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IUI
1999
ACM
14 years 1 months ago
Programming by Demonstration: An Inductive Learning Formulation
Although Programming by Demonstration (PBD) has the potential to improve the productivity of unsophisticated users, previous PBD systems have used brittle, heuristic, domain-speci...
Tessa A. Lau, Daniel S. Weld
CORR
2010
Springer
128views Education» more  CORR 2010»
13 years 9 months ago
Sublinear Optimization for Machine Learning
Abstract--We give sublinear-time approximation algorithms for some optimization problems arising in machine learning, such as training linear classifiers and finding minimum enclos...
Kenneth L. Clarkson, Elad Hazan, David P. Woodruff
JACIII
2006
97views more  JACIII 2006»
13 years 9 months ago
Opposition-Based Reinforcement Learning
In this paper a method for image segmentation using an opposition-based reinforcement learning scheme is introduced. We use this agent-based approach to optimally find the appropri...
Hamid R. Tizhoosh
DIS
2010
Springer
13 years 7 months ago
Speeding Up and Boosting Diverse Density Learning
Abstract. In multi-instance learning, each example is described by a bag of instances instead of a single feature vector. In this paper, we revisit the idea of performing multi-ins...
James R. Foulds, Eibe Frank
ICCV
1999
IEEE
14 years 1 months ago
A Subset Approach to Contour Tracking in Clutter
A new method for tracking contours of moving objects in clutter is presented. For a given object, a model of its contours is learned from training data in the form of a subset of ...
Daniel Freedman, Michael S. Brandstein