlin
2026	J	`jnl`	High-accuracy sampling for diffusion models and log-concave distributions. CoRR Fan Chen, Sinho Chewi, Constantinos Daskalakis, Alexander Rakhlin
2026	J	`jnl`	Refined Risk Bounds for Unbounded Losses via Transductive Priors. J. Mach. Learn. Res. Jian Qian, Alexander Rakhlin, Nikita Zhivotovskiy
2025	J	`jnl`	A Gapped Scale-Sensitive Dimension and Lower Bounds for Offset Rademacher Complexity. CoRR Zeyu Jia, Yury Polyanskiy, Alexander Rakhlin
2025	A*	`conf`	Decision Making in Changing Environments: Robustness, Query-Based Learning, and Differential Privacy. COLT Fan Chen, Alexander Rakhlin
2025	J	`jnl`	Decision Making in Changing Environments: Robustness, Query-Based Learning, and Differential Privacy. CoRR Fan Chen, Alexander Rakhlin
2025	A*	`conf`	Do We Need to Verify Step by Step? Rethinking Process Supervision from a Theoretical Perspective. ICML Zeyu Jia, Alexander Rakhlin, Tengyang Xie
2025	J	`jnl`	Do We Need to Verify Step by Step? Rethinking Process Supervision from a Theoretical Perspective. CoRR Zeyu Jia, Alexander Rakhlin, Tengyang Xie
2025	A*	`conf`	Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF. ICLR Tengyang Xie, Dylan J. Foster, Akshay Krishnamurthy, Corby Rosset, Ahmed Hassan Awadallah, Alexander Rakhlin
2025	A*	`conf`	GaussMark: A Practical Approach for Structural Watermarking of Language Models. ICML Adam Block, Alexander Rakhlin, Ayush Sekhari
2025	J	`jnl`	GaussMark: A Practical Approach for Structural Watermarking of Language Models. CoRR Adam Block, Ayush Sekhari, Alexander Rakhlin
2025	J	`jnl`	Near-Optimal Private Learning in Linear Contextual Bandits. CoRR Fan Chen, Jiachun Li, Alexander Rakhlin, David Simchi-Levi
2025	A*	`conf`	On the Minimax Regret of Sequential Probability Assignment via Square-Root Entropy. COLT Zeyu Jia, Alexander Rakhlin, Yury Polyanskiy
2025	J	`jnl`	On the Minimax Regret of Sequential Probability Assignment via Square-Root Entropy. CoRR Zeyu Jia, Yury Polyanskiy, Alexander Rakhlin
2025	J	`jnl`	Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits. CoRR Fan Chen, Zeyu Jia, Alexander Rakhlin, Tengyang Xie
2025	J	`jnl`	Trajectory Bellman Residual Minimization: A Simple Value-Based Method for LLM Reasoning. CoRR Yurun Yuan, Fan Chen, Zeyu Jia, Alexander Rakhlin, Tengyang Xie
2024	A*	`conf`	Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability. NeurIPS Fan Chen, Dylan J. Foster, Yanjun Han, Jian Qian, Alexander Rakhlin, Yunbei Xu
2024	J	`jnl`	Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability. CoRR Fan Chen, Dylan J. Foster, Yanjun Han, Jian Qian, Alexander Rakhlin, Yunbei Xu
2024	J	`jnl`	Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF. CoRR Tengyang Xie, Dylan J. Foster, Akshay Krishnamurthy, Corby Rosset, Ahmed Awadallah, Alexander Rakhlin
2024	A*	`conf`	How Does Variance Shape the Regret in Contextual Bandits? NeurIPS Zeyu Jia, Jian Qian, Alexander Rakhlin, Chen-Yu Wei
2024	J	`jnl`	How Does Variance Shape the Regret in Contextual Bandits? CoRR Zeyu Jia, Jian Qian, Alexander Rakhlin, Chen-Yu Wei
2024	—	`conf`	How Far Is Too Far? Studying the Effects of Domain Discrepancy on Masked Language Models. LREC/COLING Subhradeep Kayal, Alexander Rakhlin, Ali Dashti, Serguei Stepaniants
2024	A*	`conf`	Near-Optimal Learning and Planning in Separated Latent MDPs. COLT Fan Chen, Constantinos Daskalakis, Noah Golowich, Alexander Rakhlin
2024	J	`jnl`	Near-Optimal Learning and Planning in Separated Latent MDPs. CoRR Fan Chen, Constantinos Daskalakis, Noah Golowich, Alexander Rakhlin
2024	A*	`conf`	Offline Reinforcement Learning: Role of State Aggregation and Trajectory Data. COLT Zeyu Jia, Alexander Rakhlin, Ayush Sekhari, Chen-Yu Wei
2024	J	`jnl`	Offline Reinforcement Learning: Role of State Aggregation and Trajectory Data. CoRR Zeyu Jia, Alexander Rakhlin, Ayush Sekhari, Chen-Yu Wei
2024	A*	`conf`	On the Performance of Empirical Risk Minimization with Smoothed Data. COLT Adam Block, Alexander Rakhlin, Abhishek Shetty
2024	J	`jnl`	On the Performance of Empirical Risk Minimization with Smoothed Data. CoRR Adam Block, Alexander Rakhlin, Abhishek Shetty
2024	A*	`conf`	Online Estimation via Offline Estimation: An Information-Theoretic Framework. NeurIPS Dylan J. Foster, Yanjun Han, Jian Qian, Alexander Rakhlin
2024	J	`jnl`	Online Estimation via Offline Estimation: An Information-Theoretic Framework. CoRR Dylan J. Foster, Yanjun Han, Jian Qian, Alexander Rakhlin
2024	A*	`conf`	Random Latent Exploration for Deep Reinforcement Learning. ICML Srinath Mahankali, Zhang-Wei Hong, Ayush Sekhari, Alexander Rakhlin, Pulkit Agrawal
2024	J	`jnl`	Random Latent Exploration for Deep Reinforcement Learning. CoRR Srinath Mahankali, Zhang-Wei Hong, Ayush Sekhari, Alexander Rakhlin, Pulkit Agrawal
2024	J	`jnl`	Refined Risk Bounds for Unbounded Losses via Transductive Priors. CoRR Jian Qian, Alexander Rakhlin, Nikita Zhivotovskiy
2024	A*	`conf`	The Non-linear F-Design and Applications to Interactive Learning. ICML Alekh Agarwal, Jian Qian, Alexander Rakhlin, Tong Zhang
2024	A*	`conf`	The Power of Resets in Online Reinforcement Learning. NeurIPS Zakaria Mhammedi, Dylan J. Foster, Alexander Rakhlin
2024	J	`jnl`	The Power of Resets in Online Reinforcement Learning. CoRR Zakaria Mhammedi, Dylan J. Foster, Alexander Rakhlin
2023	A*	`conf`	Convergence of Adam Under Relaxed Assumptions. NeurIPS Haochuan Li, Alexander Rakhlin, Ali Jadbabaie
2023	J	`jnl`	Convergence of Adam Under Relaxed Assumptions. CoRR Haochuan Li, Ali Jadbabaie, Alexander Rakhlin
2023	J	`jnl`	Convex and Non-Convex Optimization under Generalized Smoothness. CoRR Haochuan Li, Jian Qian, Yi Tian, Alexander Rakhlin, Ali Jadbabaie
2023	A*	`conf`	Convex and Non-convex Optimization Under Generalized Smoothness. NeurIPS Haochuan Li, Jian Qian, Yi Tian, Alexander Rakhlin, Ali Jadbabaie
2023	A*	`conf`	Efficient Model-Free Exploration in Low-Rank MDPs. NeurIPS Zakaria Mhammedi, Adam Block, Dylan J. Foster, Alexander Rakhlin
2023	J	`jnl`	Efficient Model-Free Exploration in Low-Rank MDPs. CoRR Zakaria Mhammedi, Adam Block, Dylan J. Foster, Alexander Rakhlin
2023	J	`jnl`	Foundations of Reinforcement Learning and Interactive Decision Making. CoRR Dylan J. Foster, Alexander Rakhlin
2023	J	`jnl`	Lower Bounds for γ-Regret via the Decision-Estimation Coefficient. CoRR Margalit Glasgow, Alexander Rakhlin
2023	A*	`conf`	Model-Free Reinforcement Learning with the Decision-Estimation Coefficient. NeurIPS Dylan J. Foster, Noah Golowich, Jian Qian, Alexander Rakhlin, Ayush Sekhari
2023	A*	`conf`	On the Complexity of Multi-Agent Decision Making: From Learning in Games to Partial Monitoring. COLT Dean P. Foster, Dylan J. Foster, Noah Golowich, Alexander Rakhlin
2023	J	`jnl`	On the Complexity of Multi-Agent Decision Making: From Learning in Games to Partial Monitoring. CoRR Dylan J. Foster, Dean P. Foster, Noah Golowich, Alexander Rakhlin
2023	A*	`conf`	On the Variance, Admissibility, and Stability of Empirical Risk Minimization. NeurIPS Gil Kur, Eli Putterman, Alexander Rakhlin
2023	J	`jnl`	On the Variance, Admissibility, and Stability of Empirical Risk Minimization. CoRR Gil Kur, Eli Putterman, Alexander Rakhlin
2023	A*	`conf`	Oracle-Efficient Smoothed Online Learning for Piecewise Continuous Decision Making. COLT Adam Block, Max Simchowitz, Alexander Rakhlin
2023	J	`jnl`	Oracle-Efficient Smoothed Online Learning for Piecewise Continuous Decision Making. CoRR Adam Block, Alexander Rakhlin, Max Simchowitz
2023	A*	`conf`	Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL. ICML Zakaria Mhammedi, Dylan J. Foster, Alexander Rakhlin
2023	J	`jnl`	Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL. CoRR Zakaria Mhammedi, Dylan J. Foster, Alexander Rakhlin
2023	A*	`conf`	When is Agnostic Reinforcement Learning Statistically Tractable? NeurIPS Zeyu Jia, Gene Li, Alexander Rakhlin, Ayush Sekhari, Nati Srebro
2023	J	`jnl`	When is Agnostic Reinforcement Learning Statistically Tractable? CoRR Zeyu Jia, Gene Li, Alexander Rakhlin, Ayush Sekhari, Nathan Srebro
2022	J	`jnl`	A Note on Model-Free Reinforcement Learning with the Decision-Estimation Coefficient. CoRR Dylan J. Foster, Noah Golowich, Jian Qian, Alexander Rakhlin, Ayush Sekhari
2022	A*	`conf`	Damped Online Newton Step for Portfolio Selection. COLT Zakaria Mhammedi, Alexander Rakhlin
2022	J	`jnl`	Damped Online Newton Step for Portfolio Selection. CoRR Zakaria Mhammedi, Alexander Rakhlin
2022	J	`jnl`	Intrinsic Dimension Estimation Using Wasserstein Distance. J. Mach. Learn. Res. Adam Block, Zeyu Jia, Yury Polyanskiy, Alexander Rakhlin
2022	A*	`conf`	On the Complexity of Adversarial Decision Making. NeurIPS Dylan J. Foster, Alexander Rakhlin, Ayush Sekhari, Karthik Sridharan
2022	J	`jnl`	On the Complexity of Adversarial Decision Making. CoRR Dylan J. Foster, Alexander Rakhlin, Ayush Sekhari, Karthik Sridharan
2022	J	`jnl`	Rate of convergence of the smoothed empirical Wasserstein distance. CoRR Adam Block, Zeyu Jia, Yury Polyanskiy, Alexander Rakhlin
2022	A*	`conf`	Smoothed Online Learning is as Easy as Statistical Learning. COLT Adam Block, Yuval Dagan, Noah Golowich, Alexander Rakhlin
2022	J	`jnl`	Smoothed Online Learning is as Easy as Statistical Learning. CoRR Adam Block, Yuval Dagan, Noah Golowich, Alexander Rakhlin
2021	J	`jnl`	Deep learning: a statistical viewpoint. Acta Numer. Peter L. Bartlett, Andrea Montanari, Alexander Rakhlin
2021	J	`jnl`	Deep learning: a statistical viewpoint. CoRR Peter L. Bartlett, Andrea Montanari, Alexander Rakhlin
2021	J	`jnl`	Finite Time LTI System Identification. J. Mach. Learn. Res. Tuhin Sarkar, Alexander Rakhlin, Munther A. Dahleh
2021	A*	`conf`	Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective. COLT Dylan J. Foster, Alexander Rakhlin, David Simchi-Levi, Yunzong Xu
2021	J	`jnl`	Intrinsic Dimension Estimation. CoRR Adam Block, Zeyu Jia, Yury Polyanskiy, Alexander Rakhlin
2021	A*	`conf`	Majorizing Measures, Sequential Complexities, and Online Learning. COLT Adam Block, Yuval Dagan, Alexander Rakhlin
2021	J	`jnl`	On Submodular Contextual Bandits. CoRR Dean P. Foster, Alexander Rakhlin
2021	A*	`conf`	On the Minimal Error of Empirical Risk Minimization. COLT Gil Kur, Alexander Rakhlin
2021	J	`jnl`	On the Minimal Error of Empirical Risk Minimization. CoRR Gil Kur, Alexander Rakhlin
2021	—	`ch.`	ResNet. Computer-Aided Analysis of Gastrointestinal Videos Isabel Amaya-Rodriguez, Javier Civit-Masot, Francisco Luna-Perejon, Lourdes Duran-Lopez, Alexander Rakhlin, Sergey I. Nikolenko, Satoshi Kondo, Pablo Laiz, Jordi Vitrià, Santi Seguí, Patrick Brandao
2021	J	`jnl`	The Statistical Complexity of Interactive Decision Making. CoRR Dylan J. Foster, Sham M. Kakade, Jian Qian, Alexander Rakhlin
2021	A*	`conf`	Top-k eXtreme Contextual Bandits with Arm Hierarchy. ICML Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean P. Foster, Daniel N. Hill, Inderjit S. Dhillon
2021	J	`jnl`	Top-k eXtreme Contextual Bandits with Arm Hierarchy. CoRR Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean P. Foster, Daniel N. Hill, Inderjit S. Dhillon
2020	A*	`conf`	Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles. ICML Dylan J. Foster, Alexander Rakhlin
2020	J	`jnl`	Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles. CoRR Dylan J. Foster, Alexander Rakhlin
2020	J	`jnl`	ColocML: machine learning quantifies co-localization between mass spectrometry images. Bioinform. Katja Ovchinnikova, Lachlan Stuart, Alexander Rakhlin, Sergey I. Nikolenko, Theodore Alexandrov
2020	J	`jnl`	Fast Mixing of Multi-Scale Langevin Dynamics under the Manifold Hypothesis. CoRR Adam Block, Youssef Mroueh, Alexander Rakhlin, Jerret Ross
2020	J	`jnl`	Generative Modeling with Denoising Auto-Encoders and Langevin Sampling. CoRR Adam Block, Youssef Mroueh, Alexander Rakhlin
2020	J	`jnl`	Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective. CoRR Dylan J. Foster, Alexander Rakhlin, David Simchi-Levi, Yunzong Xu
2020	—	`conf`	Learning nonlinear dynamical systems from a single trajectory. L4DC Dylan J. Foster, Tuhin Sarkar, Alexander Rakhlin
2020	J	`jnl`	Learning nonlinear dynamical systems from a single trajectory. CoRR Dylan J. Foster, Alexander Rakhlin, Tuhin Sarkar
2020	A*	`conf`	Learning the Linear Quadratic Regulator from Nonlinear Observations. NeurIPS Zakaria Mhammedi, Dylan J. Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford
2020	J	`jnl`	Learning the Linear Quadratic Regulator from Nonlinear Observations. CoRR Zakaria Mhammedi, Dylan J. Foster, Max Simchowitz, Dipendra Misra, Wen Sun, Akshay Krishnamurthy, Alexander Rakhlin, John Langford
2020	A*	`conf`	On Suboptimality of Least Squares with Application to Estimation of Convex Bodies. COLT Gil Kur, Alexander Rakhlin, Adityanand Guntuboyina
2020	J	`jnl`	On Suboptimality of Least Squares with Application to Estimation of Convex Bodies. CoRR Gil Kur, Alexander Rakhlin, Adityanand Guntuboyina
2020	A*	`conf`	On the Multiple Descent of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels. COLT Tengyuan Liang, Alexander Rakhlin, Xiyu Zhai
2020	J	`jnl`	Weighted Message Passing and Minimum Energy Flow for Heterogeneous Stochastic Block Models with Side Information. J. Mach. Learn. Res. T. Tony Cai, Tengyuan Liang, Alexander Rakhlin
2019	—	`conf`	Breast Tumor Cellularity Assessment Using Deep Neural Networks. ICCV Workshops Alexander Rakhlin, Aleksei Tiulpin, Alexey A. Shvets, Alexandr A. Kalinin, Vladimir I. Iglovikov, Sergey I. Nikolenko
2019	J	`jnl`	Breast Tumor Cellularity Assessment using Deep Neural Networks. CoRR Alexander Rakhlin, Alexey A. Shvets, Alexandr A. Kalinin, Aleksei Tiulpin, Vladimir I. Iglovikov, Sergey I. Nikolenko
2019	A*	`conf`	Consistency of Interpolation with Laplace Kernels is a High-Dimensional Phenomenon. COLT Alexander Rakhlin, Xiyu Zhai
2019	A	`conf`	Does data interpolation contradict statistical optimality? AISTATS Mikhail Belkin, Alexander Rakhlin, Alexandre B. Tsybakov
2019	J	`jnl`	Finite-Time System Identification for Partially Observed LTI Systems of Unknown Order. CoRR Tuhin Sarkar, Alexander Rakhlin, Munther A. Dahleh
2019	A	`conf`	Fisher-Rao Metric, Geometry, and Complexity of Neural Networks. AISTATS Tengyuan Liang, Tomaso A. Poggio, Alexander Rakhlin, James Stokes
2019	A*	`conf`	Near optimal finite time identification of arbitrary linear dynamical systems. ICML Tuhin Sarkar, Alexander Rakhlin
2019	—	`conf`	Nonparametric System identification of Stochastic Switched Linear Systems. CDC Tuhin Sarkar, Alexander Rakhlin, Munther A. Dahleh
2019	J	`jnl`	Nonparametric System identification of Stochastic Switched Linear Systems. CoRR Tuhin Sarkar, Alexander Rakhlin, Munther A. Dahleh
2019	J	`jnl`	On the Risk of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels. CoRR Tengyuan Liang, Alexander Rakhlin, Xiyu Zhai
2019	J	`jnl`	𝓁 CoRR Dylan J. Foster, Alexander Rakhlin
2018	C	`conf`	Angiodysplasia Detection and Localization Using Deep Convolutional Neural Networks. ICMLA Alexey A. Shvets, Vladimir I. Iglovikov, Alexander Rakhlin, Alexandr A. Kalinin
2018	J	`jnl`	Angiodysplasia Detection and Localization Using Deep Convolutional Neural Networks. CoRR Alexey Shvets, Vladimir Iglovikov, Alexander Rakhlin, Alexandr A. Kalinin
2018	J	`jnl`	Automatic Instrument Segmentation in Robot-Assisted Surgery Using Deep Learning. CoRR Alexey Shvets, Alexander Rakhlin, Alexandr A. Kalinin, Vladimir Iglovikov
2018	C	`conf`	Automatic Instrument Segmentation in Robot-Assisted Surgery using Deep Learning. ICMLA Alexey A. Shvets, Alexander Rakhlin, Alexandr A. Kalinin, Vladimir I. Iglovikov
2018	J	`jnl`	Consistency of Interpolation with Laplace Kernels is a High-Dimensional Phenomenon. CoRR Alexander Rakhlin, Xiyu Zhai
2018	—	`conf`	Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis. ICIAR Alexander Rakhlin, Alexey Shvets, Vladimir Iglovikov, Alexandr A. Kalinin
2018	J	`jnl`	Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis. CoRR Alexander Rakhlin, Alexey Shvets, Vladimir Iglovikov, Alexandr A. Kalinin
2018	J	`jnl`	Does data interpolation contradict statistical optimality? CoRR Mikhail Belkin, Alexander Rakhlin, Alexandre B. Tsybakov
2018	J	`jnl`	How fast can linear dynamical systems be learned? CoRR Tuhin Sarkar, Alexander Rakhlin
2018	J	`jnl`	Just Interpolate: Kernel "Ridgeless" Regression Can Generalize. CoRR Tengyuan Liang, Alexander Rakhlin
2018	—	`conf`	Land Cover Classification From Satellite Imagery With U-Net and Lovasz-Softmax Loss. CVPR Workshops Alexander Rakhlin, Alex Davydow, Sergey I. Nikolenko
2018	A*	`conf`	Online Learning: Sufficient Statistics and the Burkholder Method. COLT Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan
2018	J	`jnl`	Online Learning: Sufficient Statistics and the Burkholder Method. CoRR Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan
2018	—	`conf`	Paediatric Bone Age Assessment Using Deep Convolutional Neural Networks. DLMIA/ML-CDS@MICCAI Vladimir I. Iglovikov, Alexander Rakhlin, Alexandr A. Kalinin, Alexey A. Shvets
2018	A*	`conf`	Size-Independent Sample Complexity of Neural Networks. COLT Noah Golowich, Alexander Rakhlin, Ohad Shamir
2018	J	`jnl`	Theory of Deep Learning IIb: Optimization Properties of SGD. CoRR Chiyuan Zhang, Qianli Liao, Alexander Rakhlin, Brando Miranda, Noah Golowich, Tomaso A. Poggio
2017	A	`conf`	Efficient Online Multiclass Prediction on Graphs via Surrogate Losses. AISTATS Alexander Rakhlin, Karthik Sridharan
2017	J	`jnl`	Efficient Sampling from Time-Varying Log-Concave Distributions. J. Mach. Learn. Res. Hariharan Narayanan, Alexander Rakhlin
2017	J	`jnl`	Fisher-Rao Metric, Geometry, and Complexity of Neural Networks. CoRR Tengyuan Liang, Tomaso A. Poggio, Alexander Rakhlin, James Stokes
2017	Misc	`conf`	Multi-armed bandits in multi-agent networks. ICASSP Shahin Shahrampour, Alexander Rakhlin, Ali Jadbabaie
2017	A*	`conf`	Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis. COLT Maxim Raginsky, Alexander Rakhlin, Matus Telgarsky
2017	J	`jnl`	Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis. CoRR Maxim Raginsky, Alexander Rakhlin, Matus Telgarsky
2017	J	`jnl`	On Detection and Structural Reconstruction of Small-World Random Networks. IEEE Trans. Netw. Sci. Eng. T. Tony Cai, Tengyuan Liang, Alexander Rakhlin
2017	A*	`conf`	On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities. COLT Alexander Rakhlin, Karthik Sridharan
2017	J	`jnl`	Pediatric Bone Age Assessment Using Deep Convolutional Neural Networks. CoRR Vladimir Iglovikov, Alexander Rakhlin, Alexandr A. Kalinin, Alexey Shvets
2017	—	`ed.`	Proceedings of the NIPS 2016 Time Series Workshop, co-located with the 30th Annual Conference on Neural Information Processing Systems (NIPS 2016), Barcelona, Spain, December 9, 2016 NIPS Time Series Workshop Oren Anava, Azadeh Khaleghi, Marco Cuturi, Vitaly Kuznetsov, Alexander Rakhlin
2017	J	`jnl`	Size-Independent Sample Complexity of Neural Networks. CoRR Noah Golowich, Alexander Rakhlin, Ohad Shamir
2017	A*	`conf`	ZigZag: A New Approach to Adaptive Online Learning. COLT Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan
2017	J	`jnl`	ZigZag: A new approach to adaptive online learning. CoRR Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan
2016	J	`jnl`	A Tutorial on Online Supervised Learning with Applications to Node Classification in Social Networks. CoRR Alexander Rakhlin, Karthik Sridharan
2016	A*	`conf`	BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits. ICML Alexander Rakhlin, Karthik Sridharan
2016	J	`jnl`	BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits. CoRR Alexander Rakhlin, Karthik Sridharan
2016	A*	`conf`	Conference on Learning Theory 2016: Preface. COLT Vitaly Feldman, Alexander Rakhlin
2016	J	`jnl`	Distributed Detection: Finite-Time Analysis and Impact of Network Topology. IEEE Trans. Autom. Control. Shahin Shahrampour, Alexander Rakhlin, Ali Jadbabaie
2016	J	`jnl`	Distributed Estimation of Dynamic Parameters : Regret Analysis. CoRR Shahin Shahrampour, Alexander Rakhlin, Ali Jadbabaie
2016	C	`conf`	Distributed estimation of dynamic parameters: Regret analysis. ACC Shahin Shahrampour, Alexander Rakhlin, Ali Jadbabaie
2016	B	`conf`	Information-theoretic analysis of stability and bias of learning algorithms. ITW Maxim Raginsky, Alexander Rakhlin, Matthew Tsao, Yihong Wu, Aolin Xu
2016	J	`jnl`	On Detection and Structural Reconstruction of Small-World Random Networks. CoRR T. Tony Cai, Tengyuan Liang, Alexander Rakhlin
2016	A*	`ed.`	Proceedings of the 29th Conference on Learning Theory, COLT 2016, New York, USA, June 23-26, 2016 COLT Vitaly Feldman, Alexander Rakhlin, Ohad Shamir
2015	—	`conf`	Adaptive Online Learning. NIPS Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan
2015	J	`jnl`	Adaptive Online Learning. CoRR Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan
2015	A*	`conf`	Escaping the Local Minima via Simulated Annealing: Optimization of Approximately Convex Functions. COLT Alexandre Belloni, Tengyuan Liang, Hariharan Narayanan, Alexander Rakhlin
2015	J	`jnl`	Escaping the Local Minima via Simulated Annealing: Optimization of Approximately Convex Functions. CoRR Alexandre Belloni, Tengyuan Liang, Hariharan Narayanan, Alexander Rakhlin
2015	J	`jnl`	Finite-time Analysis of the Distributed Detection Problem. CoRR Shahin Shahrampour, Alexander Rakhlin, Ali Jadbabaie
2015	—	`conf`	Finite-time analysis of the distributed detection problem. Allerton Shahin Shahrampour, Alexander Rakhlin, Ali Jadbabaie
2015	A*	`conf`	Hierarchies of Relaxations for Online Prediction Problems with Evolving Constraints. COLT Alexander Rakhlin, Karthik Sridharan
2015	J	`jnl`	Hierarchies of Relaxations for Online Prediction Problems with Evolving Constraints. CoRR Alexander Rakhlin, Karthik Sridharan
2015	A*	`conf`	Learning with Square Loss: Localization through Offset Rademacher Complexity. COLT Tengyuan Liang, Alexander Rakhlin, Karthik Sridharan
2015	J	`jnl`	Learning with Square Loss: Localization through Offset Rademacher Complexity. CoRR Tengyuan Liang, Alexander Rakhlin, Karthik Sridharan
2015	J	`jnl`	On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities. CoRR Alexander Rakhlin, Karthik Sridharan
2015	J	`jnl`	Online Nonparametric Regression with General Loss Functions. CoRR Alexander Rakhlin, Karthik Sridharan
2015	A	`conf`	Online Optimization : Competing with Dynamic Comparators. AISTATS Ali Jadbabaie, Alexander Rakhlin, Shahin Shahrampour, Karthik Sridharan
2015	J	`jnl`	Online Optimization : Competing with Dynamic Comparators. CoRR Ali Jadbabaie, Alexander Rakhlin, Shahin Shahrampour, Karthik Sridharan
2015	J	`jnl`	Online learning via sequential complexities. J. Mach. Learn. Res. Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
2015	J	`jnl`	Sequential Probability Assignment with Binary Alphabets and Large Classes of Experts. CoRR Alexander Rakhlin, Karthik Sridharan
2014	J	`jnl`	Distributed Detection : Finite-time Analysis and Impact of Network Topology. CoRR Shahin Shahrampour, Alexander Rakhlin, Ali Jadbabaie
2014	J	`jnl`	On Zeroth-Order Stochastic Convex Optimization via Random Walks. CoRR Tengyuan Liang, Hariharan Narayanan, Alexander Rakhlin
2014	A*	`conf`	Online Non-Parametric Regression. COLT Alexander Rakhlin, Karthik Sridharan
2014	J	`jnl`	Online Nonparametric Regression. CoRR Alexander Rakhlin, Karthik Sridharan
2014	J	`jnl`	Partial Monitoring - Classification, Regret Bounds, and Algorithms. Math. Oper. Res. Gábor Bartók, Dean P. Foster, Dávid Pál, Alexander Rakhlin, Csaba Szepesvári
2013	J	`jnl`	Competing With Strategies CoRR Wei Han, Alexander Rakhlin, Karthik Sridharan
2013	A*	`conf`	Competing With Strategies. COLT Wei Han, Alexander Rakhlin, Karthik Sridharan
2013	J	`jnl`	Empirical Entropy, Minimax Regret and Minimax Risk. CoRR Alexander Rakhlin, Karthik Sridharan, Alexandre B. Tsybakov
2013	A	`conf`	Localization and Adaptation in Online Learning. AISTATS Alexander Rakhlin, Ohad Shamir, Karthik Sridharan
2013	B	`conf`	On Semi-Probabilistic universal prediction. ITW Alexander Rakhlin, Karthik Sridharan
2013	—	`conf`	Online Learning of Dynamic Parameters in Social Networks. NIPS Shahin Shahrampour, Alexander Rakhlin, Ali Jadbabaie
2013	J	`jnl`	Online Learning of Dynamic Parameters in Social Networks. CoRR Shahin Shahrampour, Alexander Rakhlin, Ali Jadbabaie
2013	A*	`conf`	Online Learning with Predictable Sequences. COLT Alexander Rakhlin, Karthik Sridharan
2013	—	`conf`	Optimization, Learning, and Games with Predictable Sequences. NIPS Alexander Rakhlin, Karthik Sridharan
2013	J	`jnl`	Optimization, Learning, and Games with Predictable Sequences. CoRR Alexander Rakhlin, Karthik Sridharan
2013	J	`jnl`	Stochastic Convex Optimization with Bandit Feedback. SIAM J. Optim. Alekh Agarwal, Dean P. Foster, Daniel J. Hsu, Sham M. Kakade, Alexander Rakhlin
2012	J	`jnl`	Foreword. J. Comput. Syst. Sci. Alexander Rakhlin
2012	J	`jnl`	Interior-Point Methods for Full-Information and Bandit Online Learning. IEEE Trans. Inf. Theory Jacob D. Abernethy, Elad Hazan, Alexander Rakhlin
2012	A*	`conf`	Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization. ICML Alexander Rakhlin, Ohad Shamir, Karthik Sridharan
2012	A	`conf`	No Internal Regret via Neighborhood Watch. AISTATS Dean P. Foster, Alexander Rakhlin
2012	J	`jnl`	Online Learning with Predictable Sequences CoRR Alexander Rakhlin, Karthik Sridharan
2012	J	`jnl`	Quantitative Analysis of Systems Using Game-Theoretic Learning. ACM Trans. Embed. Comput. Syst. Sanjit A. Seshia, Alexander Rakhlin
2012	J	`jnl`	Relax and Localize: From Value to Algorithms CoRR Alexander Rakhlin, Ohad Shamir, Karthik Sridharan
2012	—	`conf`	Relax and Randomize : From Value to Algorithms. NIPS Alexander Rakhlin, Ohad Shamir, Karthik Sridharan
2011	A*	`conf`	Complexity-Based Approach to Calibration with Checking Rules. COLT Dean P. Foster, Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
2011	J	`jnl`	Information-Based Complexity, Feedback and Dynamics in Convex Programming. IEEE Trans. Inf. Theory Maxim Raginsky, Alexander Rakhlin
2011	—	`conf`	Lower Bounds for Passive and Active Learning. NIPS Maxim Raginsky, Alexander Rakhlin
2011	J	`jnl`	No Internal Regret via Neighborhood Watch CoRR Dean P. Foster, Alexander Rakhlin
2011	A*	`conf`	Online Learning: Beyond Regret. COLT Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
2011	J	`jnl`	Online Learning: Stochastic and Constrained Adversaries CoRR Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
2011	—	`conf`	Online Learning: Stochastic, Constrained, and Smoothed Adversaries. NIPS Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
2011	J	`jnl`	Stochastic convex optimization with bandit feedback CoRR Alekh Agarwal, Dean P. Foster, Daniel J. Hsu, Sham M. Kakade, Alexander Rakhlin
2011	—	`conf`	Stochastic convex optimization with bandit feedback. NIPS Alekh Agarwal, Dean P. Foster, Daniel J. Hsu, Sham M. Kakade, Alexander Rakhlin
2010	J	`jnl`	Information-based complexity, feedback and dynamics in sequential convex programming CoRR Maxim Raginsky, Alexander Rakhlin
2010	—	`conf`	Online Convex Programming and regularization in adaptive control. CDC Maxim Raginsky, Alexander Rakhlin, Serdar Yüksel
2010	J	`jnl`	Online Learning: Beyond Regret CoRR Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
2010	J	`jnl`	Online Learning: Random Averages, Combinatorial Parameters, and Learnability CoRR Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
2010	—	`conf`	Online Learning: Random Averages, Combinatorial Parameters, and Learnability. NIPS Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
2010	—	`conf`	Random Walk Approach to Regret Minimization. NIPS Hariharan Narayanan, Alexander Rakhlin
2009	J	`jnl`	A Stochastic View of Optimal Regret through Minimax Duality CoRR Jacob D. Abernethy, Alekh Agarwal, Peter L. Bartlett, Alexander Rakhlin
2009	A*	`conf`	A Stochastic View of Optimal Regret through Minimax Duality. COLT Jacob D. Abernethy, Alekh Agarwal, Peter L. Bartlett, Alexander Rakhlin
2009	A*	`conf`	An Efficient Bandit Algorithm for sqrt(T) Regret in Online Multiclass Prediction?. COLT Jacob D. Abernethy, Alexander Rakhlin
2009	A*	`conf`	Beating the Adaptive Bandit with High Probability. COLT Jacob D. Abernethy, Alexander Rakhlin
2009	—	`conf`	Information complexity of black-box convex optimization: A new look via feedback information theory. Allerton Maxim Raginsky, Alexander Rakhlin
2008	A*	`conf`	Competing in the Dark: An Efficient Algorithm for Bandit Linear Optimization. COLT Jacob D. Abernethy, Elad Hazan, Alexander Rakhlin
2008	A	`conf`	Game-theoretic timing analysis. ICCAD Sanjit A. Seshia, Alexander Rakhlin
2008	A*	`conf`	High-Probability Regret Bounds for Bandit Online Linear Optimization. COLT Peter L. Bartlett, Varsha Dani, Thomas P. Hayes, Sham M. Kakade, Alexander Rakhlin, Ambuj Tewari
2008	A*	`conf`	Optimal Stragies and Minimax Lower Bounds for Online Convex Games. COLT Jacob D. Abernethy, Peter L. Bartlett, Alexander Rakhlin, Ambuj Tewari
2007	—	`conf`	Adaptive Online Gradient Descent. NIPS Peter L. Bartlett, Elad Hazan, Alexander Rakhlin
2007	A*	`conf`	Multitask Learning with Expert Advice. COLT Jacob D. Abernethy, Peter L. Bartlett, Alexander Rakhlin
2007	A*	`conf`	Online discovery of similarity mappings. ICML Alexander Rakhlin, Jacob D. Abernethy, Peter L. Bartlett
2006	J	`jnl`	Stability Properties of Empirical Risk Minimization over Donsker Classes. J. Mach. Learn. Res. Andrea Caponnetto, Alexander Rakhlin
2006	—	`conf`	Stability of $K$-Means Clustering. NIPS Alexander Rakhlin, Andrea Caponnetto