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ICML
1994
IEEE
15 years 7 months ago
A Modular Q-Learning Architecture for Manipulator Task Decomposition
Compositional Q-Learning (CQ-L) (Singh 1992) is a modular approach to learning to performcomposite tasks made up of several elemental tasks by reinforcement learning. Skills acqui...
Chen K. Tham, Richard W. Prager
LREC
2008
139views Education» more  LREC 2008»
15 years 5 months ago
Identification of Comparable Argument-Head Relations in Parallel Corpora
We present the machine learning framework that we are developing, in order to support explorative search for non-trivial linguistic configurations in low-density languages (langua...
Kathrin Spreyer, Jonas Kuhn, Bettina Schrader
ECML
2003
Springer
15 years 9 months ago
Logistic Model Trees
Abstract. Tree induction methods and linear models are popular techniques for supervised learning tasks, both for the prediction of nominal classes and continuous numeric values. F...
Niels Landwehr, Mark Hall, Eibe Frank
143
Voted
CVPR
2008
IEEE
16 years 5 months ago
Max Margin AND/OR Graph learning for parsing the human body
We present a novel structure learning method, Max Margin AND/OR Graph (MM-AOG), for parsing the human body into parts and recovering their poses. Our method represents the human b...
Long Zhu, Yuanhao Chen, Yifei Lu, Chenxi Lin, Alan...
GECCO
2004
Springer
110views Optimization» more  GECCO 2004»
15 years 9 months ago
Using GP to Model Contextual Human Behavior
To create a realistic environment, some simulations require simulated agents with human behavior pattern. Creating such agents with realistic behavior can be a tedious and time con...
Hans Fernlund, Avelino J. Gonzalez