This paper is concerned with a new task of ranking, referred to as "supplementary data assisted ranking", or "supplementary ranking" for short. Different from c...
We developed Gr?mlin 2.0, a new multiple network aligner with (1) a novel scoring function that can use arbitrary features of a multiple network alignment, such as protein deletion...
Jason Flannick, Antal F. Novak, Chuong B. Do, Bala...
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
The performance of a learning classifier system is due to its two main components. First, it evolves new structures by generating new rules in a genetic process; second, it adjust...
Multi-agent learning is a crucial method to control or find solutions for systems, in which more than one entity needs to be adaptive. In today's interconnected world, such s...