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COLT
2005
Springer
15 years 8 months ago
Variations on U-Shaped Learning
The paper deals with the following problem: is returning to wrong conjectures necessary to achieve full power of algorithmic learning? Returning to wrong conjectures complements t...
Lorenzo Carlucci, Sanjay Jain, Efim B. Kinber, Fra...
98
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ICML
2005
IEEE
16 years 4 months ago
Variational Bayesian image modelling
We present a variational Bayesian framework for performing inference, density estimation and model selection in a special class of graphical models--Hidden Markov Random Fields (H...
Li Cheng, Feng Jiao, Dale Schuurmans, Shaojun Wang
ICCV
2011
IEEE
14 years 3 months ago
Robust Object Pose Estimation via Statistical Manifold Modeling
We propose a novel statistical manifold modeling approach that is capable of classifying poses of object categories from video sequences by simultaneously minimizing the intra-cla...
Liang Mei, Jingen Liu, Alfred Hero, Silvio Savares...
FLAIRS
2004
15 years 4 months ago
Developing Task Specific Sensing Strategies Using Reinforcement Learning
Robots that can adapt and perform multiple tasks promise to be a powerful tool with many applications. In order to achieve such robots, control systems have to be constructed that...
Srividhya Rajendran, Manfred Huber
COLT
2006
Springer
15 years 7 months ago
Efficient Learning Algorithms Yield Circuit Lower Bounds
We describe a new approach for understanding the difficulty of designing efficient learning algorithms. We prove that the existence of an efficient learning algorithm for a circui...
Lance Fortnow, Adam R. Klivans