Abstract In many statistical problems, maximum likelihood estimation by an EM or MM algorithm suffers from excruciatingly slow convergence. This tendency limits the application of ...
Abstract. The starting point of this work is the definition of local pattern detection given in [10] as the unsupervised detection of local regions with anomalously high data densi...
For some problems, human assistance is needed in addition to automated (algorithmic) computation. In sharp contrast to existing data management approaches, where human input is ei...
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
Pre-processing algorithms improve the quality of a compression system by removing unimportant data before encoding. This enhances both the visual quality and coding efficiency of ...
C. Andrew Segall, Passant V. Karunaratne, Aggelos ...