256 citations · 1k across the 26 of their papers we have counts for
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Efficient Distributed SGD with Variance Reduction
Soham De, Tom Goldstein
Stochastic Gradient Descent (SGD) has become one of the most popular optimization methods for training machine learning models on massive datasets. However, SGD suffers from two ma…
Variance Reduction for Distributed Stochastic Gradient Descent
Soham De, Gavin Taylor, Tom Goldstein
Variance reduction (VR) methods boost the performance of stochastic gradient descent (SGD) by enabling the use of larger, constant stepsizes and preserving linear convergence rates…
Layer-Specific Adaptive Learning Rates for Deep Networks
Bharat Singh, Soham De, Yangmuzi Zhang +2
The increasing complexity of deep learning architectures is resulting in training time requiring weeks or even months. This slow training is due in part to vanishing gradients, in…
Plagiarism Detection in Polyphonic Music using Monaural Signal Separation
Soham De, Indradyumna Roy, Tarunima Prabhakar +4
Given the large number of new musical tracks released each year, automated approaches to plagiarism detection are essential to help us track potential violations of copyright. Most…