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ICGI
2004
Springer
16 years 4 days ago
Learning Stochastic Finite Automata
Abstract. Stochastic deterministic finite automata have been introduced and are used in a variety of settings. We report here a number of results concerning the learnability of th...
Colin de la Higuera, José Oncina
IROS
2008
IEEE
121views Robotics» more  IROS 2008»
16 years 1 months ago
Learning robot motion control with demonstration and advice-operators
Abstract— As robots become more commonplace within society, the need for tools to enable non-robotics-experts to develop control algorithms, or policies, will increase. Learning ...
Brenna Argall, Brett Browning, Manuela M. Veloso
ICML
2002
IEEE
16 years 7 months ago
Learning the Kernel Matrix with Semi-Definite Programming
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
CRV
2009
IEEE
115views Robotics» more  CRV 2009»
16 years 1 months ago
Learning Model Complexity in an Online Environment
In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification pro...
Dan Levi, Shimon Ullman
EOR
2007
165views more  EOR 2007»
15 years 6 months ago
Adaptive credit scoring with kernel learning methods
Credit scoring is a method of modelling potential risk of credit applications. Traditionally, logistic regression, linear regression and discriminant analysis are the most popular...
Yingxu Yang