Varun Kanade - RankMe

104 papers A* 28A 9B 2Misc 1Journal 55Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Provably Learning Attention with Queries. CoRR Satwik Bhattamishra, Kulin Shah, Michael Hahn, Varun Kanade
2025	J	`jnl`	DEEDEE: Fast and Scalable Out-of-Distribution Dynamics Detection. CoRR Tala Aljaafari, Varun Kanade, Philip Torr, Christian Schröder de Witt
2025	J	`jnl`	Hardness of Learning Regular Languages in the Next Symbol Prediction Setting. CoRR Satwik Bhattamishra, Phil Blunsom, Varun Kanade
2025	A*	`conf`	How Global Calibration Strengthens Multiaccuracy. FOCS Sílvia Casacuberta, Parikshit Gopalan, Varun Kanade, Omer Reingold
2025	J	`jnl`	How Global Calibration Strengthens Multiaccuracy. CoRR Sílvia Casacuberta, Parikshit Gopalan, Varun Kanade, Omer Reingold
2025	J	`jnl`	Pause Tokens Strictly Increase the Expressivity of Constant-Depth Transformers. CoRR Charles London, Varun Kanade
2024	J	`jnl`	Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition. J. Mach. Learn. Res. Varun Kanade, Patrick Rebeschini, Tomas Vaskevicius
2024	A*	`conf`	Separations in the Representational Capabilities of Transformers and Recurrent Architectures. NeurIPS Satwik Bhattamishra, Michael Hahn, Phil Blunsom, Varun Kanade
2024	J	`jnl`	Separations in the Representational Capabilities of Transformers and Recurrent Architectures. CoRR Satwik Bhattamishra, Michael Hahn, Phil Blunsom, Varun Kanade
2024	A*	`conf`	Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions. ICLR Satwik Bhattamishra, Arkil Patel, Phil Blunsom, Varun Kanade
2023	J	`jnl`	On Coalescence Time in Graphs: When Is Coalescing as Fast as Meeting? ACM Trans. Algorithms Varun Kanade, Frederik Mallmann-Trenn, Thomas Sauerwald
2023	A*	`conf`	Partial Matrix Completion. NeurIPS Elad Hazan, Adam Tauman Kalai, Varun Kanade, Clara Mohri, Y. Jennifer Sun
2023	—	`conf`	Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions. ACL (1) Satwik Bhattamishra, Arkil Patel, Varun Kanade, Phil Blunsom
2023	J	`jnl`	Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions. CoRR Satwik Bhattamishra, Arkil Patel, Phil Blunsom, Varun Kanade
2022	J	`jnl`	Beyond Impossibility: Balancing Sufficiency, Separation and Accuracy. CoRR Limor Gultchin, Vincent Cohen-Addad, Sophie Giffard-Roisin, Varun Kanade, Frederik Mallmann-Trenn
2022	J	`jnl`	Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition. CoRR Varun Kanade, Patrick Rebeschini, Tomas Vaskevicius
2022	J	`jnl`	Partial Matrix Completion. CoRR Varun Kanade, Elad Hazan, Adam Tauman Kalai
2022	A*	`conf`	Sample Complexity Bounds for Robustly Learning Decision Lists against Evasion Attacks. IJCAI Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell
2022	J	`jnl`	Sample Complexity Bounds for Robustly Learning Decision Lists against Evasion Attacks. CoRR Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell
2022	J	`jnl`	Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions. CoRR Satwik Bhattamishra, Arkil Patel, Varun Kanade, Phil Blunsom
2022	A*	`conf`	When are Local Queries Useful for Robust Learning? NeurIPS Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell
2022	J	`jnl`	When are Local Queries Useful for Robust Learning? CoRR Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell
2021	B	`conf`	Efficient Learning with Arbitrary Covariate Shift. ALT Adam Tauman Kalai, Varun Kanade
2021	J	`jnl`	Efficient Learning with Arbitrary Covariate Shift. CoRR Adam Kalai, Varun Kanade
2021	A*	`conf`	How Benign is Benign Overfitting ? ICLR Amartya Sanyal, Puneet K. Dokania, Varun Kanade, Philip H. S. Torr
2021	J	`jnl`	On the Hardness of Robust Classification. J. Mach. Learn. Res. Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell
2021	A	`conf`	Online k-means Clustering. AISTATS Vincent Cohen-Addad, Benjamin Guedj, Varun Kanade, Guy Rom
2021	A*	`conf`	Towards optimally abstaining from prediction with OOD test examples. NeurIPS Adam Kalai, Varun Kanade
2021	J	`jnl`	Towards optimally abstaining from prediction. CoRR Adam Tauman Kalai, Varun Kanade
2020	A*	`conf`	Adaptive Reduced Rank Regression. NeurIPS Qiong Wu, Felix Ming Fai Wong, Yanhua Li, Zhenming Liu, Varun Kanade
2020	A	`conf`	Differentiable Causal Backdoor Discovery. AISTATS Limor Gultchin, Matt J. Kusner, Varun Kanade, Ricardo Silva
2020	J	`jnl`	Differentiable Causal Backdoor Discovery. CoRR Limor Gultchin, Matt J. Kusner, Varun Kanade, Ricardo Silva
2020	J	`jnl`	How benign is benign overfitting? CoRR Amartya Sanyal, Puneet K. Dokania, Varun Kanade, Philip H. S. Torr
2020	J	`jnl`	Lottery Tickets in Linear Models: An Analysis of Iterative Magnitude Pruning. CoRR Bryn Elesedy, Varun Kanade, Yee Whye Teh
2020	J	`jnl`	The Statistical Complexity of Early Stopped Mirror Descent. CoRR Tomas Vaskevicius, Varun Kanade, Patrick Rebeschini
2020	A*	`conf`	The Statistical Complexity of Early-Stopped Mirror Descent. NeurIPS Tomas Vaskevicius, Varun Kanade, Patrick Rebeschini
2019	J	`jnl`	Adaptive Reduced Rank Regression. CoRR Qiong Wu, Felix Ming Fai Wong, Zhenming Liu, Yanhua Li, Varun Kanade
2019	A*	`conf`	Decentralized Cooperative Stochastic Bandits. NeurIPS David Martínez-Rubio, Varun Kanade, Patrick Rebeschini
2019	J	`jnl`	Hierarchical Clustering: Objective Functions and Algorithms. J. ACM Vincent Cohen-Addad, Varun Kanade, Frederik Mallmann-Trenn, Claire Mathieu
2019	A*	`conf`	Implicit Regularization for Optimal Sparse Recovery. NeurIPS Tomas Vaskevicius, Varun Kanade, Patrick Rebeschini
2019	J	`jnl`	Implicit Regularization for Optimal Sparse Recovery. CoRR Tomas Vaskevicius, Varun Kanade, Patrick Rebeschini
2019	A*	`conf`	On coalescence time in graphs: When is coalescing as fast as meeting?: Extended Abstract. SODA Varun Kanade, Frederik Mallmann-Trenn, Thomas Sauerwald
2019	A*	`conf`	On the Hardness of Robust Classification. NeurIPS Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell
2019	J	`jnl`	On the Hardness of Robust Classification. CoRR Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell
2019	J	`jnl`	On the Hardness of Robust Classification. Electron. Colloquium Comput. Complex. Pascale Gourdeau, Varun Kanade, Marta Kwiatkowska, James Worrell
2019	J	`jnl`	Online k-means Clustering. CoRR Vincent Cohen-Addad, Benjamin Guedj, Varun Kanade, Guy Rom
2019	A	`conf`	Statistical Windows in Testing for the Initial Distribution of a Reversible Markov Chain. AISTATS Quentin Berthet, Varun Kanade
2019	J	`jnl`	mu - biased quantum Fourier sampling. Quantum Inf. Comput. Varun Kanade, Andrea Rocchetto, Simone Severini
2018	A*	`conf`	Clustering Redemption-Beyond the Impossibility of Kleinberg's Axioms. NeurIPS Vincent Cohen-Addad, Varun Kanade, Frederik Mallmann-Trenn
2018	J	`jnl`	Decentralized Cooperative Stochastic Multi-armed Bandits. CoRR David Martínez-Rubio, Varun Kanade, Patrick Rebeschini
2018	A*	`conf`	Hierarchical Clustering: Objective Functions and Algorithms. SODA Vincent Cohen-Addad, Varun Kanade, Frederik Mallmann-Trenn, Claire Mathieu
2018	J	`jnl`	Learning DNFs under product distributions via μ-biased quantum Fourier sampling. CoRR Varun Kanade, Andrea Rocchetto, Simone Severini
2018	J	`jnl`	Low Rank Structure of Learned Representations. CoRR Amartya Sanyal, Varun Kanade, Philip H. S. Torr
2018	J	`jnl`	Statistical Windows in Testing for the Initial Distribution of a Reversible Markov Chain. CoRR Quentin Berthet, Varun Kanade
2018	A*	`conf`	TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service. ICML Amartya Sanyal, Matt J. Kusner, Adrià Gascón, Varun Kanade
2018	J	`jnl`	TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service. CoRR Amartya Sanyal, Matt J. Kusner, Adrià Gascón, Varun Kanade
2017	A*	`conf`	Brief Announcement: How Large is your Graph? PODC Varun Kanade, Frederik Mallmann-Trenn, Victor Verdugo
2017	—	`conf`	From which world is your graph. NIPS Cheng Li, Felix Ming Fai Wong, Zhenming Liu, Varun Kanade
2017	J	`jnl`	From which world is your graph? CoRR Cheng Li, Felix Ming Fai Wong, Zhenming Liu, Varun Kanade
2017	—	`conf`	Hierarchical Clustering Beyond the Worst-Case. NIPS Vincent Cohen-Addad, Varun Kanade, Frederik Mallmann-Trenn
2017	J	`jnl`	Hierarchical Clustering: Objective Functions and Algorithms. CoRR Vincent Cohen-Addad, Varun Kanade, Frederik Mallmann-Trenn, Claire Mathieu
2017	A	`conf`	How Large Is Your Graph?. DISC Varun Kanade, Frederik Mallmann-Trenn, Victor Verdugo
2017	J	`jnl`	How large is your graph? CoRR Varun Kanade, Frederik Mallmann-Trenn, Victor Verdugo
2017	A	`conf`	Online Optimization of Smoothed Piecewise Constant Functions. AISTATS Vincent Cohen-Addad, Varun Kanade
2017	A*	`conf`	Reliably Learning the ReLU in Polynomial Time. COLT Surbhi Goel, Varun Kanade, Adam R. Klivans, Justin Thaler
2016	A*	`conf`	Distance in the Forest Fire Model How far are you from Eve? SODA Varun Kanade, Reut Levi, Zvi Lotker, Frederik Mallmann-Trenn, Claire Mathieu
2016	J	`jnl`	Global and Local Information in Clustering Labeled Block Models. IEEE Trans. Inf. Theory Varun Kanade, Elchanan Mossel, Tselil Schramm
2016	J	`jnl`	On coalescence time in graphs-When is coalescing as fast as meeting? CoRR Varun Kanade, Frederik Mallmann-Trenn, Thomas Sauerwald
2016	J	`jnl`	Online Optimization of Smoothed Piecewise Constant Functions. CoRR Vincent Cohen-Addad, Varun Kanade
2016	J	`jnl`	Reliably Learning the ReLU in Polynomial Time. CoRR Surbhi Goel, Varun Kanade, Adam R. Klivans, Justin Thaler
2016	—	`conf`	Stable Matching with Evolving Preferences. APPROX-RANDOM Varun Kanade, Nikos Leonardos, Frédéric Magniez
2015	B	`conf`	Learning with a Drifting Target Concept. ALT Steve Hanneke, Varun Kanade, Liu Yang
2015	J	`jnl`	Learning with a Drifting Target Concept. CoRR Steve Hanneke, Varun Kanade, Liu Yang
2015	A*	`conf`	MCMC Learning. COLT Varun Kanade, Elchanan Mossel
2015	J	`jnl`	Stable Matching with Evolving Preferences. CoRR Varun Kanade, Nikos Leonardos, Frédéric Magniez
2014	A	`conf`	Attribute-efficient evolvability of linear functions. ITCS Elaine Angelino, Varun Kanade
2014	J	`jnl`	Distribution-Independent Reliable Learning. CoRR Varun Kanade, Justin Thaler
2014	A*	`conf`	Distribution-independent Reliable Learning. COLT Varun Kanade, Justin Thaler
2014	—	`conf`	Global and Local Information in Clustering Labeled Block Models. APPROX-RANDOM Varun Kanade, Elchanan Mossel, Tselil Schramm
2014	J	`jnl`	Global and Local Information in Clustering Labeled Block Models. CoRR Varun Kanade, Elchanan Mossel, Tselil Schramm
2014	J	`jnl`	Learning Hurdles for Sleeping Experts. ACM Trans. Comput. Theory Varun Kanade, Thomas Steinke
2014	A*	`conf`	Tracking Adversarial Targets. ICML Yasin Abbasi-Yadkori, Peter L. Bartlett, Varun Kanade
2013	J	`jnl`	Attribute-Efficient Evolvability of Linear Functions. CoRR Elaine Angelino, Varun Kanade
2013	A*	`conf`	Learning Using Local Membership Queries. COLT Pranjal Awasthi, Vitaly Feldman, Varun Kanade
2013	J	`jnl`	MCMC Learning. CoRR Varun Kanade, Elchanan Mossel
2013	—	`conf`	Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions. NIPS Yasin Abbasi-Yadkori, Peter L. Bartlett, Varun Kanade, Yevgeny Seldin, Csaba Szepesvári
2012	A*	`conf`	Computational Bounds on Statistical Query Learning. COLT Vitaly Feldman, Varun Kanade
2012	J	`jnl`	Distributed Non-Stochastic Experts CoRR Varun Kanade, Zhenming Liu, Bozidar Radunovic
2012	—	`conf`	Distributed Non-Stochastic Experts. NIPS Varun Kanade, Zhenming Liu, Bozidar Radunovic
2012	A	`conf`	Learning hurdles for sleeping experts. ITCS Varun Kanade, Thomas Steinke
2012	J	`jnl`	Learning using Local Membership Queries under Smooth Distributions CoRR Pranjal Awasthi, Varun Kanade
2012	J	`jnl`	Reliable agnostic learning. J. Comput. Syst. Sci. Adam Tauman Kalai, Varun Kanade, Yishay Mansour
2011	J	`jnl`	Computational Bottlenecks for Evolvability. Electron. Colloquium Comput. Complex. Varun Kanade
2011	J	`jnl`	Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression CoRR Sham M. Kakade, Adam Tauman Kalai, Varun Kanade, Ohad Shamir
2011	—	`conf`	Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression. NIPS Sham M. Kakade, Adam Kalai, Varun Kanade, Ohad Shamir
2011	A*	`conf`	Evolution with Recombination. FOCS Varun Kanade
2011	J	`jnl`	Learning Hurdles for Sleeping Experts. Electron. Colloquium Comput. Complex. Varun Kanade, Thomas Steinke
2010	J	`jnl`	Evolution with Drifting Targets CoRR Varun Kanade, Leslie G. Valiant, Jennifer Wortman Vaughan
2010	A*	`conf`	Evolution with Drifting Targets. COLT Varun Kanade, Leslie G. Valiant, Jennifer Wortman Vaughan
2009	—	`conf`	Potential-Based Agnostic Boosting. NIPS Adam Kalai, Varun Kanade
2009	A*	`conf`	Reliable Agnostic Learning. COLT Adam Tauman Kalai, Varun Kanade, Yishay Mansour
2009	A	`conf`	Sleeping Experts and Bandits with Stochastic Action Availability and Adversarial Rewards. AISTATS Varun Kanade, H. Brendan McMahan, Brent Bryan
2007	Misc	`conf`	Life (and routing) on the Wireless Manifold. HotNets Varun Kanade, Santosh S. Vempala
2007	A	`conf`	SWARM: A Parallel Programming Framework for Multicore Processors. IPDPS David A. Bader, Varun Kanade, Kamesh Madduri