1.3k citations · 3.8k across the 222 of their papers we have counts for
5 papers · 2 filters
Learning to Remove Cuts in Integer Linear Programming
Pol Puigdemont, Stratis Skoulakis, Grigorios Chrysos +1
Cutting plane methods are a fundamental approach for solving integer linear programs (ILPs). In each iteration of such methods, additional linear constraints (cuts) are introduced…
Efficient Continual Finite-Sum Minimization
Ioannis Mavrothalassitis, Stratis Skoulakis, Leello Tadesse Dadi +1
Given a sequence of functions with , finite-sum minimization seeks a point minimizing $\sum_{j=1}^n…
Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces
Angeliki Kamoutsi, Peter Schmitt-Förster, Tobias Sutter +2
This work studies discrete-time discounted Markov decision processes with continuous state and action spaces and addresses the inverse problem of inferring a cost function from obs…
Universal Gradient Methods for Stochastic Convex Optimization
Anton Rodomanov, Ali Kavis, Yongtao Wu +2
We develop universal gradient methods for Stochastic Convex Optimization (SCO). Our algorithms automatically adapt not only to the oracle's noise but also to the Hölder smoothness…
Krylov Cubic Regularized Newton: A Subspace Second-Order Method with Dimension-Free Convergence Rate
Ruichen Jiang, Parameswaran Raman, Shoham Sabach +3
Second-order optimization methods, such as cubic regularized Newton methods, are known for their rapid convergence rates; nevertheless, they become impractical in high-dimensional…