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» Problems of learning in multi-agent systems
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145
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CORR
2004
Springer
140views Education» more  CORR 2004»
15 years 4 months ago
Integrating Defeasible Argumentation and Machine Learning Techniques
The field of machine learning (ML) is concerned with the question of how to construct algorithms that automatically improve with experience. In recent years many successful ML app...
Sergio Alejandro Gómez, Carlos Iván ...
ICMLA
2009
15 years 2 months ago
Alive on Back-feed Culprit Identification via Machine Learning
We describe an application of machine learning techniques toward the problem of predicting which network protector switch is the cause of an Alive on Back-Feed (ABF) event in the ...
Bert C. Huang, Ansaf Salleb-Aouissi, Philip Gross
ICML
1998
IEEE
16 years 5 months ago
Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions
This paper introduces a new algorithm, Q2, foroptimizingthe expected output ofamultiinput noisy continuous function. Q2 is designed to need only a few experiments, it avoids stron...
Andrew W. Moore, Jeff G. Schneider, Justin A. Boya...
164
Voted
JMLR
2006
169views more  JMLR 2006»
15 years 5 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
CVPR
2009
IEEE
17 years 4 days ago
Learning Optimized MAP Estimates in Continuously-Valued MRF Models
We present a new approach for the discriminative training of continuous-valued Markov Random Field (MRF) model parameters. In our approach we train the MRF model by optimizing t...
Kegan G. G. Samuel, Marshall F. Tappen