Empirical studies on link blacklisting show that the delivery rate is very sensitive to the calibration of the blacklisting threshold. If the calibration is too restrictive (the th...
Flavio Fabbri, Marco Zuniga, Daniele Puccinelli, P...
We present SpeedBoost, a natural extension of functional gradient descent, for learning anytime predictors, which automatically trade computation time for predictive accuracy by s...
With energy consumption becoming one of the first-class optimization parameters in computer system design, compilation techniques that consider performance and energy simultaneous...
We present a decentralized market-based approach to resource allocation in a heterogeneous overlay network. The presented resource allocation strategy assigns overlay network reso...
Jay Smith, Edwin K. P. Chong, Anthony A. Maciejews...
This paper highlights the crucial role that modern machine learning techniques can play in the optimization of treatment strategies for patients with chronic disorders. In particu...
Arthur Guez, Robert D. Vincent, Massimo Avoli, Joe...