The resource constraint project scheduling problem (RCPSP) is an NP-hard benchmark problem in scheduling which takes into account the limitation of resources’ availabilities in ...
It is investigated for which choice of a parameter q, denoting the number of contexts, the class of simple external contextual languages is iteratively learnable. On one hand, the ...
Leonor Becerra-Bonache, John Case, Sanjay Jain, Fr...
We give an algorithm for the on-line learning of permutations. The algorithm maintains its uncertainty about the target permutation as a doubly stochastic weight matrix, and makes...
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
In a trend that reflects the increasing demand for intelligent applications driven by business data, IBM today is building out a significant number of applications that leverage m...