Nishant A. Mehta
Nishant A. Mehta
Assistant Professor, University of Victoria
Verified email at - Homepage
Cited by
Cited by
MLPACK: A scalable C++ machine learning library
RR Curtin, JR Cline, NP Slagle, WB March, P Ram, NA Mehta, AG Gray
The Journal of Machine Learning Research 14 (1), 801-805, 2013
Fast rates in statistical and online learning
T Van Erven, PD Grünwald, NA Mehta, MD Reid, RC Williamson
The Journal of Machine Learning Research 16 (1), 1793-1861, 2015
Fast rates for general unbounded loss functions: from ERM to generalized Bayes
PD Grünwald, NA Mehta
Journal of Machine Learning Research 21 (56), 1-80, 2020
Fast rates with high probability in exp-concave statistical learning
N Mehta
Artificial Intelligence and Statistics, 1085-1093, 2017
Sparsity-based generalization bounds for predictive sparse coding
N Mehta, A Gray
International Conference on Machine Learning, 36-44, 2013
A tight excess risk bound via a unified PAC-Bayesian–Rademacher–Shtarkov–MDL complexity
PD Grünwald, NA Mehta
Algorithmic Learning Theory, 433-465, 2019
Safe-Bayesian generalized linear regression
R Heide, A Kirichenko, P Grunwald, N Mehta
International Conference on Artificial Intelligence and Statistics, 2623-2633, 2020
On the sample complexity of predictive sparse coding
NA Mehta, AG Gray
arXiv preprint arXiv:1202.4050, 2012
Generalized mixability via entropic duality
MD Reid, RM Frongillo, RC Williamson, N Mehta
Conference on Learning Theory, 1501-1522, 2015
Computer detection approaches for the identification of phasic electromyographic (EMG) activity during human sleep
JA Fairley, G Georgoulas, NA Mehta, AG Gray, DL Bliwise
Biomedical Signal Processing and Control 7 (6), 606-615, 2012
Fast rates with unbounded losses
PD Grünwald, NA Mehta
arXiv preprint arXiv:1605.00252 2, 14, 2016
Modeling software behavior using learned predicates
AX Zheng, MS Musuvathi, NA Mehta
US Patent 9,098,621, 2015
From stochastic mixability to fast rates
NA Mehta, RC Williamson
Advances in Neural Information Processing Systems 27, 2014
Independent component analysis
F Westad, M Kermit
Elsevier, 2009
Optimal algorithms for private online learning in a stochastic environment
B Hu, Z Huang, NA Mehta
arXiv preprint arXiv:2102.07929, 2021
Problem-dependent regret bounds for online learning with feedback graphs
B Hu, NA Mehta, J Pan
Uncertainty in Artificial Intelligence, 852-861, 2020
Intelligent caching algorithms in heterogeneous wireless networks with uncertainty
B Hu, Y Chen, Z Huang, NA Mehta, J Pan
2019 IEEE 39th International Conference on Distributed Computing Systems …, 2019
Minimax multi-task learning and a generalized loss-compositional paradigm for MTL
N Mehta, D Lee, A Gray
Advances in Neural Information Processing Systems 25, 2012
Fast rates for general unbounded loss functions: from ERM to generalized Bayes
PD Grünwald, NA Mehta
arXiv preprint arXiv:1605.00252, 2016
VisIRR: interactive visual information retrieval and recommendation for large-scale document data
J Choo, C Lee, E Clarkson, Z Liu, H Lee, DHP Chau, F Li, R Kannan, ...
Georgia Institute of Technology, 2013
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