Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
Speculation is an every day phenomenon whereby one acts in anticipation of particular conditions that are likely to hold in the future. Computer science research has seen many suc...
This paper describes a class ofprobabilistic approximation algorithms based on bucket elimination which o er adjustable levels of accuracy ande ciency. We analyzethe approximation...
Models for sequential decision making under uncertainty (e.g., Markov decision processes,or MDPs) have beenstudied in operations research for decades. The recent incorporation of ...
The polyhedral model is known to be a powerful framework to reason about high level loop transformations. Recent developments in optimizing compilers broke some generally accepted ...