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» Evaluating learning algorithms and classifiers
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GECCO
2006
Springer
208views Optimization» more  GECCO 2006»
14 years 2 months ago
Comparing evolutionary and temporal difference methods in a reinforcement learning domain
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
SDM
2008
SIAM
176views Data Mining» more  SDM 2008»
14 years 6 days ago
A General Model for Multiple View Unsupervised Learning
Multiple view data, which have multiple representations from different feature spaces or graph spaces, arise in various data mining applications such as information retrieval, bio...
Bo Long, Philip S. Yu, Zhongfei (Mark) Zhang
SIGIR
2008
ACM
13 years 10 months ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 8 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
PRESENCE
2008
185views more  PRESENCE 2008»
13 years 10 months ago
Pilot Evaluation Study of a Virtual Paracentesis Simulator for Skill Training and Assessment: The Beneficial Effect of Haptic Di
Effective, real-time training of health care professionals in invasive procedures is a challenging task. Furthermore, assessing in practice the acquisition of the dexterity and sk...
Costas S. Tzafestas, Kostas Birbas, Yiannis Koumpo...