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AAAI
2008
15 years 9 months ago
Maximum Entropy Inverse Reinforcement Learning
Recent research has shown the benefit of framing problems of imitation learning as solutions to Markov Decision Problems. This approach reduces learning to the problem of recoveri...
Brian Ziebart, Andrew L. Maas, J. Andrew Bagnell, ...
AAAI
2010
15 years 6 months ago
Computing Cost-Optimal Definitely Discriminating Tests
The goal of testing is to discriminate between multiple hypotheses about a system--for example, different fault diagnoses--by applying input patterns and verifying or falsifying t...
Anika Schumann, Jinbo Huang, Martin Sachenbacher
ICWE
2005
Springer
16 years 5 days ago
Discovering Re-usable Design Solutions in Web Conceptual Schemas: Metrics and Methodology
Abstract. In the Internet era, the development of Web applications has impressively evolved and is characterized by a large degree of complexity. To this end, software community ha...
Yannis Panagis, Evangelos Sakkopoulos, Spiros Sirm...
184
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ACCV
2006
Springer
16 years 19 days ago
A Local Basis Representation for Estimating Human Pose from Cluttered Images
Recovering the pose of a person from single images is a challenging problem. This paper discusses a bottom-up approach that uses local image features to estimate human upper body p...
Ankur Agarwal, Bill Triggs
185
Voted
IBPRIA
2009
Springer
15 years 11 months ago
Inference and Learning for Active Sensing, Experimental Design and Control
In this paper we argue that maximum expected utility is a suitable framework for modeling a broad range of decision problems arising in pattern recognition and related fields. Exa...
Hendrik Kück, Matthew Hoffman, Arnaud Doucet,...