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ICML
2006
IEEE
14 years 9 months ago
An intrinsic reward mechanism for efficient exploration
How should a reinforcement learning agent act if its sole purpose is to efficiently learn an optimal policy for later use? In other words, how should it explore, to be able to exp...
Özgür Simsek, Andrew G. Barto
ECCV
2008
Springer
14 years 10 months ago
Feature Correspondence Via Graph Matching: Models and Global Optimization
Abstract. In this paper we present a new approach for establishing correspondences between sparse image features related by an unknown non-rigid mapping and corrupted by clutter an...
Lorenzo Torresani, Vladimir Kolmogorov, Carsten Ro...
SODA
2000
ACM
106views Algorithms» more  SODA 2000»
13 years 10 months ago
Algorithms for optimizing production DNA sequencing
We discuss the problem of optimally "finishing" a partially sequenced, reconstructed DNA segment. At first sight, this appears to be computationally hard. We construct a...
Éva Czabarka, Goran Konjevod, Madhav V. Mar...
CVPR
2011
IEEE
13 years 5 months ago
Using Global Bag of Features Models in Random Fields for Joint Categorization and Segmentation of Objects
We propose to bridge the gap between Random Field (RF) formulations for joint categorization and segmentation (JCaS), which model local interactions among pixels and superpixels, ...
Dheeraj Singaraju, René, Vidal
CIKM
2009
Springer
14 years 3 months ago
Incremental query evaluation for support vector machines
Support vector machines (SVMs) have been widely used in multimedia retrieval to learn a concept in order to find the best matches. In such a SVM active learning environment, the ...
Danzhou Liu, Kien A. Hua