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ECML
2004
Springer
14 years 1 months ago
Batch Reinforcement Learning with State Importance
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
Lihong Li, Vadim Bulitko, Russell Greiner
NIPS
2007
13 years 9 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
ICML
2005
IEEE
14 years 8 months ago
Augmenting naive Bayes for ranking
Naive Bayes is an effective and efficient learning algorithm in classification. In many applications, however, an accurate ranking of instances based on the class probability is m...
Harry Zhang, Liangxiao Jiang, Jiang Su
CAV
2010
Springer
176views Hardware» more  CAV 2010»
13 years 10 months ago
Lazy Annotation for Program Testing and Verification
Abstract. We describe an interpolant-based approach to test generation and model checking for sequential programs. The method generates Floyd/Hoare style annotations of the program...
Kenneth L. McMillan
ICML
2004
IEEE
14 years 8 months ago
A spatio-temporal extension to Isomap nonlinear dimension reduction
We present an extension of Isomap nonlinear dimension reduction (Tenenbaum et al., 2000) for data with both spatial and temporal relationships. Our method, ST-Isomap, augments the...
Odest Chadwicke Jenkins, Maja J. Mataric