Recent research advances on interactive machine learning

Recent Advances in Predictive (Machine) Learning

Prediction involves estimating the unknown value of an attribute of a system under study given the values of other measured attributes. In prediction (machine) learning the prediction rule is derived from data consisting of previously solved cases. Most methods for predictive learning were originated many years ago at the dawn of the computer age. Recently two new techniques have emerged that h...

Recent Advances in Conotoxin Classification by Using Machine Learning Methods.

Conotoxins are disulfide-rich small peptides, which are invaluable peptides that target ion channel and neuronal receptors. Conotoxins have been demonstrated as potent pharmaceuticals in the treatment of a series of diseases, such as Alzheimer's disease, Parkinson's disease, and epilepsy. In addition, conotoxins are also ideal molecular templates for the development of new drug lead compounds a...

Recent Advances in Machine Learning and Game Playing

Game-playing applications offer various challenges for machine learning, including opening book learning, learning of evaluation functions, player modeling, and others. In this paper, we briefly highlight the most important achievements of this field and summarize some important recent advance.

Recent Advances in BLV Research.

Different animal models have been proposed to investigate the mechanisms of Human T-lymphotropic Virus (HTLV)-induced pathogenesis: rats, transgenic and NOD-SCID/γcnull (NOG) mice, rabbits, squirrel monkeys, baboons and macaques. These systems indeed provide useful information but have intrinsic limitations such as lack of disease relevance, species specificity or inadequate immune response. An...

Recent Advances and Research Challenges