16 citations · 20 across the 6 of their papers we have counts for
4 papers · 1 filter
No quantum speedup over gradient descent for non-smooth convex optimization
Ankit Garg, Robin Kothari, Praneeth Netrapalli +1
We study the first-order convex optimization problem, where we have black-box access to a (not necessarily smooth) function and its (sub)gradient. O…
Recent progress on scaling algorithms and applications
Ankit Garg, Rafael Oliveira
Scaling problems have a rich and diverse history, and thereby have found numerous applications in several fields of science and engineering. For instance, the matrix scaling proble…
Efficient algorithms for tensor scaling, quantum marginals and moment polytopes
Peter Bürgisser, Cole Franks, Ankit Garg +3
We present a polynomial time algorithm to approximately scale tensors of any format to arbitrary prescribed marginals (whenever possible). This unifies and generalizes a sequence o…
Operator Scaling via Geodesically Convex Optimization, Invariant Theory and Polynomial Identity Testing
Zeyuan Allen-Zhu, Ankit Garg, Yuanzhi Li +2
We propose a new second-order method for geodesically convex optimization on the natural hyperbolic metric over positive definite matrices. We apply it to solve the operator scalin…