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ICML
1999
IEEE
16 years 5 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
15 years 10 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
15 years 5 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»
15 years 1 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»
15 years 1 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