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126
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ICDM
2005
IEEE
163views Data Mining» more  ICDM 2005»
15 years 8 months ago
Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning
Active machine learning algorithms are used when large numbers of unlabeled examples are available and getting labels for them is costly (e.g. requiring consulting a human expert)...
Thomas Takeo Osugi, Kun Deng, Stephen D. Scott
142
Voted
ECML
2006
Springer
15 years 6 months ago
Multiple-Instance Learning Via Random Walk
This paper presents a decoupled two stage solution to the multiple-instance learning (MIL) problem. With a constructed affinity matrix to reflect the instance relations, a modified...
Dong Wang, Jianmin Li, Bo Zhang
123
Voted
AAAI
2010
15 years 4 months ago
A Restriction of Extended Resolution for Clause Learning SAT Solvers
Modern complete SAT solvers almost uniformly implement variations of the clause learning framework introduced by Grasp and Chaff. The success of these solvers has been theoretical...
Gilles Audemard, George Katsirelos, Laurent Simon
134
Voted
AOIS
2004
15 years 4 months ago
A Systematic Approach for Including Machine Learning in Multi-agent Systems
Large scale multi-agent systems (MASs) in unpredictable environments must use machine learning techniques to perform their goals and improve the performance of the system. This pap...
José Alberto R. P. Sardinha, Alessandro F. ...
138
Voted
ICML
2010
IEEE
15 years 3 months ago
A Conditional Random Field for Multiple-Instance Learning
We present MI-CRF, a conditional random field (CRF) model for multiple instance learning (MIL). MI-CRF models bags as nodes in a CRF with instances as their states. It combines di...
Thomas Deselaers, Vittorio Ferrari