Looking for sparsity is nowadays crucial to speed up the training of large-scale neural networks. Projections onto the \ell_{1} and \ell_{1,\propto} are among the most efficient techniques to sparsify and reduce the overall cost of neural networks. In this paper, we introduce a new projection algorithm for the \ell_{1,\infty} norm ball. Its worst-case time complexity is $\mathcal{O}(nm+J\log...Show More
In this paper, we propose a model to schedule the next 24 hours of operations in a bulk cargo port to unload bulk cargo trains onto stockpiles. It is a problem that includes multiple parts such as splitting long trains into shorter ones and the routing of bulk material through a configurable network of conveyors to the stockpiles. Managing such trains (up to three kilometers long) also requires sp...Show More
Heuristics are one of the most important tools to guide search to solve combinatorial problems. They are often specifically designed for one single problem and require both expertise and implementation work. Generic frameworks like SAT or CSP have developed heuristics that obey general principles like first fail or are able to learn and adapt from the exploration of the search tree like Dom/wDeg. ...Show More
