L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized...
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. N...
Planning as satisfiability (SAT-Plan) is one of the best approaches to optimal planning, which has been shown effective on problems in many different domains. However, the potenti...
: This work is about an algorithm for solving a linear program which is simple to apply. There are three algorithms in this work. The first algorithm solves a two-variable linear p...
We examine the issues that arise in extending an estimatedregression (ER) planner to reason about autonomous processes that run and have continuous and discrete effects without th...
We develop a novel method for fitting high-resolution template meshes to detailed human body range scans with sparse 3D markers. We formulate an optimization problem in which the ...