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TMI
2010
182views more  TMI 2010»
14 years 10 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
AAAI
2011
13 years 11 months ago
Quantity Makes Quality: Learning with Partial Views
In many real world applications, the number of examples to learn from is plentiful, but we can only obtain limited information on each individual example. We study the possibiliti...
Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, O...
NIPS
2004
15 years 1 months ago
Active Learning for Anomaly and Rare-Category Detection
We introduce a novel active-learning scenario in which a user wants to work with a learning algorithm to identify useful anomalies. These are distinguished from the traditional st...
Dan Pelleg, Andrew W. Moore
ICDE
2008
IEEE
137views Database» more  ICDE 2008»
16 years 1 months ago
Stop Chasing Trends: Discovering High Order Models in Evolving Data
Abstract-- Many applications are driven by evolving data -patterns in web traffic, program execution traces, network event logs, etc., are often non-stationary. Building prediction...
Shixi Chen, Haixun Wang, Shuigeng Zhou, Philip S. ...
PAMI
2006
136views more  PAMI 2006»
14 years 11 months ago
Data Driven Image Models through Continuous Joint Alignment
This paper presents a family of techniques that we call congealing for modeling image classes from data. The idea is to start with a set of images and make them appear as similar a...
Erik G. Learned-Miller