The three-mode partitioning model is a clustering model for three-way three-mode data sets that implies a simultaneous partitioning of all three modes involved in the data. In the...
Random sampling is one of the most fundamental data management tools available. However, most current research involving sampling considers the problem of how to use a sample, and...
Following the well-studied two-stage optimization framework for stochastic optimization [15, 18], we study approximation algorithms for robust two-stage optimization problems with ...
Uriel Feige, Kamal Jain, Mohammad Mahdian, Vahab S...
− In this paper, we present a new timing-driven placement algorithm, which attempts to minimize zigzags and crisscrosses on the timing-critical paths of a circuit. We observed th...
In recent years there has been a great deal of interest in "modular reinforcement learning" (MRL). Typically, problems are decomposed into concurrent subgoals, allowing ...
Sooraj Bhat, Charles Lee Isbell Jr., Michael Matea...