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» Predicting Chinese Abbreviations from Definitions: An Empiri...
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BMCBI
2008
165views more  BMCBI 2008»
13 years 5 months ago
Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics
Background: Mass spectrometry is a key technique in proteomics and can be used to analyze complex samples quickly. One key problem with the mass spectrometric analysis of peptides...
Wiebke Timm, Alexandra Scherbart, Sebastian Bö...
BMCBI
2010
108views more  BMCBI 2010»
13 years 5 months ago
Predicting changes in protein thermostability brought about by single- or multi-site mutations
Background: An important aspect of protein design is the ability to predict changes in protein thermostability arising from single- or multi-site mutations. Protein thermostabilit...
Jian Tian, Ningfeng Wu, Xiaoyu Chu, Yunliu Fan
NIPS
2004
13 years 6 months ago
A Temporal Kernel-Based Model for Tracking Hand Movements from Neural Activities
We devise and experiment with a dynamical kernel-based system for tracking hand movements from neural activity. The state of the system corresponds to the hand location, velocity,...
Lavi Shpigelman, Koby Crammer, Rony Paz, Eilon Vaa...
KDD
2004
ACM
117views Data Mining» more  KDD 2004»
14 years 5 months ago
Regularized multi--task learning
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Theodoros Evgeniou, Massimiliano Pontil
ESANN
2006
13 years 6 months ago
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...