Nishant A. Mehta

According to our database, Nishant A. Mehta authored at least 32 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Near-optimal Per-Action Regret Bounds for Sleeping Bandits.

Quan Nguyen, Nishant A. Mehta

CoRR, 2024

2023

An improved regret analysis for UCB-N and TS-N.

Nishant A. Mehta

CoRR, 2023

Adversarial Online Multi-Task Reinforcement Learning.

Quan Nguyen, Nishant A. Mehta

Proceedings of the International Conference on Algorithmic Learning Theory, 2023

Thresholded linear bandits.

Nishant A. Mehta, Junpei Komiyama, Vamsi K. Potluru, Andrea Nguyen, Mica Grant-Hagen

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2021

Optimal Algorithms for Private Online Learning in a Stochastic Environment.

Bingshan Hu, Zhiming Huang, Nishant A. Mehta

CoRR, 2021

Best-case lower bounds in online learning.

Cristóbal Guzmán, Nishant A. Mehta, Ali Mortazavi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Fast Rates for General Unbounded Loss Functions: From ERM to Generalized Bayes.

Peter D. Grünwald, Nishant A. Mehta

J. Mach. Learn. Res., 2020

A Farewell to Arms: Sequential Reward Maximization on a Budget with a Giving Up Option.

Pon Kumar Sharoff, Nishant A. Mehta, Ravi Ganti

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Safe-Bayesian Generalized Linear Regression.

Rianne de Heide, Alisa Kirichenko, Peter Grunwald, Nishant A. Mehta

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Problem-dependent Regret Bounds for Online Learning with Feedback Graphs.

Bingshan Hu, Nishant A. Mehta, Jianping Pan

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Dying Experts: Efficient Algorithms with Optimal Regret Bounds.

Hamid Shayestehmanesh, Sajjad Azami, Nishant A. Mehta

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Intelligent Caching Algorithms in Heterogeneous Wireless Networks with Uncertainty.

Bingshan Hu, Yunjin Chen, Zhiming Huang, Nishant A. Mehta, Jianping Pan

Proceedings of the 39th IEEE International Conference on Distributed Computing Systems, 2019

A tight excess risk bound via a unified PAC-Bayesian-Rademacher-Shtarkov-MDL complexity.

Peter D. Grünwald, Nishant A. Mehta

Proceedings of the Algorithmic Learning Theory, 2019

Multi-Observation Regression.

Rafael M. Frongillo, Nishant A. Mehta, Tom Morgan, Bo Waggoner

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Interpreting Word-Level Hidden State Behaviour of Character-Level LSTM Language Models.

Avery Hiebert, Cole Peterson, Alona Fyshe, Nishant A. Mehta

Proceedings of the Workshop: Analyzing and Interpreting Neural Networks for NLP, 2018

2017

Fast rates with high probability in exp-concave statistical learning.

Nishant A. Mehta

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

CompAdaGrad: A Compressed, Complementary, Computationally-Efficient Adaptive Gradient Method.

Nishant A. Mehta, Alistair P. Rendell, Anish Varghese, Christfried Webers

CoRR, 2016

From exp-concavity to variance control: O(1/n) rates and online-to-batch conversion with high probability.

Nishant A. Mehta

CoRR, 2016

Fast Rates with Unbounded Losses.

Peter D. Grünwald, Nishant A. Mehta

CoRR, 2016

2015

Fast rates in statistical and online learning.

Tim van Erven, Peter D. Grünwald, Nishant A. Mehta, Mark D. Reid, Robert C. Williamson

J. Mach. Learn. Res., 2015

Generalized Mixability via Entropic Duality.

Mark D. Reid, Rafael M. Frongillo, Robert C. Williamson, Nishant A. Mehta

Proceedings of The 28th Conference on Learning Theory, 2015

2014

On sparse representations and new meta-learning paradigms for representation learning.

Nishant A. Mehta

PhD thesis, 2014

From Stochastic Mixability to Fast Rates.

Nishant A. Mehta, Robert C. Williamson

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

MLPACK: a scalable C++ machine learning library.

Ryan R. Curtin, James R. Cline, N. P. Slagle, William B. March, Parikshit Ram, Nishant A. Mehta, Alexander G. Gray

J. Mach. Learn. Res., 2013

Sparsity-Based Generalization Bounds for Predictive Sparse Coding.

Nishant Ajay Mehta, Alexander G. Gray

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

On the Sample Complexity of Predictive Sparse Coding

Nishant A. Mehta, Alexander G. Gray

CoRR, 2012

Computer detection approaches for the identification of phasic electromyographic (EMG) activity during human sleep.

Jacqueline Fairley, George K. Georgoulas, Nishant A. Mehta, Alexander G. Gray, Donald L. Bliwise

Biomed. Signal Process. Control., 2012

Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL.

Nishant A. Mehta, Dongryeol Lee, Alexander G. Gray

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

Optimal Control Strategies for an SSVEP-Based Brain-Computer Interface.

Nishant Ajay Mehta, Sadhir Hussain S. Hameed, Melody Moore Jackson

Int. J. Hum. Comput. Interact., 2011

2010

Generative and Latent Mean Map Kernels

Nishant A. Mehta, Alexander G. Gray

CoRR, 2010

Recognizing Sign Language from Brain Imaging.

Nishant Ajay Mehta, Thad Starner, Melody Moore Jackson, Karolyn O. Babalola, George Andrew James

Proceedings of the 20th International Conference on Pattern Recognition, 2010

2009

FuncICA for Time Series Pattern Discovery.

Nishant A. Mehta, Alexander G. Gray

Proceedings of the SIAM International Conference on Data Mining, 2009