Rajiv Khanna
Rajiv Khanna
Postdoc, UC Berkeley
Bestätigte E-Mail-Adresse bei berkeley.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Examples are not Enough, Learn to Criticize! Criticism for Interpretability
B Kim, R Khanna, O Koyejo
Advances in Neural Information Processing Systems 29 (NIPS 2016) 29, 2280--2288, 2016
4002016
Examples are not enough, learn to criticize! criticism for interpretability
B Kim, R Khanna, OO Koyejo
Advances in Neural Information Processing Systems, 2280-2288, 2016
4002016
Structured learning for non-smooth ranking losses
S Chakrabarti, R Khanna, U Sawant, C Bhattacharyya
Proceedings of the 14th ACM SIGKDD international conference on knowledge …, 2008
1312008
Estimating rates of rare events with multiple hierarchies through scalable log-linear models
D Agarwal, R Agrawal, R Khanna, N Kota
Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010
1042010
Scalable greedy feature selection via weak submodularity
R Khanna, E Elenberg, A Dimakis, S Negahban, J Ghosh
Artificial Intelligence and Statistics, 1560-1568, 2017
602017
Restricted strong convexity implies weak submodularity
ER Elenberg, R Khanna, AG Dimakis, S Negahban
The Annals of Statistics 46 (6B), 3539-3568, 2018
582018
A unified optimization view on generalized matching pursuit and frank-wolfe
F Locatello, R Khanna, M Tschannen, M Jaggi
Artificial Intelligence and Statistics, 860-868, 2017
502017
Interpreting black box predictions using fisher kernels
R Khanna, B Kim, J Ghosh, S Koyejo
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
482019
Restricted strong convexity implies weak submodularity
ER Elenberg, R Khanna, AG Dimakis, S Negahban
arXiv preprint arXiv:1612.00804, 2016
372016
Boosting variational inference: an optimization perspective
F Locatello, R Khanna, J Ghosh, G Ratsch
International Conference on Artificial Intelligence and Statistics, 464-472, 2018
232018
On approximation guarantees for greedy low rank optimization
R Khanna, ER Elenberg, AG Dimakis, J Ghosh, S Negahban
International Conference on Machine Learning, 1837-1846, 2017
232017
Sparse submodular probabilistic PCA
R Khanna, J Ghosh, R Poldrack, O Koyejo
Artificial Intelligence and Statistics, 453-461, 2015
222015
IHT dies hard: Provable accelerated iterative hard thresholding
R Khanna, A Kyrillidis
International Conference on Artificial Intelligence and Statistics, 188-198, 2018
212018
Boosting black box variational inference
F Locatello, G Dresdner, R Khanna, I Valera, G Rätsch
arXiv preprint arXiv:1806.02185, 2018
202018
Translating relevance scores to probabilities for contextual advertising
D Agarwal, E Gabrilovich, R Hall, V Josifovski, R Khanna
Proceedings of the 18th ACM conference on Information and knowledge …, 2009
202009
Adversarially-trained deep nets transfer better
F Utrera, E Kravitz, NB Erichson, R Khanna, MW Mahoney
arXiv preprint arXiv:2007.05869, 2020
192020
Parallel matrix factorization for binary response
R Khanna, L Zhang, D Agarwal, BC Chen
2013 IEEE International Conference on Big Data, 430-438, 2013
152013
On prior distributions and approximate inference for structured variables
OO Koyejo, R Khanna, J Ghosh, R Poldrack
Advances in Neural Information Processing Systems 27, 676-684, 2014
142014
Improved guarantees and a multiple-descent curve for Column Subset Selection and the Nystr\" om method
M Dereziński, R Khanna, MW Mahoney
arXiv preprint arXiv:2002.09073, 2020
112020
Towards a better understanding of predict and count models
SS Keerthi, T Schnabel, R Khanna
arXiv preprint arXiv:1511.02024, 2015
82015
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