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ICML
2007
IEEE
16 years 7 months ago
Simple, robust, scalable semi-supervised learning via expectation regularization
Although semi-supervised learning has been an active area of research, its use in deployed applications is still relatively rare because the methods are often difficult to impleme...
Gideon S. Mann, Andrew McCallum
ICML
2001
IEEE
16 years 7 months ago
Continuous-Time Hierarchical Reinforcement Learning
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
Mohammad Ghavamzadeh, Sridhar Mahadevan
ICANN
2009
Springer
15 years 11 months ago
Learning SVMs from Sloppily Labeled Data
This paper proposes a modelling of Support Vector Machine (SVM) learning to address the problem of learning with sloppy labels. In binary classification, learning with sloppy labe...
Guillaume Stempfel, Liva Ralaivola
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
16 years 6 months ago
Query chains: learning to rank from implicit feedback
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
Filip Radlinski, Thorsten Joachims
VL
2009
IEEE
126views Visual Languages» more  VL 2009»
16 years 1 months ago
Predicting reuse of end-user web macro scripts
Repositories of code written by end-user programmers are beginning to emerge, but when a piece of code is new or nobody has yet reused it, then current repositories provide users ...
Christopher Scaffidi, Christopher Bogart, Margaret...