Reinforcement Learning research is traditionally devoted to solve single-task problems. Therefore, anytime a new task is faced, learning must be restarted from scratch. Recently, ...
Mixed multi-unit combinatorial auctions are combinatorial auctions in which the auctioneer and the bidders negotiate over transformations rather than over simple goods. By proposi...
Grid-warping is a recent placement strategy based on a novel physical analogy: rather than move the gates to optimize their location, it elastically deforms a model of the 2-D chi...
The fused Lasso penalty enforces sparsity in both the coefficients and their successive differences, which is desirable for applications with features ordered in some meaningful w...
Pattern Databases were a major breakthrough in heuristic search by solving hard combinatorial problems various orders of magnitude faster than state-of-the-art techniques at that ...