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AAAI
2012
8 years 25 days ago
Prediction and Fault Detection of Environmental Signals with Uncharacterised Faults
Many signals of interest are corrupted by faults of an unknown type. We propose an approach that uses Gaussian processes and a general “fault bucket” to capture a priori uncha...
Michael A. Osborne, Roman Garnett, Kevin Swersky, ...
CVPR
2012
IEEE
8 years 26 days ago
Complex loss optimization via dual decomposition
We describe a novel max-margin parameter learning approach for structured prediction problems under certain non-decomposable performance measures. Structured prediction is a commo...
Mani Ranjbar, Arash Vahdat, Greg Mori
ICMLA
2009
9 years 8 months ago
Structured Prediction with Relative Margin
In structured prediction problems, outputs are not confined to binary labels; they are often complex objects such as sequences, trees, or alignments. Support Vector Machine (SVM) ...
Pannagadatta K. Shivaswamy, Tony Jebara
JMLR
2008
230views more  JMLR 2008»
9 years 10 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
EUSFLAT
2003
9 years 11 months ago
Fuzzy models for prediction based on random set semantics
In this paper we propose a random set framework for learning linguistic models for prediction problems. We show how we can model prediction problems based on learning linguistic p...
Nicholas J. Randon, Jonathan Lawry
PAKDD
2009
ACM
233views Data Mining» more  PAKDD 2009»
10 years 3 months ago
A Kernel Framework for Protein Residue Annotation
Abstract. Over the last decade several prediction methods have been developed for determining structural and functional properties of individual protein residues using sequence and...
Huzefa Rangwala, Christopher Kauffman, George Kary...
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