12 citations · 15 across the 6 of their papers we have counts for
4 papers · 1 filter
Online Inverse Linear Optimization: Efficient Logarithmic-Regret Algorithm, Robustness to Suboptimality, and Lower Bound
Shinsaku Sakaue, Taira Tsuchiya, Han Bao +1
In online inverse linear optimization, a learner observes time-varying sets of feasible actions and an agent's optimal actions, selected by solving linear optimization over the fea…
Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation
Shinsaku Sakaue, Taihei Oki
Learning sketching matrices for fast and accurate low-rank approximation (LRA) has gained increasing attention. Recently, Bartlett, Indyk, and Wagner (COLT 2022) presented a genera…
Sample Complexity of Learning Heuristic Functions for Greedy-Best-First and A* Search
Shinsaku Sakaue, Taihei Oki
Greedy best-first search (GBFS) and A* search (A*) are popular algorithms for path-finding on large graphs. Both use so-called heuristic functions, which estimate how close a verte…
Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictions
Shinsaku Sakaue, Taihei Oki
Augmenting algorithms with learned predictions is a promising approach for going beyond worst-case bounds. Dinitz, Im, Lavastida, Moseley, and Vassilvitskii~(2021) have demonstrate…