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NIPS
2008
15 years 4 months ago
Structure Learning in Human Sequential Decision-Making
We use graphical models and structure learning to explore how people learn policies in sequential decision making tasks. Studies of sequential decision-making in humans frequently...
Daniel Acuña, Paul R. Schrater
ICTAI
2009
IEEE
15 years 9 months ago
Learning for Dynamic Assignments Reordering
In this paper a new learning scheme for SAT is proposed. The originality of our approach arises from its ability to achieve clause learning even if no conflict occurs. This clear...
Saïd Jabbour
AAAI
2008
15 years 5 months ago
Instance-level Semisupervised Multiple Instance Learning
Multiple instance learning (MIL) is a branch of machine learning that attempts to learn information from bags of instances. Many real-world applications such as localized content-...
Yangqing Jia, Changshui Zhang
CVPR
2004
IEEE
15 years 6 months ago
Modeling Complex Motion by Tracking and Editing Hidden Markov Graphs
In this paper, we propose a generative model for representing complex motion, such as wavy river, dancing fire and dangling cloth. Our generative method consists of four component...
Yizhou Wang, Song Chun Zhu
MLQ
2011
14 years 10 months ago
Weak Borel chromatic numbers
Given a graph G whose set of vertices is a Polish space X, the weak Borel chromatic number of G is the least size of a family of pairwise disjoint G-independent Borel sets that cov...
Stefan Geschke