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ICDM
2007
IEEE
122views Data Mining» more  ICDM 2007»
15 years 7 months ago
Noise Modeling with Associative Corruption Rules
This paper presents an active learning approach to the problem of systematic noise inference and noise elimination, specifically the inference of Associated Corruption (AC) rules...
Yan Zhang, Xindong Wu
122
Voted
HRI
2010
ACM
15 years 6 months ago
Transparent active learning for robots
—This research aims to enable robots to learn from human teachers. Motivated by human social learning, we believe that a transparent learning process can help guide the human tea...
Crystal Chao, Maya Cakmak, Andrea Lockerd Thomaz
MLDM
2005
Springer
15 years 7 months ago
Supervised Evaluation of Dataset Partitions: Advantages and Practice
In the context of large databases, data preparation takes a greater importance : instances and explanatory attributes have to be carefully selected. In supervised learning, instanc...
Sylvain Ferrandiz, Marc Boullé
TMI
2010
182views more  TMI 2010»
14 years 12 months ago
A Bayesian Mixture Approach to Modeling Spatial Activation Patterns in Multisite fMRI Data
Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
Seyoung Kim, Padhraic Smyth, Hal S. Stern
ALT
2008
Springer
15 years 10 months ago
Learning with Temporary Memory
In the inductive inference framework of learning in the limit, a variation of the bounded example memory (Bem) language learning model is considered. Intuitively, the new model con...
Steffen Lange, Samuel E. Moelius, Sandra Zilles