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» A Machine Learning Approach to TCP Throughput Prediction
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ICML
2009
IEEE
15 years 10 months ago
Learning spectral graph transformations for link prediction
We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
Andreas Lommatzsch, Jérôme Kunegis
AAI
2008
93views more  AAI 2008»
14 years 9 months ago
Adaptive Machine Learning in Delayed Feedback Domains by Selective Relearning
We present a novel hybrid technique for improving the predictive performance of an online Machine Learning system: Combining advantages from both memory based and concept based pr...
Marcus-Christopher Ludl, Achim Lewandowski, Georg ...
ICML
2008
IEEE
15 years 10 months ago
Predicting diverse subsets using structural SVMs
In many retrieval tasks, one important goal involves retrieving a diverse set of results (e.g., documents covering a wide range of topics for a search query). First of all, this r...
Yisong Yue, Thorsten Joachims
GECCO
2008
Springer
135views Optimization» more  GECCO 2008»
14 years 10 months ago
Evolving sequence patterns for prediction of sub-cellular locations of eukaryotic proteins
A genetic algorithm (GA) is utilised to discover known and novel PROSITE-like sequence templates that can be used to classify the sub-cellular location of eukaryotic proteins. Whi...
Greg Paperin
ECML
2005
Springer
15 years 3 months ago
Error-Sensitive Grading for Model Combination
Abstract. Ensemble learning is a powerful learning approach that combines multiple classifiers to improve prediction accuracy. An important decision while using an ensemble of cla...
Surendra K. Singhi, Huan Liu