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» Learning Algorithms for Domain Adaptation
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IJCAI
2001
15 years 4 months ago
Exploiting Multiple Secondary Reinforcers in Policy Gradient Reinforcement Learning
Most formulations of Reinforcement Learning depend on a single reinforcement reward value to guide the search for the optimal policy solution. If observation of this reward is rar...
Gregory Z. Grudic, Lyle H. Ungar
ICCS
2007
Springer
15 years 9 months ago
Adaptive Observation Strategies for Forecast Error Minimization
Abstract. Using a scenario of multiple mobile observing platforms (UAVs) measuring weather variables in distributed regions of the Pacific, we are developing algorithms that will ...
Nicholas Roy, Han-Lim Choi, Daniel Gombos, James H...
ATAL
2004
Springer
15 years 8 months ago
Decentralized Language Learning through Acting
This paper presents an algorithm for learning the meaning of messages communicated between agents that interact while acting optimally towards a cooperative goal. Our reinforcemen...
Claudia V. Goldman, Martin Allen, Shlomo Zilberste...
NN
2006
Springer
114views Neural Networks» more  NN 2006»
15 years 3 months ago
Modular learning models in forecasting natural phenomena
Modular model is a particular type of committee machine and is comprised of a set of specialized (local) models each of which is responsible for a particular region of the input s...
Dimitri P. Solomatine, Michael Baskara L. A. Siek
WOSP
1998
ACM
15 years 7 months ago
Poems: end-to-end performance design of large parallel adaptive computational systems
The POEMS project is creating an environment for end-to-end performance modeling of complex parallel and distributed systems, spanning the domains of application software, runti...
Ewa Deelman, Aditya Dube, Adolfy Hoisie, Yong Luo,...