Publications
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QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding
Dan Alistarh, Demjan Grubic, Jerry Li, Ryota Tomioka, Milan Vojnovic
arXiv, 2017
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Learning Graphical Models via Multiplicative Weights
Adam Klivans, Raghu Meka
arXiv, 2017
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Implicit regularization in matrix factorization
Suriya Gunasekar, Blake Woodworth, Srinadh Bhojanapalli, Behnam Neyshabur, Nathan Srebro
arXiv, 2017
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Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm
Liu, Wang
NeurIPS, 2016
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A Nearly-Linear Time Framework for Graph-Structured Sparsity
Chinmay Hegde, Piotr Indyk, Ludwig Schmidt
PMLR, 2015
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Stochastic gradient descent, weighted sampling, and the randomized Kaczmarz algorithm
Deanna Needell, Nathan Srebro & Rachel Ward
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Information and Human Values
Kenneth R. Fleischmann
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Low-rank Matrix Completion using Alternating Minimization
Prateek Jain, Praneeth Netrapalli, Sujay Sanghavi
arXiv, 2012
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Sparse and Low-Rank Matrix Decompositions
Venkat Chandrasekaran, Sujay Sanghavi, Pablo A. Parrilo, Alan S. Willsky
arXiv, 2009
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A Covenant with Transparency: Opening the Black Box of Models
Kenneth R. Fleischmann, William A. Wallace
ACM, 2005
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Gradient-based Monitoring of Learning Machines
L. Liu, J. Salmon, Z. Harchaoui
ICASSP, 2021
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Active Reward Learning from Critiques
Yuchen Cui, Scott Niekum