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» Machine Learning by Function Decomposition
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JMLR
2010
135views more  JMLR 2010»
14 years 10 months ago
Bundle Methods for Regularized Risk Minimization
A wide variety of machine learning problems can be described as minimizing a regularized risk functional, with different algorithms using different notions of risk and differen...
Choon Hui Teo, S. V. N. Vishwanathan, Alex J. Smol...
IGARSS
2010
14 years 6 months ago
Calibrating probabilities for hyperspectral classification of rock types
This paper investigates the performance of machine learning methods for classifying rock types from hyperspectral data. The main objective is to test the impact on classification ...
Sildomar T. Monteiro, Richard J. Murphy
TOMS
1998
148views more  TOMS 1998»
14 years 11 months ago
PELLPACK: A Problem-Solving Environment for PDE-Based Applications on Multicomputer Platforms
This paper presents the software architecture and implementation of the problem solving environment (PSE) PELLPACK for modeling physical objects described by partial differential ...
Elias N. Houstis, John R. Rice, Sanjiva Weerawaran...
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JMLR
2008
230views more  JMLR 2008»
14 years 11 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...
ICMLA
2010
14 years 9 months ago
Semi-Supervised Anomaly Detection for EEG Waveforms Using Deep Belief Nets
Abstract--Clinical electroencephalography (EEG) is routinely used to monitor brain function in critically ill patients, and specific EEG waveforms are recognized by clinicians as s...
Drausin Wulsin, Justin Blanco, Ram Mani, Brian Lit...