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83
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LCPC
2005
Springer
15 years 3 months ago
Analytic Models and Empirical Search: A Hybrid Approach to Code Optimization
Compilers employ system models, sometimes implicitly, to make code optimization decisions. These models are analytic; they reflect their implementor’s understanding and beliefs ...
Arkady Epshteyn, María Jesús Garzar&...
CORR
2010
Springer
146views Education» more  CORR 2010»
14 years 9 months ago
Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization
Solving stochastic optimization problems under partial observability, where one needs to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously diffic...
Daniel Golovin, Andreas Krause
76
Voted
CORR
2004
Springer
103views Education» more  CORR 2004»
14 years 9 months ago
Online convex optimization in the bandit setting: gradient descent without a gradient
We study a general online convex optimization problem. We have a convex set S and an unknown sequence of cost functions c1, c2, . . . , and in each period, we choose a feasible po...
Abraham Flaxman, Adam Tauman Kalai, H. Brendan McM...
IJCAI
2003
14 years 11 months ago
Generalizing Plans to New Environments in Relational MDPs
A longstanding goal in planning research is the ability to generalize plans developed for some set of environments to a new but similar environment, with minimal or no replanning....
Carlos Guestrin, Daphne Koller, Chris Gearhart, Ne...
GECCO
2006
Springer
186views Optimization» more  GECCO 2006»
15 years 1 months ago
Genetic algorithms for action set selection across domains: a demonstration
Action set selection in Markov Decision Processes (MDPs) is an area of research that has received little attention. On the other hand, the set of actions available to an MDP agent...
Greg Lee, Vadim Bulitko