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IPM
2008
100views more  IPM 2008»
15 years 6 months ago
Query-level loss functions for information retrieval
Many machine learning technologies such as support vector machines, boosting, and neural networks have been applied to the ranking problem in information retrieval. However, since...
Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng W...
ICML
2004
IEEE
16 years 6 months ago
Adaptive cognitive orthotics: combining reinforcement learning and constraint-based temporal reasoning
Reminder systems support people with impaired prospective memory and/or executive function, by providing them with reminders of their functional daily activities. We integrate tem...
Matthew R. Rudary, Satinder P. Singh, Martha E. Po...
ML
1998
ACM
136views Machine Learning» more  ML 1998»
15 years 5 months ago
Co-Evolution in the Successful Learning of Backgammon Strategy
Following Tesauro’s work on TD-Gammon, we used a 4000 parameter feed-forward neural network to develop a competitive backgammon evaluation function. Play proceeds by a roll of t...
Jordan B. Pollack, Alan D. Blair
ICML
2006
IEEE
16 years 6 months ago
Relational temporal difference learning
We introduce relational temporal difference learning as an effective approach to solving multi-agent Markov decision problems with large state spaces. Our algorithm uses temporal ...
Nima Asgharbeygi, David J. Stracuzzi, Pat Langley
ICML
2007
IEEE
16 years 6 months ago
Trust region Newton methods for large-scale logistic regression
Large-scale logistic regression arises in many applications such as document classification and natural language processing. In this paper, we apply a trust region Newton method t...
Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi