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» Algorithmic Theories of Everything
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ICML
2000
IEEE
16 years 7 months ago
Learning Subjective Functions with Large Margins
In manyoptimization and decision problems the objective function can be expressed as a linear combinationof competingcriteria, the weights of whichspecify the relative importanceo...
Claude-Nicolas Fiechter, Seth Rogers
ICML
1996
IEEE
16 years 7 months ago
Toward Optimal Feature Selection
In this paper, we examine a method for feature subset selection based on Information Theory. Initially, a framework for de ning the theoretically optimal, but computationally intr...
Daphne Koller, Mehran Sahami
STOC
2003
ACM
122views Algorithms» more  STOC 2003»
16 years 6 months ago
Learning juntas
We consider a fundamental problem in computational learning theory: learning an arbitrary Boolean function which depends on an unknown set of k out of n Boolean variables. We give...
Elchanan Mossel, Ryan O'Donnell, Rocco A. Servedio
201
Voted
TACAS
2010
Springer
221views Algorithms» more  TACAS 2010»
16 years 1 months ago
Trace-Based Symbolic Analysis for Atomicity Violations
Abstract. We propose a symbolic algorithm to accurately predict atomicity violations by analyzing a concrete execution trace of a concurrent program. We use both the execution trac...
Chao Wang, Rhishikesh Limaye, Malay K. Ganai, Aart...
ICRA
2009
IEEE
188views Robotics» more  ICRA 2009»
16 years 24 days ago
Potential field guide for humanoid multicontacts acyclic motion planning
Abstract—We present a motion planning algorithm that computes rough trajectories used by a contact-points planner as a guide to grow its search graph. We adapt collision-free mot...
Karim Bouyarmane, Adrien Escande, Florent Lamiraux...