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ICML
2003
IEEE
16 years 19 days ago
Relational Instance Based Regression for Relational Reinforcement Learning
Relational reinforcement learning (RRL) is a Q-learning technique which uses first order regression techniques to generalize the Qfunction. Both the relational setting and the Q-l...
Kurt Driessens, Jan Ramon
ALT
2008
Springer
15 years 8 months ago
Active Learning in Multi-armed Bandits
In this paper we consider the problem of actively learning the mean values of distributions associated with a finite number of options (arms). The algorithms can select which opti...
András Antos, Varun Grover, Csaba Szepesv&a...
KDD
1998
ACM
212views Data Mining» more  KDD 1998»
15 years 4 months ago
Learning to Predict Rare Events in Event Sequences
Learning to predict rare events from sequences of events with categorical features is an important, real-world, problem that existing statistical and machine learning methods are ...
Gary M. Weiss, Haym Hirsh
EMNLP
2007
15 years 1 months ago
Incremental Dependency Parsing Using Online Learning
We describe an incremental parser that was trained to minimize cost over sentences rather than over individual parsing actions. This is an attempt to use the advantages of the two...
Richard Johansson, Pierre Nugues
ICML
2007
IEEE
16 years 19 days ago
Approximate maximum margin algorithms with rules controlled by the number of mistakes
We present a family of incremental Perceptron-like algorithms (PLAs) with margin in which both the "effective" learning rate, defined as the ratio of the learning rate t...
Petroula Tsampouka, John Shawe-Taylor