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ML
2002
ACM
220views Machine Learning» more  ML 2002»
13 years 9 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich
MT
2002
118views more  MT 2002»
13 years 9 months ago
Principles of Context-Based Machine Translation Evaluation
This article defines a Framework for Machine Translation Evaluation (FEMTI) which relates the quality model used to evaluate a machine translation system to the purpose and context...
Eduard H. Hovy, Margaret King, Andrei Popescu-Beli...
JUCS
2008
132views more  JUCS 2008»
13 years 9 months ago
Searching ... in a Web
: Search engines--"web dragons"--are the portals through which we access society's treasure trove of information. They do not publish the algorithms they use to sort...
Ian H. Witten
STTT
2010
122views more  STTT 2010»
13 years 8 months ago
Rodin: an open toolset for modelling and reasoning in Event-B
Event-B is a formal method for system-level modelling and analysis. Key features of Event-B are the use of set theory as a modelling notation, the use of ent to represent systems a...
Jean-Raymond Abrial, Michael J. Butler, Stefan Hal...
ICMLA
2009
13 years 7 months ago
Learning Probabilistic Structure Graphs for Classification and Detection of Object Structures
Abstract--This paper presents a novel and domainindependent approach for graph-based structure learning. The approach is based on solving the Maximum Common SubgraphIsomorphism pro...
Johannes Hartz