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» A Theory for Memory-Based Learning
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ECCV
2006
Springer
16 years 8 months ago
Conditional Infomax Learning: An Integrated Framework for Feature Extraction and Fusion
The paper introduces a new framework for feature learning in classification motivated by information theory. We first systematically study the information structure and present a n...
Dahua Lin, Xiaoou Tang
CHI
2009
ACM
16 years 6 months ago
Two studies of opportunistic programming: interleaving web foraging, learning, and writing code
This paper investigates the role of online resources in problem solving. We look specifically at how programmers--an exemplar form of knowledge workers--opportunistically interlea...
Joel Brandt, Philip J. Guo, Joel Lewenstein, Mira ...
KDD
2009
ACM
178views Data Mining» more  KDD 2009»
16 years 6 months ago
Constrained optimization for validation-guided conditional random field learning
Conditional random fields(CRFs) are a class of undirected graphical models which have been widely used for classifying and labeling sequence data. The training of CRFs is typicall...
Minmin Chen, Yixin Chen, Michael R. Brent, Aaron E...
ICAC
2006
IEEE
16 years 11 days ago
A Hybrid Reinforcement Learning Approach to Autonomic Resource Allocation
— Reinforcement Learning (RL) provides a promising new approach to systems performance management that differs radically from standard queuing-theoretic approaches making use of ...
Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mo...
MM
2006
ACM
203views Multimedia» more  MM 2006»
16 years 8 days ago
Learning image manifolds by semantic subspace projection
In many image retrieval applications, the mapping between highlevel semantic concept and low-level features is obtained through a learning process. Traditional approaches often as...
Jie Yu, Qi Tian