Many combinatorial problems arising in machine learning can be reduced to the problem of minimizing a submodular function. Submodular functions are a natural discrete analog of co...
Energy-based learning (EBL) is a general framework to describe supervised and unsupervised training methods for probabilistic and non-probabilistic factor graphs. An energy-based ...
In this paper, we explore a hybrid global/local search optimization framework for dynamic voltage scaling in embedded multiprocessor systems. The problem is to find, for a multipr...
Abstract—Protein structure prediction is the problem of finding the functional conformation of a protein given only its amino uence. The HP lattice model is an abstract formulat...
Mario Garza-Fabre, Eduardo Rodriguez-Tello, Gregor...
In this paper we introduce and study Shortest Path Discovery (SPD) problems, a generalization of shortest path problems: In SPD one is given a directed edgeweighted graph and the ...