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» Learning Algorithms for Domain Adaptation
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108
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ICML
2010
IEEE
15 years 1 months ago
Inverse Optimal Control with Linearly-Solvable MDPs
We present new algorithms for inverse optimal control (or inverse reinforcement learning, IRL) within the framework of linearlysolvable MDPs (LMDPs). Unlike most prior IRL algorit...
Dvijotham Krishnamurthy, Emanuel Todorov
113
Voted
ICCV
1998
IEEE
16 years 2 months ago
Wormholes in Shape Space: Tracking Through Discontinuous Changes in Shape
Existing object tracking algorithms generally use some form of local optimisation, assuming that an object's position and shape change smoothly over time. In some situations ...
Tony Heap, David Hogg
94
Voted
ICRA
2008
IEEE
119views Robotics» more  ICRA 2008»
15 years 7 months ago
Maximum likelihood estimation of sensor and action model functions on a mobile robot
— In order for a mobile robot to accurately interpret its sensations and predict the effects of its actions, it must have accurate models of its sensors and actuators. These mode...
Daniel Stronger, Peter Stone
104
Voted
KDD
1998
ACM
112views Data Mining» more  KDD 1998»
15 years 4 months ago
Evaluating Usefulness for Dynamic Classification
This paper develops the concept of usefulness in the context of supervised learning. We argue that usefulness can be used to improve the performance of classification rules (as me...
Gholamreza Nakhaeizadeh, Charles Taylor, Carsten L...
82
Voted
COLT
2008
Springer
15 years 2 months ago
High-Probability Regret Bounds for Bandit Online Linear Optimization
We present a modification of the algorithm of Dani et al. [8] for the online linear optimization problem in the bandit setting, which with high probability has regret at most O ( ...
Peter L. Bartlett, Varsha Dani, Thomas P. Hayes, S...