Learning temporal causal graph structures from multivariate time-series data reveals important dependency relationships between current observations and histories, and provides a ...
Yan Liu 0002, Alexandru Niculescu-Mizil, Aurelie C...
Background: Sequence-derived structural and physicochemical descriptors have frequently been used in machine learning prediction of protein functional families, thus there is a ne...
Serene A. K. Ong, Hong Huang Lin, Yu Zong Chen, Ze...
We consider the problem of learning a sparse multi-task regression, where the structure in the outputs can be represented as a tree with leaf nodes as outputs and internal nodes a...
Background: Predicting a protein's structural or functional class from its amino acid sequence or structure is a fundamental problem in computational biology. Recently, there...
Iain Melvin, Jason Weston, Christina S. Leslie, Wi...
Abstract-- Multicore microprocessors have been largely motivated by the diminishing returns in performance and the increased power consumption of single-threaded ILP microprocessor...
Matthew Curtis-Maury, Karan Singh, Sally A. McKee,...