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IJCV
2011
264views more  IJCV 2011»
13 years 13 days ago
Cost-Sensitive Active Visual Category Learning
Abstract We present an active learning framework that predicts the tradeoff between the effort and information gain associated with a candidate image annotation, thereby ranking un...
Sudheendra Vijayanarasimhan, Kristen Grauman
ML
2010
ACM
127views Machine Learning» more  ML 2010»
13 years 3 months ago
Stability and model selection in k-means clustering
Abstract Clustering Stability methods are a family of widely used model selection techniques for data clustering. Their unifying theme is that an appropriate model should result in...
Ohad Shamir, Naftali Tishby
SOCRATES
2008
100views Education» more  SOCRATES 2008»
13 years 6 months ago
Quality in eLearning. Some Results from a National Research Program
Quality is an open concept. Something has a good quality when the most salient of its characteristics have a positive value. What are this relevant features? It depends on the int...
Patrizia Ghislandi, Anna Pedroni, Daniela Paolino,...
ICML
2005
IEEE
14 years 6 months ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore
GECCO
2010
Springer
153views Optimization» more  GECCO 2010»
13 years 8 months ago
Multi-task evolutionary shaping without pre-specified representations
Shaping functions can be used in multi-task reinforcement learning (RL) to incorporate knowledge from previously experienced tasks to speed up learning on a new task. So far, rese...
Matthijs Snel, Shimon Whiteson