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NLPRS
2001
Springer
15 years 6 months ago
A Separate-and-Learn Approach to EM Learning of PCFGs
WeproposeanewapproachtoEMlearning of PCFGs. We completely separate the process of EM learning from that of parsing, andfor theformer, weintroduce a new EM algorithm called the gra...
Taisuke Sato, Shigeru Abe, Yoshitaka Kameya, Kiyoa...
INCDM
2010
Springer
138views Data Mining» more  INCDM 2010»
15 years 6 days ago
Learning Discriminative Distance Functions for Case Retrieval and Decision Support
The importance of learning distance functions is gradually being acknowledged by the machine learning community, and different techniques are suggested that can successfully learn ...
Alexey Tsymbal, Martin Huber, Shaohua Kevin Zhou
ICRA
2008
IEEE
169views Robotics» more  ICRA 2008»
15 years 8 months ago
Sparse incremental learning for interactive robot control policy estimation
— We are interested in transferring control policies for arbitrary tasks from a human to a robot. Using interactive demonstration via teloperation as our transfer scenario, we ca...
Daniel H. Grollman, Odest Chadwicke Jenkins
ICMCS
2008
IEEE
207views Multimedia» more  ICMCS 2008»
15 years 8 months ago
Structure learning in a Bayesian network-based video indexing framework
Several stochastic models provide an effective framework to identify the temporal structure of audiovisual data. Most of them need as input a first video structure, i.e. connecti...
Siwar Baghdadi, Guillaume Gravier, Claire-Hé...
ICASSP
2011
IEEE
14 years 5 months ago
Sparse coding and dictionary learning based on the MDL principle
The power of sparse signal coding with learned overcomplete dictionaries has been demonstrated in a variety of applications and fields, from signal processing to statistical infe...
Ignacio Ramírez, Guillermo Sapiro