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Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization


Jul 31, 2018
Blake Woodworth, Jialei Wang, Brendan McMahan, Nathan Srebro


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Distributed Stochastic Multi-Task Learning with Graph Regularization


Feb 11, 2018
Weiran Wang, Jialei Wang, Mladen Kolar, Nathan Srebro


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Rate Optimal Estimation and Confidence Intervals for High-dimensional Regression with Missing Covariates


Nov 03, 2017
Yining Wang, Jialei Wang, Sivaraman Balakrishnan, Aarti Singh

* 41 pages, 1 figure, 3 tables 

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Parallel Bayesian Global Optimization of Expensive Functions


Nov 01, 2017
Jialei Wang, Scott C. Clark, Eric Liu, Peter I. Frazier


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Gradient Sparsification for Communication-Efficient Distributed Optimization


Oct 26, 2017
Jianqiao Wangni, Jialei Wang, Ji Liu, Tong Zhang


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Improved Optimization of Finite Sums with Minibatch Stochastic Variance Reduced Proximal Iterations


Oct 11, 2017
Jialei Wang, Tong Zhang


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A General Distributed Dual Coordinate Optimization Framework for Regularized Loss Minimization


Aug 25, 2017
Shun Zheng, Jialei Wang, Fen Xia, Wei Xu, Tong Zhang


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Memory and Communication Efficient Distributed Stochastic Optimization with Minibatch-Prox


Jun 09, 2017
Jialei Wang, Weiran Wang, Nathan Srebro


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Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms


Mar 07, 2017
Jialei Wang, Lin Xiao


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Efficient coordinate-wise leading eigenvector computation


Feb 25, 2017
Jialei Wang, Weiran Wang, Dan Garber, Nathan Srebro


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Stochastic Canonical Correlation Analysis


Feb 21, 2017
Chao Gao, Dan Garber, Nathan Srebro, Jialei Wang, Weiran Wang


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Multi-Information Source Optimization


Nov 15, 2016
Matthias Poloczek, Jialei Wang, Peter I. Frazier

* Added: benchmark logistic regression on MNIST/USPS, comparison to MTBO/entropy search, estimation of hyper-parameters 

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Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis


Nov 14, 2016
Weiran Wang, Jialei Wang, Dan Garber, Nathan Srebro

* Accepted by NIPS 2016 

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Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data


Oct 10, 2016
Jialei Wang, Jason D. Lee, Mehrdad Mahdavi, Mladen Kolar, Nathan Srebro


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Warm Starting Bayesian Optimization


Aug 11, 2016
Matthias Poloczek, Jialei Wang, Peter I. Frazier

* To Appear in the Proc. of the 2016 Winter Simulation Conference 

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Efficient Distributed Learning with Sparsity


May 25, 2016
Jialei Wang, Mladen Kolar, Nathan Srebro, Tong Zhang


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Removing Clouds and Recovering Ground Observations in Satellite Image Sequences via Temporally Contiguous Robust Matrix Completion


Apr 13, 2016
Jialei Wang, Peder A. Olsen, Andrew R. Conn, Aurelie C. Lozano

* To Appear In Conference on Computer Vision and Pattern Recognition (CVPR 2016) 

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Distributed Multi-Task Learning with Shared Representation


Mar 07, 2016
Jialei Wang, Mladen Kolar, Nathan Srebro


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Reducing Runtime by Recycling Samples


Feb 05, 2016
Jialei Wang, Hai Wang, Nathan Srebro


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Distributed Multitask Learning


Oct 02, 2015
Jialei Wang, Mladen Kolar, Nathan Srebro


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Bayesian optimization for materials design


Jun 03, 2015
Peter I. Frazier, Jialei Wang


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Inference for Sparse Conditional Precision Matrices


Dec 24, 2014
Jialei Wang, Mladen Kolar


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Fast Bounded Online Gradient Descent Algorithms for Scalable Kernel-Based Online Learning


Jun 18, 2012
Peilin Zhao, Jialei Wang, Pengcheng Wu, Rong Jin, Steven C. H. Hoi

* ICML2012 

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Exact Soft Confidence-Weighted Learning


Jun 18, 2012
Jialei Wang, Peilin Zhao, Steven C. H. Hoi

* ICML2012 

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