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HRI
2007
ACM
15 years 3 months ago
Learning by demonstration with critique from a human teacher
Learning by demonstration can be a powerful and natural tool for developing robot control policies. That is, instead of tedious hand-coding, a robot may learn a control policy by ...
Brenna Argall, Brett Browning, Manuela M. Veloso
GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
15 years 3 months ago
On-line evolutionary computation for reinforcement learning in stochastic domains
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
Shimon Whiteson, Peter Stone
ICML
2007
IEEE
16 years 15 days ago
Robust multi-task learning with t-processes
Most current multi-task learning frameworks ignore the robustness issue, which means that the presence of "outlier" tasks may greatly reduce overall system performance. ...
Shipeng Yu, Volker Tresp, Kai Yu
ICML
2010
IEEE
15 years 23 days ago
OTL: A Framework of Online Transfer Learning
In this paper, we investigate a new machine learning framework called Online Transfer Learning (OTL) that aims to transfer knowledge from some source domain to an online learning ...
Peilin Zhao, Steven C. H. Hoi
ICTAI
2010
IEEE
14 years 9 months ago
A Semantic Similarity Language Model to Improve Automatic Image Annotation
In recent years, with the rapid proliferation of digital images, the need to search and retrieve the images accurately, efficiently, and conveniently is becoming more acute. Automa...
Tianxia Gong, Shimiao Li, Chew Lim Tan