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IJCAI
1997
15 years 8 months ago
An Effective Learning Method for Max-Min Neural Networks
Max and min operations have interesting properties that facilitate the exchange of information between the symbolic and real-valued domains. As such, neural networks that employ m...
Loo-Nin Teow, Kia-Fock Loe
IJCAI
1989
15 years 8 months ago
Learning to Diagnose by Doing
This paper is a study on the process of evolution of a novice to an expert in a diagnostic context. In er, we have chosen an abstract example of a diagnostic problem. The results ...
Jayant Kalagnanam, Eswaran Subrahmanian
SLP
1989
105views more  SLP 1989»
15 years 8 months ago
Automatic Ordering of Subgoals - A Machine Learning Approach
This paper describes a learning system, LASSY1, which explores domains represented by Prolog databases, and use its acquired knowledge to increase the efficiency of a Prolog inter...
Shaul Markovitch, Paul D. Scott
NPL
2006
90views more  NPL 2006»
15 years 6 months ago
Hierarchical Incremental Class Learning with Reduced Pattern Training
Hierarchical Incremental Class Learning (HICL) is a new task decomposition method that addresses the pattern classification problem. HICL is proven to be a good classifier but clos...
Sheng Uei Guan, Chunyu Bao, Ru-Tian Sun
SIAMJO
2008
104views more  SIAMJO 2008»
15 years 6 months ago
A Minimax Theorem with Applications to Machine Learning, Signal Processing, and Finance
This paper concerns a fractional function of the form xT a/ xT Bx, where B is positive definite. We consider the game of choosing x from a convex set, to maximize the function, an...
Seung-Jean Kim, Stephen P. Boyd