226 citations · 1.9k across the 128 of their papers we have counts for
8 papers · 1 filter
Cost-Driven Representation Learning for Linear Quadratic Gaussian Control: Part I
Yi Tian, Kaiqing Zhang, Russ Tedrake +1
We study the task of learning state representations from potentially high-dimensional observations, with the goal of controlling an unknown partially observable system. We pursue a…
Computing Brascamp-Lieb Constants through the lens of Thompson Geometry
Melanie Weber, Suvrit Sra
This paper studies algorithms for efficiently computing Brascamp-Lieb constants, a task that has recently received much interest. In particular, we reduce the computation to a nonl…
CCCP is Frank-Wolfe in disguise
Alp Yurtsever, Suvrit Sra
This paper uncovers a simple but rather surprising connection: it shows that the well-known convex-concave procedure (CCCP) and its generalization to constrained problems are both…
On a class of geodesically convex optimization problems solved via Euclidean MM methods
Melanie Weber, Suvrit Sra
We study geodesically convex (g-convex) problems that can be written as a difference of Euclidean convex functions. This structure arises in several optimization problems in statis…
Theory and Algorithms for Diffusion Processes on Riemannian Manifolds
Xiang Cheng, Jingzhao Zhang, Suvrit Sra
We study geometric stochastic differential equations (SDEs) and their approximations on Riemannian manifolds. In particular, we introduce a simple new construction of geometric SDE…
Understanding the unstable convergence of gradient descent
Kwangjun Ahn, Jingzhao Zhang, Suvrit Sra
Most existing analyses of (stochastic) gradient descent rely on the condition that for -smooth costs, the step size is less than . However, many works have observed that in…