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» Improved Approximation Algorithms for Label Cover Problems
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AAAI
2012
13 years 5 months ago
Transfer Learning with Graph Co-Regularization
Transfer learning proves to be effective for leveraging labeled data in the source domain to build an accurate classifier in the target domain. The basic assumption behind transf...
Mingsheng Long, Jianmin Wang 0001, Guiguang Ding, ...
IROS
2008
IEEE
203views Robotics» more  IROS 2008»
15 years 9 months ago
Learning equivalent action choices from demonstration
Abstract— In their interactions with the world robots inevitably face equivalent action choices, situations in which multiple actions are equivalently applicable. In this paper, ...
Sonia Chernova, Manuela M. Veloso
ATAL
2011
Springer
14 years 2 months ago
Quality-bounded solutions for finite Bayesian Stackelberg games: scaling up
The fastest known algorithm for solving General Bayesian Stackelberg games with a finite set of follower (adversary) types have seen direct practical use at the LAX airport for o...
Manish Jain, Christopher Kiekintveld, Milind Tambe
ECML
2006
Springer
15 years 6 months ago
Active Learning with Irrelevant Examples
Abstract. Active learning algorithms attempt to accelerate the learning process by requesting labels for the most informative items first. In real-world problems, however, there ma...
Dominic Mazzoni, Kiri Wagstaff, Michael C. Burl
ICPR
2010
IEEE
15 years 9 months ago
Continuous Markov Random Field Optimization using Fusion Move Driven Markov Chain Monte Carlo Technique
Many vision applications have been formulated as Markov Random Field (MRF) problems. Although many of them are discrete labeling problems, continuous formulation often achieves gre...
Wonsik Kim (Seoul National University), Kyoung Mu ...