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» An Algorithm for Learning Abductive Rules
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ICML
2010
IEEE
13 years 9 months ago
Nonparametric Return Distribution Approximation for Reinforcement Learning
Standard Reinforcement Learning (RL) aims to optimize decision-making rules in terms of the expected return. However, especially for risk-management purposes, other criteria such ...
Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashim...
GECCO
2004
Springer
107views Optimization» more  GECCO 2004»
14 years 1 months ago
Multiple Species Weighted Voting - A Genetics-Based Machine Learning System
Multiple Species Weighted Voting (MSWV) is a genetics-based machine learning (GBML) system with relatively few parameters that combines N two-class classifiers into an N -class cla...
Alexander F. Tulai, Franz Oppacher
ACL
2003
13 years 9 months ago
Learning to Predict Pitch Accents and Prosodic Boundaries in Dutch
We train a decision tree inducer (CART) and a memory-based classifier (MBL) on predicting prosodic pitch accents and breaks in Dutch text, on the basis of shallow, easy-to-comput...
Erwin Marsi, Martin Reynaert, Antal van den Bosch,...
IJCAI
2007
13 years 9 months ago
Some Effects of a Reduced Relational Vocabulary on the Whodunit Problem
A key issue in artificial intelligence lies in finding the amount of input detail needed to do successful learning. Too much detail causes overhead and makes learning prone to ove...
Daniel T. Halstead, Kenneth D. Forbus
JAIR
2007
113views more  JAIR 2007»
13 years 8 months ago
Chain: A Dynamic Double Auction Framework for Matching Patient Agents
In this paper we present and evaluate a general framework for the design of truthful auctions for matching agents in a dynamic, two-sided market. A single commodity, such as a res...
Jonathan Bredin, David C. Parkes, Quang Duong