Kanade, Varun

40 publications

NeurIPS 2025 Pause Tokens Strictly Increase the Expressivity of Constant-Depth Transformers Charles London, Varun Kanade

NeurIPS 2025 Selective Omniprediction and Fair Abstention Sílvia Casacuberta, Varun Kanade

JMLR 2024 Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition Varun Kanade, Patrick Rebeschini, Tomas Vaskevicius

NeurIPS 2024 Separations in the Representational Capabilities of Transformers and Recurrent Architectures Satwik Bhattamishra, Michael Hahn, Phil Blunsom, Varun Kanade

ICLR 2024 Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions Satwik Bhattamishra, Arkil Patel, Phil Blunsom, Varun Kanade

NeurIPS 2023 Partial Matrix Completion Elad Hazan, Adam Tauman Kalai, Varun Kanade, Clara Mohri, Y. Jennifer Sun

NeurIPSW 2023 Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions Satwik Bhattamishra, Arkil Patel, Phil Blunsom, Varun Kanade

IJCAI 2022 Sample Complexity Bounds for Robustly Learning Decision Lists Against Evasion Attacks Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell

NeurIPS 2022 When Are Local Queries Useful for Robust Learning? Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell

AISTATS 2021 Online K-Means Clustering Vincent Cohen-Addad, Benjamin Guedj, Varun Kanade, Guy Rom

ALT 2021 Efficient Learning with Arbitrary Covariate Shift Adam Tauman Kalai, Varun Kanade

ICLR 2021 How Benign Is Benign Overfitting ? Amartya Sanyal, Puneet K. Dokania, Varun Kanade, Philip Torr

JMLR 2021 On the Hardness of Robust Classification Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell

NeurIPS 2021 Towards Optimally Abstaining from Prediction with OOD Test Examples Adam Kalai, Varun Kanade

NeurIPS 2020 Adaptive Reduced Rank Regression Qiong Wu, Felix MF Wong, Yanhua Li, Zhenming Liu, Varun Kanade

AISTATS 2020 Differentiable Causal Backdoor Discovery Limor Gultchin, Matt Kusner, Varun Kanade, Ricardo Silva

NeurIPS 2020 The Statistical Complexity of Early-Stopped Mirror Descent Tomas Vaskevicius, Varun Kanade, Patrick Rebeschini

NeurIPS 2019 Decentralized Cooperative Stochastic Bandits David Martínez-Rubio, Varun Kanade, Patrick Rebeschini

NeurIPS 2019 Implicit Regularization for Optimal Sparse Recovery Tomas Vaskevicius, Varun Kanade, Patrick Rebeschini

NeurIPS 2019 On the Hardness of Robust Classification Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell

AISTATS 2019 Statistical Windows in Testing for the Initial Distribution of a Reversible Markov Chain Quentin Berthet, Varun Kanade

NeurIPS 2018 Clustering Redemption–Beyond the Impossibility of Kleinberg’s Axioms Vincent Cohen-Addad, Varun Kanade, Frederik Mallmann-Trenn

ICML 2018 TAPAS: Tricks to Accelerate (encrypted) Prediction as a Service Amartya Sanyal, Matt Kusner, Adria Gascon, Varun Kanade

NeurIPS 2017 From Which World Is Your Graph Cheng Li, Felix MF Wong, Zhenming Liu, Varun Kanade

NeurIPS 2017 Hierarchical Clustering Beyond the Worst-Case Vincent Cohen-Addad, Varun Kanade, Frederik Mallmann-Trenn

AISTATS 2017 Online Optimization of Smoothed Piecewise Constant Functions Vincent Cohen-Addad, Varun Kanade

COLT 2017 Reliably Learning the ReLU in Polynomial Time Surbhi Goel, Varun Kanade, Adam Klivans, Justin Thaler

ALT 2015 Learning with a Drifting Target Concept Steve Hanneke, Varun Kanade, Liu Yang

COLT 2015 MCMC Learning Varun Kanade, Elchanan Mossel

COLT 2014 Distribution-Independent Reliable Learning Varun Kanade, Justin Thaler

ICML 2014 Tracking Adversarial Targets Yasin Abbasi-Yadkori, Peter Bartlett, Varun Kanade

COLT 2013 Learning Using Local Membership Queries Pranjal Awasthi, Vitaly Feldman, Varun Kanade

NeurIPS 2013 Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions Yasin Abbasi Yadkori, Peter L Bartlett, Varun Kanade, Yevgeny Seldin, Csaba Szepesvari

COLT 2012 Computational Bounds on Statistical Query Learning Vitaly Feldman, Varun Kanade

NeurIPS 2012 Distributed Non-Stochastic Experts Varun Kanade, Zhenming Liu, Bozidar Radunovic

NeurIPS 2011 Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression Sham M. Kakade, Varun Kanade, Ohad Shamir, Adam Kalai

COLT 2010 Evolution with Drifting Targets Varun Kanade, Leslie G. Valiant, Jennifer Wortman Vaughan

NeurIPS 2009 Potential-Based Agnostic Boosting Varun Kanade, Adam Kalai

COLT 2009 Reliable Agnostic Learning Adam Tauman Kalai, Varun Kanade, Yishay Mansour

AISTATS 2009 Sleeping Experts and Bandits with Stochastic Action Availability and Adversarial Rewards Varun Kanade, H. Brendan McMahan, Brent Bryan