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» Using Problems to Learn Service-Oriented Computing
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139
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JMLR
2012
13 years 5 months ago
Structured Output Learning with High Order Loss Functions
Often when modeling structured domains, it is desirable to leverage information that is not naturally expressed as simply a label. Examples include knowledge about the evaluation ...
Daniel Tarlow, Richard S. Zemel
118
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ML
1998
ACM
101views Machine Learning» more  ML 1998»
15 years 2 months ago
Elevator Group Control Using Multiple Reinforcement Learning Agents
Recent algorithmic and theoretical advances in reinforcement learning (RL) have attracted widespread interest. RL algorithmshave appeared that approximatedynamic programming on an ...
Robert H. Crites, Andrew G. Barto
161
Voted
SDM
2009
SIAM
202views Data Mining» more  SDM 2009»
15 years 12 months ago
Proximity-Based Anomaly Detection Using Sparse Structure Learning.
We consider the task of performing anomaly detection in highly noisy multivariate data. In many applications involving real-valued time-series data, such as physical sensor data a...
Tsuyoshi Idé, Aurelie C. Lozano, Naoki Abe,...
ICRA
2006
IEEE
104views Robotics» more  ICRA 2006»
15 years 8 months ago
Implicit Coordination in Robotic Teams using Learned Prediction Models
— Many application tasks require the cooperation of two or more robots. Humans are good at cooperation in shared workspaces, because they anticipate and adapt to the intentions a...
Freek Stulp, Michael Isik, Michael Beetz
149
Voted
STACS
2010
Springer
15 years 7 months ago
A Dichotomy Theorem for the General Minimum Cost Homomorphism Problem
Abstract. In the constraint satisfaction problem (CSP), the aim is to find an assignment of values to a set of variables subject to specified constraints. In the minimum cost hom...
Rustem Takhanov