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ML
2002
ACM
114views Machine Learning» more  ML 2002»
14 years 9 months ago
Building a Basic Block Instruction Scheduler with Reinforcement Learning and Rollouts
The execution order of a block of computer instructions on a pipelined machine can make a difference in running time by a factor of two or more. Compilers use heuristic schedulers...
Amy McGovern, J. Eliot B. Moss, Andrew G. Barto
CVPR
2011
IEEE
14 years 5 months ago
Online Group-Structured Dictionary Learning
We develop a dictionary learning method which is (i) online, (ii) enables overlapping group structures with (iii) non-convex sparsity-inducing regularization and (iv) handles the ...
Zoltan Szabo, Barnabas Poczos, Andras Lorincz
INTERSPEECH
2010
14 years 4 months ago
Memory-based active learning for French broadcast news
Stochastic dependency parsers can achieve very good results when they are trained on large corpora that have been manually annotated. Active learning is a procedure that aims at r...
Frédéric Tantini, Christophe Cerisar...
COLT
2008
Springer
14 years 11 months ago
Combining Expert Advice Efficiently
We show how models for prediction with expert advice can be defined concisely and clearly using hidden Markov models (HMMs); standard HMM algorithms can then be used to efficientl...
Wouter M. Koolen, Steven de Rooij
ICRA
2006
IEEE
131views Robotics» more  ICRA 2006»
15 years 3 months ago
Using Reinforcement Learning to Improve Exploration Trajectories for Error Minimization
Abstract— The mapping and localization problems have received considerable attention in robotics recently. The exploration problem that drives mapping has started to generate sim...
Thomas Kollar, Nicholas Roy