Nishant A. Mehta

51 papers A* 7A 10B 2Journal 28Unranked 3
YearRankTypeTitle / Venue / Authors
2025 A* conf
Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity.
ICML
Quan M. Nguyen, Nishant A. Mehta, Cristóbal Guzmán
2025 J jnl
Data-dependent Bounds with
CoRR
Quan Nguyen, Shinji Ito, Junpei Komiyama, Nishant A. Mehta
2025 A* conf
Data-dependent Bounds with T-Optimal Best-of-Both-Worlds Guarantees in Multi-Armed Bandits using Stability-Penalty Matching.
COLT
Quan M. Nguyen, Shinji Ito, Junpei Komiyama, Nishant A. Mehta
2025 A* conf
No-Regret Incentive-Compatible Online Learning under Exact Truthfulness with Non-Myopic Experts.
EC
Junpei Komiyama, Nishant A. Mehta, Ali Mortazavi
2025 J jnl
No-regret incentive-compatible online learning under exact truthfulness with non-myopic experts.
CoRR
Junpei Komiyama, Nishant A. Mehta, Ali Mortazavi
2024 J jnl
Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity.
CoRR
Quan Nguyen, Nishant A. Mehta, Cristóbal Guzmán
2024 A conf
Near-optimal Per-Action Regret Bounds for Sleeping Bandits.
AISTATS
Quan M. Nguyen, Nishant A. Mehta
2024 J jnl
Near-optimal Per-Action Regret Bounds for Sleeping Bandits.
CoRR
Quan Nguyen, Nishant A. Mehta
2024 J jnl
On the price of exact truthfulness in incentive-compatible online learning with bandit feedback: A regret lower bound for WSU-UX.
CoRR
Ali Mortazavi, Junhao Lin, Nishant A. Mehta
2024 A conf
On the price of exact truthfulness in incentive-compatible online learning with bandit feedback: a regret lower bound for WSU-UX.
AISTATS
Ali Mortazavi, Junhao Lin, Nishant A. Mehta
2024 A* conf
Open Problem: Optimal Rates for Stochastic Decision-Theoretic Online Learning Under Differentially Privacy.
COLT
Bingshan Hu, Nishant A. Mehta
2023 B conf
Adversarial Online Multi-Task Reinforcement Learning.
ALT
Quan Nguyen, Nishant A. Mehta
2023 J jnl
Adversarial Online Multi-Task Reinforcement Learning.
CoRR
Quan Nguyen, Nishant A. Mehta
2023 J jnl
An improved regret analysis for UCB-N and TS-N.
CoRR
Nishant A. Mehta
2023 A conf
Thresholded linear bandits.
AISTATS
Nishant A. Mehta, Junpei Komiyama, Vamsi K. Potluru, Andrea Nguyen, Mica Grant-Hagen
2021 J jnl
Best-Case Lower Bounds in Online Learning.
CoRR
Cristóbal Guzmán, Nishant A. Mehta, Ali Mortazavi
2021 A* conf
Best-case lower bounds in online learning.
NeurIPS
Cristóbal Guzmán, Nishant A. Mehta, Ali Mortazavi
2021 J jnl
Optimal Algorithms for Private Online Learning in a Stochastic Environment.
CoRR
Bingshan Hu, Zhiming Huang, Nishant A. Mehta
2020 A conf
A Farewell to Arms: Sequential Reward Maximization on a Budget with a Giving Up Option.
AISTATS
Pon Kumar Sharoff, Nishant A. Mehta, Ravi Ganti
2020 J jnl
A Farewell to Arms: Sequential Reward Maximization on a Budget with a Giving Up Option.
CoRR
Pon Kumar Sharoff, Nishant A. Mehta, Ravi Ganti
2020 J jnl
Fast Rates for General Unbounded Loss Functions: From ERM to Generalized Bayes.
J. Mach. Learn. Res.
Peter D. Grünwald, Nishant A. Mehta
2020 A conf
Safe-Bayesian Generalized Linear Regression.
AISTATS
Rianne de Heide, Alisa Kirichenko, Peter Grunwald, Nishant A. Mehta
2019 B conf
A tight excess risk bound via a unified PAC-Bayesian-Rademacher-Shtarkov-MDL complexity.
ALT
Peter D. Grünwald, Nishant A. Mehta
2019 A* conf
Dying Experts: Efficient Algorithms with Optimal Regret Bounds.
NeurIPS
Hamid Shayestehmanesh, Sajjad Azami, Nishant A. Mehta
2019 J jnl
Dying Experts: Efficient Algorithms with Optimal Regret Bounds.
CoRR
Hamid Shayestehmanesh, Sajjad Azami, Nishant A. Mehta
2019 A conf
Intelligent Caching Algorithms in Heterogeneous Wireless Networks with Uncertainty.
ICDCS
Bingshan Hu, Yunjin Chen, Zhiming Huang, Nishant A. Mehta, Jianping Pan
2019 A conf
Multi-Observation Regression.
AISTATS
Rafael M. Frongillo, Nishant A. Mehta, Tom Morgan, Bo Waggoner
2019 A conf
Problem-dependent Regret Bounds for Online Learning with Feedback Graphs.
UAI
Bingshan Hu, Nishant A. Mehta, Jianping Pan
2019 J jnl
Safe-Bayesian Generalized Linear Regression.
CoRR
Rianne de Heide, Alisa Kirichenko, Nishant A. Mehta, Peter Grünwald
2018 — conf
Interpreting Word-Level Hidden State Behaviour of Character-Level LSTM Language Models.
BlackboxNLP@EMNLP
Avery Hiebert, Cole Peterson, Alona Fyshe, Nishant A. Mehta
2018 J jnl
Multi-Observation Regression.
CoRR
Rafael M. Frongillo, Nishant A. Mehta, Tom Morgan, Bo Waggoner
2017 J jnl
A Tight Excess Risk Bound via a Unified PAC-Bayesian-Rademacher-Shtarkov-MDL Complexity.
CoRR
Peter D. Grünwald, Nishant A. Mehta
2017 A conf
Fast rates with high probability in exp-concave statistical learning.
AISTATS
Nishant A. Mehta
2016 J jnl
CompAdaGrad: A Compressed, Complementary, Computationally-Efficient Adaptive Gradient Method.
CoRR
Nishant A. Mehta, Alistair P. Rendell, Anish Varghese, Christfried Webers
2016 J jnl
Fast Rates with Unbounded Losses.
CoRR
Peter D. Grünwald, Nishant A. Mehta
2016 J jnl
From exp-concavity to variance control: O(1/n) rates and online-to-batch conversion with high probability.
CoRR
Nishant A. Mehta
2015 J jnl
Fast rates in statistical and online learning.
CoRR
Tim van Erven, Peter D. Grünwald, Nishant A. Mehta, Mark D. Reid, Robert C. Williamson
2015 J jnl
Fast rates in statistical and online learning.
J. Mach. Learn. Res.
Tim van Erven, Peter D. Grünwald, Nishant A. Mehta, Mark D. Reid, Robert C. Williamson
2015 A* conf
Generalized Mixability via Entropic Duality.
COLT
Mark D. Reid, Rafael M. Frongillo, Robert C. Williamson, Nishant A. Mehta
2014 — conf
From Stochastic Mixability to Fast Rates.
NIPS
Nishant A. Mehta, Robert C. Williamson
2014 J jnl
From Stochastic Mixability to Fast Rates.
CoRR
Nishant A. Mehta, Robert C. Williamson
2014 J jnl
Generalized Mixability via Entropic Duality.
CoRR
Mark D. Reid, Rafael M. Frongillo, Robert C. Williamson, Nishant A. Mehta
2014 — —
On sparse representations and new meta-learning paradigms for representation learning.
Nishant A. Mehta
2013 J jnl
MLPACK: a scalable C++ machine learning library.
J. Mach. Learn. Res.
Ryan R. Curtin, James R. Cline, N. P. Slagle, William B. March, Parikshit Ram, Nishant A. Mehta, Alexander G. Gray
2012 J jnl
Computer detection approaches for the identification of phasic electromyographic (EMG) activity during human sleep.
Biomed. Signal Process. Control.
Jacqueline Fairley, George K. Georgoulas, Nishant A. Mehta, Alexander G. Gray, Donald L. Bliwise
2012 J jnl
MLPACK: A Scalable C++ Machine Learning Library
CoRR
Ryan R. Curtin, James R. Cline, N. P. Slagle, William B. March, Parikshit Ram, Nishant A. Mehta, Alexander G. Gray
2012 J jnl
Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL
CoRR
Nishant A. Mehta, Dongryeol Lee, Alexander G. Gray
2012 — conf
Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL.
NIPS
Nishant A. Mehta, Dongryeol Lee, Alexander G. Gray
2012 J jnl
On the Sample Complexity of Predictive Sparse Coding
CoRR
Nishant A. Mehta, Alexander G. Gray
2010 J jnl
Generative and Latent Mean Map Kernels
CoRR
Nishant A. Mehta, Alexander G. Gray
2009 A conf
FuncICA for Time Series Pattern Discovery.
SDM
Nishant A. Mehta, Alexander G. Gray