11 citations · 16 across the 5 of their papers we have counts for
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math.OC2020
Explicit Regularization of Stochastic Gradient Methods through Duality
Anant Raj, Francis Bach
We consider stochastic gradient methods under the interpolation regime where a perfect fit can be obtained (minimum loss at each observation). While previous work highlighted the i…
math.OC2019
Importance Sampling via Local Sensitivity
Anant Raj, Cameron Musco, Lester Mackey
Given a loss function that can be written as the sum of losses over a large set of inputs , it is often desirable to approximate $…
math.OC2018
k-SVRG: Variance Reduction for Large Scale Optimization
Anant Raj, Sebastian U. Stich
Variance reduced stochastic gradient (SGD) methods converge significantly faster than the vanilla SGD counterpart. However, these methods are not very practical on large scale prob…