Linear support vector machines (SVM) are useful for classifying large-scale sparse data. Problems with sparse features are common in applications such as document classification a...
Abstract: Polynomial computations over fixed-size bitvectors are found in many practical datapath designs. For efficient RTL synthesis, it is important to identify good decompositi...
Sivaram Gopalakrishnan, Priyank Kalla, M. Brandon ...
In this paper, we tackle the problem of localizing graphical symbols on complex technical document images by using an original approach to solve the subgraph isomorphism problem. ...
Matching Pursuit decomposes a signal into a linear expansion of functions selected from a redundant dictionary, isolating the signal structures that are coherent with respect to a...
Fulvio Moschetti, Lorenzo Granai, Pierre Vanderghe...
Learning Bayesian network structure from large-scale data sets, without any expertspecified ordering of variables, remains a difficult problem. We propose systematic improvements ...