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ML
2002
ACM
220views Machine Learning» more  ML 2002»
13 years 7 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
PPSN
2010
Springer
13 years 6 months ago
Optimisation and Generalisation: Footprints in Instance Space
Abstract. The chief purpose of research in optimisation is to understand how to design (or choose) the most suitable algorithm for a given distribution of problem instances. Ideall...
David W. Corne, Alan P. Reynolds
TASLP
2011
13 years 3 months ago
Estimating Dominance in Multi-Party Meetings Using Speaker Diarization
—With the increase in cheap commercially available sensors, recording meetings is becoming an increasingly practical option. With this trend comes the need to summarize the recor...
Hayley Hung, Yan Huang, Gerald Friedland, Daniel G...
COLT
1997
Springer
14 years 11 days ago
On-line Learning and the Metrical Task System Problem
We relate two problems that have been explored in two distinct communities. The first is the problem of combining expert advice, studied extensively in the computational learning...
Avrim Blum, Carl Burch
WSC
1998
13 years 9 months ago
ExpertFit: Total Support for Simulation Input Modeling
In this paper, we discuss the critical role of simulation input modeling in a successful simulation study. Two pitfalls in simulation input modeling are then presented and we expl...
Averill M. Law, Michael G. McComas