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ADMA
2006
Springer
110views Data Mining» more  ADMA 2006»
15 years 8 months ago
Learning with Local Drift Detection
Abstract. Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
João Gama, Gladys Castillo
COLT
1995
Springer
15 years 8 months ago
Learning with Unreliable Boundary Queries
We introduce a new model for learning with membership queries in which queries near the boundary of a target concept may receive incorrect or “don’t care” responses. In part...
Avrim Blum, Prasad Chalasani, Sally A. Goldman, Do...
UAI
2008
15 years 6 months ago
Learning Arithmetic Circuits
Graphical models are usually learned without regard to the cost of doing inference with them. As a result, even if a good model is learned, it may perform poorly at prediction, be...
Daniel Lowd, Pedro Domingos
LEGE
2003
80views Education» more  LEGE 2003»
15 years 6 months ago
Theoretical Foundations for E-Learning Environments Direct to Virtual Scientific Experiments
In this work we want to put in evidence the necessity to integrate theoretical, methodological and didactical aspects with innovative e-learning systems, in order to hypothesize po...
PAMI
2010
249views more  PAMI 2010»
15 years 3 months ago
A Dynamic Texture-Based Approach to Recognition of Facial Actions and Their Temporal Models
—In this work we propose a dynamic-texture-based approach to the recognition of facial Action Units (AUs, atomic facial gestures) and their temporal models (i.e., sequences of te...
Sander Koelstra, Maja Pantic, Ioannis Patras