15 citations · 44 across the 9 of their papers we have counts for
5 papers · 1 filter
Model Predictive Control via On-Policy Imitation Learning
Kwangjun Ahn, Zakaria Mhammedi, Horia Mania +2
In this paper, we leverage the rapid advances in imitation learning, a topic of intense recent focus in the Reinforcement Learning (RL) literature, to develop new sample complexity…
Riemannian Perspective on Matrix Factorization
Kwangjun Ahn, Felipe Suarez
We study the non-convex matrix factorization approach to matrix completion via Riemannian geometry. Based on an optimization formulation over a Grassmannian manifold, we characteri…
SGD with shuffling: optimal rates without component convexity and large epoch requirements
Kwangjun Ahn, Chulhee Yun, Suvrit Sra
We study without-replacement SGD for solving finite-sum optimization problems. Specifically, depending on how the indices of the finite-sum are shuffled, we consider the RandomShuf…
On Tight Convergence Rates of Without-replacement SGD
Kwangjun Ahn, Suvrit Sra
For solving finite-sum optimization problems, SGD without replacement sampling is empirically shown to outperform SGD. Denoting by the number of components in the cost and …
From Nesterov's Estimate Sequence to Riemannian Acceleration
Kwangjun Ahn, Suvrit Sra
We propose the first global accelerated gradient method for Riemannian manifolds. Toward establishing our result we revisit Nesterov's estimate sequence technique and develop an al…