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AAAI
2011
14 years 6 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
GECCO
2004
Springer
107views Optimization» more  GECCO 2004»
16 years 4 days ago
Multiple Species Weighted Voting - A Genetics-Based Machine Learning System
Multiple Species Weighted Voting (MSWV) is a genetics-based machine learning (GBML) system with relatively few parameters that combines N two-class classifiers into an N -class cla...
Alexander F. Tulai, Franz Oppacher
AAAI
2010
15 years 8 months ago
Assisting Users with Clustering Tasks by Combining Metric Learning and Classification
Interactive clustering refers to situations in which a human labeler is willing to assist a learning algorithm in automatically clustering items. We present a related but somewhat...
Sumit Basu, Danyel Fisher, Steven M. Drucker, Hao ...
JMLR
2006
153views more  JMLR 2006»
15 years 6 months ago
Collaborative Multiagent Reinforcement Learning by Payoff Propagation
In this article we describe a set of scalable techniques for learning the behavior of a group of agents in a collaborative multiagent setting. As a basis we use the framework of c...
Jelle R. Kok, Nikos A. Vlassis
ICDM
2010
IEEE
226views Data Mining» more  ICDM 2010»
15 years 4 months ago
Edge Weight Regularization over Multiple Graphs for Similarity Learning
The growth of the web has directly influenced the increase in the availability of relational data. One of the key problems in mining such data is computing the similarity between o...
Pradeep Muthukrishnan, Dragomir R. Radev, Qiaozhu ...