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AII
1992
15 years 8 months ago
Learning from Multiple Sources of Inaccurate Data
Most theoretical models of inductive inference make the idealized assumption that the data available to a learner is from a single and accurate source. The subject of inaccuracies ...
Ganesh Baliga, Sanjay Jain, Arun Sharma
KDD
2007
ACM
276views Data Mining» more  KDD 2007»
16 years 4 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
GECCO
2006
Springer
198views Optimization» more  GECCO 2006»
15 years 8 months ago
Reward allotment in an event-driven hybrid learning classifier system for online soccer games
This paper describes our study into the concept of using rewards in a classifier system applied to the acquisition of decision-making algorithms for agents in a soccer game. Our a...
Yuji Sato, Yosuke Akatsuka, Takenori Nishizono
ALT
2003
Springer
15 years 8 months ago
Efficiently Learning the Metric with Side-Information
Abstract. A crucial problem in machine learning is to choose an appropriate representation of data, in a way that emphasizes the relations we are interested in. In many cases this ...
Tijl De Bie, Michinari Momma, Nello Cristianini
IUI
2009
ACM
16 years 1 months ago
Learning to generalize for complex selection tasks
Selection tasks are common in modern computer interfaces: we are often required to select a set of files, emails, data entries, and the like. File and data browsers have sorting a...
Alan Ritter, Sumit Basu