Computational social choice is an interdisciplinary eld of study at the interface of social choice theory and computer science, with knowledge owing in either direction. On the o...
In Sequential Viterbi Models, such as HMMs, MEMMs, and Linear Chain CRFs, the type of patterns over output sequences that can be learned by the model depend directly on the modelâ...
One approach to reduce the complexity of the task in the analysis of large scale genome-wide expression is to group the genes showing similar expression patterns into what are cal...
coarse procedures or very abstract frames from the point of view of algorithm, because some crucial issues like the representation, evolution, storage, and learning process of conc...
In this paper we eliminate the need for parameter estimation associated with the set covering machine (SCM) by directly minimizing generalization error bounds. Firstly, we consider...