Ashwin Pananjady
Orcid: 0000-0003-0824-9815
According to our database1,
Ashwin Pananjady
authored at least 46 papers
between 2013 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2024
Do Algorithms and Barriers for Sparse Principal Component Analysis Extend to Other Structured Settings?
IEEE Trans. Signal Process., 2024
Alternating minimization for generalized rank one matrix sensing: Sharp predictions from a random initialization.
Proceedings of the International Conference on Algorithmic Learning Theory, 2024
Learning the Eye of the Beholder: Statistical Modeling and Estimation for Personalized Color Perception.
Proceedings of the 60th Annual Allerton Conference on Communication, 2024
2023
Accelerated and Instance-Optimal Policy Evaluation with Linear Function Approximation.
SIAM J. Math. Data Sci., March, 2023
Proceedings of the 24th ACM Conference on Economics and Computation, 2023
Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
2022
IEEE Trans. Inf. Theory, 2022
A Dual Accelerated Method for Online Stochastic Distributed Averaging: From Consensus to Decentralized Policy Evaluation.
CoRR, 2022
Optimal and instance-dependent guarantees for Markovian linear stochastic approximation.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022
A Dual Accelerated Method for a Class of Distributed Optimization Problems: From Consensus to Decentralized Policy Evaluation.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022
2021
Instance-Dependent ℓ<sub>∞</sub>-Bounds for Policy Evaluation in Tabular Reinforcement Learning.
IEEE Trans. Inf. Theory, 2021
SIAM J. Math. Data Sci., 2021
2020
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems.
J. Mach. Learn. Res., 2020
Isotonic regression with unknown permutations: Statistics, computation, and adaptation.
CoRR, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the IEEE International Symposium on Information Theory, 2020
2019
Value function estimation in Markov reward processes: Instance-dependent 𝓁<sub>∞</sub>-bounds for policy evaluation.
CoRR, 2019
CoRR, 2019
Proceedings of the IEEE International Symposium on Information Theory, 2019
2018
Linear Regression With Shuffled Data: Statistical and Computational Limits of Permutation Recovery.
IEEE Trans. Inf. Theory, 2018
IEEE Trans. Inf. Theory, 2018
IEEE Trans. Inf. Theory, 2018
CoRR, 2018
Breaking the 1/√n Barrier: Faster Rates for Permutation-based Models in Polynomial Time.
CoRR, 2018
Breaking the $1/\sqrtn$ Barrier: Faster Rates for Permutation-based Models in Polynomial Time.
Proceedings of the Conference On Learning Theory, 2018
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
2017
IEEE/ACM Trans. Netw., 2017
CoRR, 2017
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017
Wasserstein stability of the entropy power inequality for log-concave random vectors.
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017
2016
CoRR, 2016
Proceedings of the 54th Annual Allerton Conference on Communication, 2016
2015
On the complexity of making a distinguished vertex minimum or maximum degree by vertex deletion.
J. Discrete Algorithms, 2015
Proceedings of the IEEE International Symposium on Information Theory, 2015
Proceedings of the 2015 IEEE Conference on Computer Communications, 2015
2014
Proceedings of the Twentieth National Conference on Communications, 2014
2013