Transfer learning aims to solve new learning problems by extracting and making use of the common knowledge found in related domains. A key element of transfer learning is to ident...
Qiang Yang, Vincent Wenchen Zheng, Bin Li, Hankz H...
Exponential algorithms, i.e. algorithms of complexity O(cn ) for some c > 1, seem to be unavoidable in the case of NP-complete problems (unless P=NP), especially if the problem ...
This paper describes the result of our study on neural learning to solve the classification problems in which data is unbalanced and noisy. We conducted the study on three differen...
Generalized Belief Propagation (gbp) has proven to be a promising technique for performing inference on Markov random fields (mrfs). However, its heavy computational cost and large...
Case-Based Reasoning (CBR) is a methodology that reuses the solutions of previous similar problems to solve new problems. Adaptation is the most difficult stage in the CBR cycle, e...