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02/17/2021
Robust Estimation of Tree Structured Markov Random Fields
We study the problem of learning tree-structured Markov random fields (M...
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11/28/2020
On Generalization of Adaptive Methods for Over-parameterized Linear Regression
Over-parameterization and adaptive methods have played a crucial role in...
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06/10/2020
Robust Estimation of Tree Structured Ising Models
We consider the task of learning Ising models when the signs of differen...
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01/10/2020
Choosing the Sample with Lowest Loss makes SGD Robust
The presence of outliers can potentially significantly skew the paramete...
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11/12/2019
Negative sampling in semi-supervised learning
We introduce Negative Sampling in Semi-Supervised Learning (NS3L), a sim...
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11/16/2018
Minimum norm solutions do not always generalize well for over-parameterized problems
Stochastic gradient descent is the de facto algorithm for training deep ...
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05/04/2017
Matrix Factorization with Side and Higher Order Information
The problem of predicting unobserved entries of a partially observed mat...
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03/22/2016
