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Xinhua Zhang

University of Alberta

Proximal Mapping for Deep Regularization

Jun 14, 2020
Mao Li, Yingyi Ma, Xinhua Zhang

* 24 pages, 7 figures 

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Convex Representation Learning for Generalized Invariance in Semi-Inner-Product Space

Apr 25, 2020
Yingyi Ma, Vignesh Ganapathiraman, Yaoliang Yu, Xinhua Zhang


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Generalised Lipschitz Regularisation Equals Distributional Robustness

Feb 11, 2020
Zac Cranko, Zhan Shi, Xinhua Zhang, Richard Nock, Simon Kornblith


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Consistent Robust Adversarial Prediction for General Multiclass Classification

Dec 18, 2018
Rizal Fathony, Kaiser Asif, Anqi Liu, Mohammad Ali Bashiri, Wei Xing, Sima Behpour, Xinhua Zhang, Brian D. Ziebart

* 48 pages, 10 figures 

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Distributionally Robust Graphical Models

Nov 07, 2018
Rizal Fathony, Ashkan Rezaei, Mohammad Ali Bashiri, Xinhua Zhang, Brian D. Ziebart

* Appears in Neural Information Processing Systems, 2018 

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DS-MLR: Exploiting Double Separability for Scaling up Distributed Multinomial Logistic Regression

Aug 03, 2018
Parameswaran Raman, Sriram Srinivasan, Shin Matsushima, Xinhua Zhang, Hyokun Yun, S. V. N. Vishwanathan


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Exp-Concavity of Proper Composite Losses

May 20, 2018
Parameswaran Kamalaruban, Robert C. Williamson, Xinhua Zhang

* PMLR 40:1035-1065, 2015 

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Distributed Stochastic Optimization of the Regularized Risk

Jun 09, 2015
Shin Matsushima, Hyokun Yun, Xinhua Zhang, S. V. N. Vishwanathan


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Generalized Conditional Gradient for Sparse Estimation

Oct 17, 2014
Yaoliang Yu, Xinhua Zhang, Dale Schuurmans

* 67 pages, 20 figures 

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Convex Relaxations of Bregman Divergence Clustering

Sep 26, 2013
Hao Cheng, Xinhua Zhang, Dale Schuurmans

* Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI2013) 

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Regularizers versus Losses for Nonlinear Dimensionality Reduction: A Factored View with New Convex Relaxations

Jun 27, 2012
Yaoliang Yu, James Neufeld, Ryan Kiros, Xinhua Zhang, Dale Schuurmans

* Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012) 

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Smoothing Multivariate Performance Measures

Feb 14, 2012
Xinhua Zhang, Ankan Saha, S. V. N. Vishwanatan


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Regularized Risk Minimization by Nesterov's Accelerated Gradient Methods: Algorithmic Extensions and Empirical Studies

Nov 01, 2010
Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan

* 28 pages. Supplementary material for NIPS 2010 paper "Lower Bounds on Rate of Convergence of Cutting Plane Methods" by the same authors 

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New Approximation Algorithms for Minimum Enclosing Convex Shapes

Sep 15, 2010
Ankan Saha, S. V. N. Vishwanathan, Xinhua Zhang

* 18 Pages Accepted in SODA 2011 

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Faster Rates for training Max-Margin Markov Networks

Mar 06, 2010
Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan

* 14 pages Submitted to COLT 2010 

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Lower Bounds for BMRM and Faster Rates for Training SVMs

Sep 08, 2009
Ankan Saha, Xinhua Zhang, S. V. N. Vishwanathan

* 21 pages, 49 figures 

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