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IJCAI
1997
15 years 8 months ago
Learning Topological Maps with Weak Local Odometric Information
cal maps provide a useful abstraction for robotic navigation and planning. Although stochastic mapscan theoreticallybe learned using the Baum-Welch algorithm,without strong prior ...
Hagit Shatkay, Leslie Pack Kaelbling
TNN
2010
176views Management» more  TNN 2010»
15 years 1 months ago
Sparse approximation through boosting for learning large scale kernel machines
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
Ping Sun, Xin Yao
CDC
2009
IEEE
138views Control Systems» more  CDC 2009»
15 years 4 months ago
Beyond local optimality: An improved approach to hybrid model learning
Abstract-- Local convergence is a limitation of many optimization approaches for multimodal functions. For hybrid model learning, this can mean a compromise in accuracy. We develop...
Stephanie Gil, Brian Williams
CSSE
2008
IEEE
15 years 8 months ago
JThreadSpy: A Tool for Improving the Effectiveness of Concurrent System Teaching and Learning
Both teaching and learning multithreaded ing are complex tasks, due to the abstraction of the concepts, the non-determinism of the scheduler, the impossibility of using classical s...
Giovanni Malnati, Caterina Maria Cuva, Claudia Bar...
ICRA
2008
IEEE
229views Robotics» more  ICRA 2008»
16 years 1 months ago
Learning of moving cast shadows for dynamic environments
Abstract— We propose a novel online framework for detecting moving shadows in video sequences using statistical learning techniques. In this framework, Support Vector Machines ar...
Ajay J. Joshi, Nikolaos Papanikolopoulos