We present SpeedBoost, a natural extension of functional gradient descent, for learning anytime predictors, which automatically trade computation time for predictive accuracy by s...
Both optimization and learning play important roles in a system for intelligent tasks. On one hand, we introduce three types of optimization tasks studied in the machine learning l...
Recent work has shown that machine learning can automate and in some cases outperform hand crafted compiler optimizations. Central to such an approach is that machine learning tec...
The molecular distance geometry problem can be formulated as the problem of finding an immersion in R3 of a given undirected, nonnegatively weighted graph G. In this paper, we di...
Carlile Lavor, Leo Liberti, Antonio Mucherino, Nel...
—We consider a scenario in which users share an access point and are mainly interested in VoIP applications. Each user is allowed to adapt to varying network conditions by choosi...