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Adversarially-Trained Deep Nets Transfer Better

Jul 11, 2020
Francisco Utrera, Evan Kravitz, N. Benjamin Erichson, Rajiv Khanna, Michael W. Mahoney


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Boundary thickness and robustness in learning models

Jul 09, 2020
Yaoqing Yang, Rajiv Khanna, Yaodong Yu, Amir Gholami, Kurt Keutzer, Joseph E. Gonzalez, Kannan Ramchandran, Michael W. Mahoney


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Bayesian Coresets: An Optimization Perspective

Jul 01, 2020
Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo


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Improved guarantees and a multiple-descent curve for the Column Subset Selection Problem and the Nyström method

Feb 21, 2020
Michał Dereziński, Rajiv Khanna, Michael W. Mahoney


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Learning Sparse Distributions using Iterative Hard Thresholding

Nov 07, 2019
Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo

* NeurIPS 2019 

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On Linear Convergence of Weighted Kernel Herding

Jul 19, 2019
Rajiv Khanna, Michael W. Mahoney


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Boosting Black Box Variational Inference

Nov 01, 2018
Francesco Locatello, Gideon Dresdner, Rajiv Khanna, Isabel Valera, Gunnar Rätsch


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Interpreting Black Box Predictions using Fisher Kernels

Oct 23, 2018
Rajiv Khanna, Been Kim, Joydeep Ghosh, Oluwasanmi Koyejo


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Boosting Variational Inference: an Optimization Perspective

Mar 07, 2018
Francesco Locatello, Rajiv Khanna, Joydeep Ghosh, Gunnar Rätsch

* AISTATS 2018 

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IHT dies hard: Provable accelerated Iterative Hard Thresholding

Dec 26, 2017
Rajiv Khanna, Anastasios Kyrillidis

* 22 pages, accepted to AISTATS 2018 

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Restricted Strong Convexity Implies Weak Submodularity

Oct 12, 2017
Ethan R. Elenberg, Rajiv Khanna, Alexandros G. Dimakis, Sahand Negahban


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Scalable Greedy Feature Selection via Weak Submodularity

Mar 08, 2017
Rajiv Khanna, Ethan Elenberg, Alexandros G. Dimakis, Sahand Negahban, Joydeep Ghosh

* To appear in AISTATS 2017 

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On Approximation Guarantees for Greedy Low Rank Optimization

Mar 08, 2017
Rajiv Khanna, Ethan Elenberg, Alexandros G. Dimakis, Sahand Negahban


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A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe

Mar 07, 2017
Francesco Locatello, Rajiv Khanna, Michael Tschannen, Martin Jaggi

* appearing at AISTATS 2017 

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Information Projection and Approximate Inference for Structured Sparse Variables

Jul 12, 2016
Rajiv Khanna, Joydeep Ghosh, Russell Poldrack, Oluwasanmi Koyejo


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Pursuits in Structured Non-Convex Matrix Factorizations

Feb 12, 2016
Rajiv Khanna, Michael Tschannen, Martin Jaggi


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Towards a Better Understanding of Predict and Count Models

Nov 06, 2015
S. Sathiya Keerthi, Tobias Schnabel, Rajiv Khanna

* 17 pages 

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Parallel Matrix Factorization for Binary Response

Mar 22, 2012
Rajiv Khanna, Liang Zhang, Deepak Agarwal, Beechung Chen


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