- We propose a novel framework for imitation learning that helps a humanoid robot achieve its goal of learning. There are apparent discrepancies in shapes and sizes among humans an...
Woosung Yang, Nak Young Chong, ChangHwan Kim, Bum-...
This paper presents the dynamics of multiple learning agents from an evolutionary game theoretic perspective. We provide replicator dynamics models for cooperative coevolutionary ...
Abstract. We establish a generic theoretical tool to construct probabilistic bounds for algorithms where the output is a subset of objects from an initial pool of candidates (or mo...
Background: Many researchers are concerned with the comparability and reliability of microarray gene expression data. Recent completion of the MicroArray Quality Control (MAQC) pr...
James J. Chen, Huey-miin Hsueh, Robert R. Delongch...
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...