Robust reasoning requires learning from problem solving episodes. Past experience must be compiled to provide adaptation to new contingencies and intelligent modification of solut...
Multi-label learning deals with data associated with multiple labels simultaneously. Previous work on multi-label learning assumes that for each instance, the "full" lab...
Various alternatives have been developed to improve the Winner-Takes-All (WTA) mechanism in vector quantization, including the Neural Gas (NG). However, the behavior of these algo...
Aree Witoelar, Michael Biehl, Anarta Ghosh, Barbar...
In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...