Varun Kanade

Orcid: 0000-0002-2300-4819

According to our database1, Varun Kanade authored at least 59 papers between 2007 and 2023.

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Bibliography

2023
On Coalescence Time in Graphs: When Is Coalescing as Fast as Meeting?
ACM Trans. Algorithms, April, 2023

Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions.
CoRR, 2023

Partial Matrix Completion.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Partial Matrix Completion.
CoRR, 2022

Beyond Impossibility: Balancing Sufficiency, Separation and Accuracy.
CoRR, 2022

Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition.
CoRR, 2022

When are Local Queries Useful for Robust Learning?
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sample Complexity Bounds for Robustly Learning Decision Lists against Evasion Attacks.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021
On the Hardness of Robust Classification.
J. Mach. Learn. Res., 2021

Towards optimally abstaining from prediction.
CoRR, 2021

Towards optimally abstaining from prediction with OOD test examples.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

How Benign is Benign Overfitting ?
Proceedings of the 9th International Conference on Learning Representations, 2021

Efficient Learning with Arbitrary Covariate Shift.
Proceedings of the Algorithmic Learning Theory, 2021

Online k-means Clustering.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Lottery Tickets in Linear Models: An Analysis of Iterative Magnitude Pruning.
CoRR, 2020

The Statistical Complexity of Early-Stopped Mirror Descent.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Adaptive Reduced Rank Regression.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Differentiable Causal Backdoor Discovery.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
mu - biased quantum Fourier sampling.
Quantum Inf. Comput., 2019

Hierarchical Clustering: Objective Functions and Algorithms.
J. ACM, 2019

On coalescence time in graphs: When is coalescing as fast as meeting?: Extended Abstract.
Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2019

Implicit Regularization for Optimal Sparse Recovery.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Decentralized Cooperative Stochastic Bandits.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Statistical Windows in Testing for the Initial Distribution of a Reversible Markov Chain.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Decentralized Cooperative Stochastic Multi-armed Bandits.
CoRR, 2018

Low Rank Structure of Learned Representations.
CoRR, 2018

Learning DNFs under product distributions via μ-biased quantum Fourier sampling.
CoRR, 2018

Clustering Redemption-Beyond the Impossibility of Kleinberg's Axioms.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
How Large Is Your Graph?.
Proceedings of the 31st International Symposium on Distributed Computing, 2017

Brief Announcement: How Large is your Graph?
Proceedings of the ACM Symposium on Principles of Distributed Computing, 2017

From which world is your graph.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Hierarchical Clustering Beyond the Worst-Case.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Reliably Learning the ReLU in Polynomial Time.
Proceedings of the 30th Conference on Learning Theory, 2017

Online Optimization of Smoothed Piecewise Constant Functions.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Global and Local Information in Clustering Labeled Block Models.
IEEE Trans. Inf. Theory, 2016

Distance in the Forest Fire Model How far are you from Eve?
Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, 2016

Stable Matching with Evolving Preferences.
Proceedings of the Approximation, 2016

2015
MCMC Learning.
Proceedings of The 28th Conference on Learning Theory, 2015

Learning with a Drifting Target Concept.
Proceedings of the Algorithmic Learning Theory - 26th International Conference, 2015

2014
Attribute-efficient evolvability of linear functions.
Proceedings of the Innovations in Theoretical Computer Science, 2014

Tracking Adversarial Targets.
Proceedings of the 31th International Conference on Machine Learning, 2014

Distribution-independent Reliable Learning.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Learning Using Local Membership Queries.
Proceedings of the COLT 2013, 2013

2012
Computational Bounds on Statistical Query Learning.
Proceedings of the COLT 2012, 2012

Reliable agnostic learning.
J. Comput. Syst. Sci., 2012

Learning using Local Membership Queries under Smooth Distributions
CoRR, 2012

Distributed Non-Stochastic Experts.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011
Learning Hurdles for Sleeping Experts.
Electron. Colloquium Comput. Complex., 2011

Computational Bottlenecks for Evolvability.
Electron. Colloquium Comput. Complex., 2011

Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Evolution with Recombination.
Proceedings of the IEEE 52nd Annual Symposium on Foundations of Computer Science, 2011

2010
Evolution with Drifting Targets.
Proceedings of the COLT 2010, 2010

2009
Sleeping Experts and Bandits with Stochastic Action Availability and Adversarial Rewards.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Potential-Based Agnostic Boosting.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2007
SWARM: A Parallel Programming Framework for Multicore Processors.
Proceedings of the 21th International Parallel and Distributed Processing Symposium (IPDPS 2007), 2007

Life (and routing) on the Wireless Manifold.
Proceedings of the 6th ACM Workshop on Hot Topics in Networks, 2007


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