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» Stochastic complexity in learning
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CVPR
2003
IEEE
16 years 8 months ago
An Efficient Approach to Learning Inhomogeneous Gibbs Model
Inhomogeneous Gibbs model (IGM) [4] is an effective maximum entropy model in characterizing complex highdimensional distributions. However, its training process is so slow that th...
Ziqiang Liu, Hong Chen, Heung-Yeung Shum
191
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CVPR
2003
IEEE
16 years 8 months ago
Learning Object Intrinsic Structure for Robust Visual Tracking
In this paper, a novel method to learn the intrinsic object structure for robust visual tracking is proposed. The basic assumption is that the parameterized object state lies on a...
Qiang Wang, Guangyou Xu, Haizhou Ai
ICML
2004
IEEE
16 years 7 months ago
Learning associative Markov networks
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
ALT
2002
Springer
16 years 3 months ago
Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning
We describe a new boosting algorithm that is the first such algorithm to be both smooth and adaptive. These two features make possible performance improvements for many learning ...
Dmitry Gavinsky
AIED
2009
Springer
16 years 1 months ago
MetaTutor: Analyzing Self-Regulated Learning in a Tutoring System for Biology
We report preliminary data of an initial laboratory study examining the effectiveness of self-regulated learning (SRL) training versus no training on learners’ ability to deploy ...
Roger Azevedo, Amy M. Witherspoon, Arthur C. Graes...