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NEUROSCIENCE
2001
Springer
15 years 8 months ago
Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
Doina Caragea, Adrian Silvescu, Vasant Honavar
127
Voted
CVPR
2009
IEEE
16 years 10 months ago
Let the Kernel Figure it Out; Principled Learning of Pre-processing for Kernel Classifiers
Most modern computer vision systems for high-level tasks, such as image classification, object recognition and segmentation, are based on learning algorithms that are able to se...
Peter V. Gehler, Sebastian Nowozin
125
Voted
ICML
1999
IEEE
16 years 4 months ago
Implicit Imitation in Multiagent Reinforcement Learning
Imitation is actively being studied as an effective means of learning in multi-agent environments. It allows an agent to learn how to act well (perhaps optimally) by passively obs...
Bob Price, Craig Boutilier
IUI
2009
ACM
16 years 10 days ago
From geek to sleek: integrating task learning tools to support end users in real-world applications
Numerous techniques exist to help users automate repetitive tasks; however, none of these methods fully support enduser creation, use, and modification of the learned tasks. We pr...
Aaron Spaulding, Jim Blythe, Will Haines, Melinda ...
136
Voted
KES
2005
Springer
15 years 9 months ago
User Preference Learning for Multimedia Personalization in Pervasive Computing Environment
Pervasive computing environment and users’ demand for multimedia personalization precipitate a need for personalization tools to help people access desired multimedia content at ...
Zhiwen Yu, Daqing Zhang, Xingshe Zhou, Changde Li