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POPL
2009
ACM
16 years 7 months ago
Equality saturation: a new approach to optimization
Optimizations in a traditional compiler are applied sequentially, with each optimization destructively modifying the program to produce a transformed program that is then passed t...
Ross Tate, Michael Stepp, Zachary Tatlock, Sorin L...
GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
15 years 10 months ago
On-line evolutionary computation for reinforcement learning in stochastic domains
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
Shimon Whiteson, Peter Stone
SDM
2008
SIAM
144views Data Mining» more  SDM 2008»
15 years 8 months ago
Active Learning with Model Selection in Linear Regression
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
Masashi Sugiyama, Neil Rubens
NIPS
2007
15 years 8 months ago
Discriminative Batch Mode Active Learning
Active learning sequentially selects unlabeled instances to label with the goal of reducing the effort needed to learn a good classifier. Most previous studies in active learning...
Yuhong Guo, Dale Schuurmans
CVPR
2008
IEEE
16 years 9 months ago
Dynamic visual category learning
Dynamic visual category learning calls for efficient adaptation as new training images become available or new categories are defined, existing training images or categories becom...
Tom Yeh, Trevor Darrell