5 citations · 12 across the 5 of their papers we have counts for
5 papers
Variational Principles for Mirror Descent and Mirror Langevin Dynamics
Belinda Tzen, Anant Raj, Maxim Raginsky +1
Mirror descent, introduced by Nemirovski and Yudin in the 1970s, is a primal-dual convex optimization method that can be tailored to the geometry of the optimization problem at han…
Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models
Anant Raj, Umut Şimşekli, Alessandro Rudi
This paper deals with the problem of efficient sampling from a stochastic differential equation, given the drift function and the diffusion matrix. The proposed approach leverages…
Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions
Anant Raj, Lingjiong Zhu, Mert Gürbüzbalaban +1
Heavy-tail phenomena in stochastic gradient descent (SGD) have been reported in several empirical studies. Experimental evidence in previous works suggests a strong interplay betwe…
Screening Rules for Convex Problems
Anant Raj, Jakob Olbrich, Bernd Gärtner +2
We propose a new framework for deriving screening rules for convex optimization problems. Our approach covers a large class of constrained and penalized optimization formulations,…
Mind the Gap: Subspace based Hierarchical Domain Adaptation
Anant Raj, Vinay P. Namboodiri, Tinne Tuytelaars
Domain adaptation techniques aim at adapting a classifier learnt on a source domain to work on the target domain. Exploiting the subspaces spanned by features of the source and tar…