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» Generalizing over Several Learning Settings
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MLDM
2005
Springer
14 years 1 months ago
Linear Manifold Clustering
In this paper we describe a new cluster model which is based on the concept of linear manifolds. The method identifies subsets of the data which are embedded in arbitrary oriented...
Robert M. Haralick, Rave Harpaz
CIVR
2007
Springer
14 years 2 months ago
Semantics reinforcement and fusion learning for multimedia streams
Fusion of multimedia streams for enhanced performance is a critical problem for retrieval. However, fusion performance tends to easily overfit the hillclimb set used to learn fus...
Dhiraj Joshi, Milind R. Naphade, Apostol Natsev
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
13 years 11 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
SIGMOD
2007
ACM
125views Database» more  SIGMOD 2007»
14 years 8 months ago
Optimizing mpf queries: decision support and probabilistic inference
Managing uncertain data using probabilistic frameworks has attracted much interest lately in the database literature, and a central computational challenge is probabilistic infere...
Héctor Corrada Bravo, Raghu Ramakrishnan
EH
1999
IEEE
351views Hardware» more  EH 1999»
14 years 3 days ago
Evolvable Hardware or Learning Hardware? Induction of State Machines from Temporal Logic Constraints
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...