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» Generation of Attributes for Learning Algorithms
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EUROCOLT
1999
Springer
14 years 1 months ago
Regularized Principal Manifolds
Many settings of unsupervised learning can be viewed as quantization problems — the minimization of the expected quantization error subject to some restrictions. This allows the ...
Alex J. Smola, Robert C. Williamson, Sebastian Mik...
AI
2010
Springer
13 years 7 months ago
Agent decision-making in open mixed networks
Computer systems increasingly carry out tasks in mixed networks, that is in group settings in which they interact both with other computer systems and with people. Participants in...
Ya'akov Gal, Barbara J. Grosz, Sarit Kraus, Avi Pf...
SIAMCOMP
1998
86views more  SIAMCOMP 1998»
13 years 9 months ago
Exact Learning of Discretized Geometric Concepts
We first present an algorithm that uses membership and equivalence queries to exactly identify a discretized geometric concept defined by the union of m axis-parallel boxes in d-...
Nader H. Bshouty, Paul W. Goldberg, Sally A. Goldm...
ICGI
2010
Springer
13 years 7 months ago
Learning PDFA with Asynchronous Transitions
In this paper we extend the PAC learning algorithm due to Clark and Thollard for learning distributions generated by PDFA to automata whose transitions may take varying time length...
Borja Balle, Jorge Castro, Ricard Gavaldà
SIGMOD
2007
ACM
181views Database» more  SIGMOD 2007»
14 years 9 months ago
Progressive and selective merge: computing top-k with ad-hoc ranking functions
The family of threshold algorithm (i.e., TA) has been widely studied for efficiently computing top-k queries. TA uses a sort-merge framework that assumes data lists are pre-sorted...
Dong Xin, Jiawei Han, Kevin Chen-Chuan Chang