Learning from imbalanced datasets presents a convoluted problem both from the modeling and cost standpoints. In particular, when a class is of great interest but occurs relatively...
Nitesh V. Chawla, David A. Cieslak, Lawrence O. Ha...
In this paper, we investigate Reinforcement learning (RL) in multi-agent systems (MAS) from an evolutionary dynamical perspective. Typical for a MAS is that the environment is not ...
Karl Tuyls, Pieter Jan't Hoen, Bram Vanschoenwinke...
We present a new method, called UTAGMS , for multiple criteria ranking of alternatives from set A using a set of additive value functions which result from an ordinal regression. ...
Salvatore Greco, Vincent Mousseau, Roman Slowinski
Motivation: Most previous approaches to model biochemical networks havefocusedeither on the characterization of a networkstructurewith a number of components or on the estimation ...
Background: With the completion of the genome sequences of human, mouse, and other species and the advent of high throughput functional genomic research technologies such as biomi...
Peisen Zhang, Jinghui Zhang, Huitao Sheng, James J...