In the context of physical synthesis, large-scale standard-cell placement algorithms must facilitate incremental changes to layout, both local and global. In particular, flexible ...
Saurabh N. Adya, Igor L. Markov, Paul G. Villarrub...
Abstract— We develop a general framework for MAP estimation in discrete and Gaussian graphical models using Lagrangian relaxation techniques. The key idea is to reformulate an in...
Jason K. Johnson, Dmitry M. Malioutov, Alan S. Wil...
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
In this paper we develop a theoretical analysis of the performance of sampling-based fitted value iteration (FVI) to solve infinite state-space, discounted-reward Markovian decisi...
"Experts algorithms" constitute a methodology for choosing actions repeatedly, when the rewards depend both on the choice of action and on the unknown current state of t...