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ICML
1999
IEEE
14 years 9 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox
COLT
2007
Springer
14 years 3 months ago
Property Testing: A Learning Theory Perspective
Property testing deals with tasks where the goal is to distinguish between the case that an object (e.g., function or graph) has a prespecified property (e.g., the function is li...
Dana Ron
ICML
2010
IEEE
13 years 10 months ago
Boosting Classifiers with Tightened L0-Relaxation Penalties
We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...
Noam Goldberg, Jonathan Eckstein
IOR
2010
128views more  IOR 2010»
13 years 6 months ago
Dynamic Assortment Optimization with a Multinomial Logit Choice Model and Capacity Constraint
The paper considers a stylized model of a dynamic assortment optimization problem, where given a limited capacity constraint, we must decide the assortment of products to offer to...
Paat Rusmevichientong, Zuo-Jun Max Shen, David B. ...
IJBRA
2010
133views more  IJBRA 2010»
13 years 6 months ago
Scalable biomedical Named Entity Recognition: investigation of a database-supported SVM approach
This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features and ...
Mona Soliman Habib, Jugal Kalita