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AI
2007
Springer
15 years 5 months ago
Learning action models from plan examples using weighted MAX-SAT
AI planning requires the definition of action models using a formal action and plan description language, such as the standard Planning Domain Definition Language (PDDL), as inp...
Qiang Yang, Kangheng Wu, Yunfei Jiang
188
Voted
AROBOTS
2008
158views more  AROBOTS 2008»
15 years 5 months ago
Learning traversability models for autonomous mobile vehicles
Autonomous mobile robots need to adapt their behavior to the terrain over which they drive, and to predict the traversability of the terrain so that they can effectively plan thei...
Michael Shneier, Tommy Chang, Tsai Hong, William P...
166
Voted
PAMI
2008
161views more  PAMI 2008»
15 years 4 months ago
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models
The Expectation Maximization (EM) algorithm is widely used for learning finite mixture models despite its greedy nature. Most popular model-based clustering techniques might yield...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...
ICIP
2009
IEEE
16 years 6 months ago
Learning Local Models For 2d Human Motion Tracking
We present a novel approach to tracking 2D human motion in uncalibrated monocular videos. Human motion usually exhibits timevarying patterns, and we propose to use locally learnt ...
ICRA
2008
IEEE
124views Robotics» more  ICRA 2008»
15 years 11 months ago
Simultaneous learning of motion and sensor model parameters for mobile robots
— Motion and sensor models are crucial components in current algorithms for mobile robot localization and mapping. These models are typically provided and hand-tuned by a human o...
Teddy N. Yap Jr., Christian R. Shelton