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CVPR
2009
IEEE
17 years 1 months ago
Learning Visual Flows: A Lie Algebraic Approach
We present a novel method for modeling dynamic visual phenomena, which consists of two key aspects. First, the in- tegral motion of constituent elements in a dynamic scene is ca...
Dahua Lin, W. Eric L. Grimson, John W. Fisher III
ICML
2009
IEEE
16 years 7 months ago
Trajectory prediction: learning to map situations to robot trajectories
Trajectory planning and optimization is a fundamental problem in articulated robotics. Algorithms used typically for this problem compute optimal trajectories from scratch in a ne...
Nikolay Jetchev, Marc Toussaint
ICCV
2007
IEEE
16 years 1 months ago
Shape Priors using Manifold Learning Techniques
We introduce a non-linear shape prior for the deformable model framework that we learn from a set of shape samples using recent manifold learning techniques. We model a category o...
Patrick Etyngier, Florent Ségonne, Renaud K...
ILP
2007
Springer
16 years 28 days ago
Structural Statistical Software Testing with Active Learning in a Graph
Structural Statistical Software Testing (SSST) exploits the control flow graph of the program being tested to construct test cases. Specifically, SSST exploits the feasible paths...
Nicolas Baskiotis, Michèle Sebag
COLT
2005
Springer
16 years 9 days ago
A PAC-Style Model for Learning from Labeled and Unlabeled Data
Abstract. There has been growing interest in practice in using unlabeled data together with labeled data in machine learning, and a number of different approaches have been develo...
Maria-Florina Balcan, Avrim Blum