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