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» The Probabilistic Method
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JMLR
2002
115views more  JMLR 2002»
15 years 3 months ago
PAC-Bayesian Generalisation Error Bounds for Gaussian Process Classification
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
Matthias Seeger
128
Voted
RECOMB
2004
Springer
16 years 3 months ago
Using motion planning to study RNA folding kinetics
We propose a novel, motion planning based approach to approximately map the energy landscape of an RNA molecule. Our method is based on the successful probabilistic roadmap motion...
Xinyu Tang, Bonnie Kirkpatrick, Shawna L. Thomas, ...
162
Voted
KDD
2012
ACM
178views Data Mining» more  KDD 2012»
13 years 5 months ago
Mining event periodicity from incomplete observations
Advanced technology in GPS and sensors enables us to track physical events, such as human movements and facility usage. Periodicity analysis from the recorded data is an important...
Zhenhui Li, Jingjing Wang, Jiawei Han
116
Voted
KDD
2004
ACM
207views Data Mining» more  KDD 2004»
16 years 3 months ago
Belief state approaches to signaling alarms in surveillance systems
Surveillance systems have long been used to monitor industrial processes and are becoming increasingly popular in public health and anti-terrorism applications. Most early detecti...
Kaustav Das, Andrew W. Moore, Jeff G. Schneider
107
Voted
BERTINORO
2005
Springer
15 years 9 months ago
Prediction-Based Software Availability Enhancement
We propose a new paradigm for software availability enhancement. We offer a two-step strategy: Failure prediction followed by maintenance actions with the objective of avoiding imp...
Felix Salfner, Günther A. Hoffmann, Miroslaw ...