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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
APPROX
2009
Springer
136views Algorithms» more  APPROX 2009»
16 years 1 months ago
Succinct Representation of Codes with Applications to Testing
Motivated by questions in property testing, we search for linear error-correcting codes that have the “single local orbit” property: i.e., they are specified by a single loca...
Elena Grigorescu, Tali Kaufman, Madhu Sudan
ICML
2006
IEEE
16 years 7 months ago
Learning hierarchical task networks by observation
Knowledge-based planning methods offer benefits over classical techniques, but they are time consuming and costly to construct. There has been research on learning plan knowledge ...
Negin Nejati, Pat Langley, Tolga Könik
CGO
2009
IEEE
16 years 1 months ago
Automatic Feature Generation for Machine Learning Based Optimizing Compilation
Recent work has shown that machine learning can automate and in some cases outperform hand crafted compiler optimizations. Central to such an approach is that machine learning tec...
Hugh Leather, Edwin V. Bonilla, Michael O'Boyle
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