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» On-line Algorithms in Machine Learning
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146
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ICML
2005
IEEE
16 years 4 months ago
Exploration and apprenticeship learning in reinforcement learning
We consider reinforcement learning in systems with unknown dynamics. Algorithms such as E3 (Kearns and Singh, 2002) learn near-optimal policies by using "exploration policies...
Pieter Abbeel, Andrew Y. Ng
139
Voted
MLCW
2005
Springer
15 years 9 months ago
Learning Textual Entailment on a Distance Feature Space
Textual Entailment recognition is a very difficult task as it is one of the fundamental problems in any semantic theory of natural language. As in many other NLP tasks, Machine Lea...
Maria Teresa Pazienza, Marco Pennacchiotti, Fabio ...
116
Voted
GECCO
2007
Springer
148views Optimization» more  GECCO 2007»
15 years 10 months ago
Fuzzy-UCS: preliminary results
This paper presents Fuzzy-UCS, a Michigan-style Learning Fuzzy-Classifier System designed for supervised learning tasks. Fuzzy-UCS combines the generalization capabilities of UCS...
Albert Orriols-Puig, Jorge Casillas, Ester Bernad&...
ICML
2007
IEEE
16 years 4 months ago
Simpler core vector machines with enclosing balls
The core vector machine (CVM) is a recent approach for scaling up kernel methods based on the notion of minimum enclosing ball (MEB). Though conceptually simple, an efficient impl...
András Kocsor, Ivor W. Tsang, James T. Kwok
126
Voted
ECML
2006
Springer
15 years 7 months ago
An Efficient Approximation to Lookahead in Relational Learners
Abstract. Greedy machine learning algorithms suffer from shortsightedness, potentially returning suboptimal models due to limited exploration of the search space. Greedy search mis...
Jan Struyf, Jesse Davis, C. David Page Jr.