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» Transfer of Learning for Complex Task Domains: a Demonstrati...
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OIR
2010
101views more  OIR 2010»
13 years 5 months ago
Supporting information access in e-learning by integrating digital libraries and ontology
Purpose – The purpose of this paper is to examine the integration of digital library (DL) technologies with ontology-based knowledge representation in providing semantic rich in...
Daqing He, Yefei Peng, Ming Mao, Dan Wu
GECCO
2009
Springer
13 years 11 months ago
NEAT in increasingly non-linear control situations
Evolution of neural networks, as implemented in NEAT, has proven itself successful on a variety of low-level control problems such as pole balancing and vehicle control. Nonethele...
Matthias J. Linhardt, Martin V. Butz
GECCO
2005
Springer
162views Optimization» more  GECCO 2005»
14 years 16 days ago
An autonomous explore/exploit strategy
In reinforcement learning problems it has been considered that neither exploitation nor exploration can be pursued exclusively without failing at the task. The optimal balance bet...
Alex McMahon, Dan Scott, William N. L. Browne
COLING
2010
13 years 2 months ago
Cross-Market Model Adaptation with Pairwise Preference Data for Web Search Ranking
Machine-learned ranking techniques automatically learn a complex document ranking function given training data. These techniques have demonstrated the effectiveness and flexibilit...
Jing Bai, Fernando Diaz, Yi Chang, Zhaohui Zheng, ...
NIPS
2003
13 years 8 months ago
Max-Margin Markov Networks
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
Benjamin Taskar, Carlos Guestrin, Daphne Koller