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» Learning with Globally Predictive Tests
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PROMISE
2010
14 years 4 months ago
On the value of learning from defect dense components for software defect prediction
BACKGROUND: Defect predictors learned from static code measures can isolate code modules with a higher than usual probability of defects. AIMS: To improve those learners by focusi...
Hongyu Zhang, Adam Nelson, Tim Menzies
COLT
2010
Springer
14 years 7 months ago
Quantum Predictive Learning and Communication Complexity with Single Input
We define a new model of quantum learning that we call Predictive Quantum (PQ). This is a quantum analogue of PAC, where during the testing phase the student is only required to a...
Dmitry Gavinsky
ECCV
2010
Springer
15 years 2 months ago
Learning What and How of Contextual Models for Scene Labeling
We present a data-driven approach to predict the importance of edges and construct a Markov network for image analysis based on statistical models of global and local image feature...
TON
2010
167views more  TON 2010»
14 years 4 months ago
A Machine Learning Approach to TCP Throughput Prediction
TCP throughput prediction is an important capability in wide area overlay and multi-homed networks where multiple paths may exist between data sources and receivers. In this paper...
Mariyam Mirza, Joel Sommers, Paul Barford, Xiaojin...
LION
2009
Springer
135views Optimization» more  LION 2009»
15 years 4 months ago
Neural Network Pairwise Interaction Fields for Protein Model Quality Assessment
We present a new knowledge-based Model Quality Assessment Program (MQAP) at the residue level which evaluates single protein structure models. We use a tree representation of the ...
Alberto J. M. Martin, Alessandro Vullo, Gianluca P...