We propose an ℓ1 criterion for dictionary learning for sparse signal representation. Instead of directly searching for the dictionary vectors, our dictionary learning approach i...
Learning processes allow the central nervous system to learn relationships between stimuli. Even stimuli from different modalities can easily be associated, and these associations ...
Matthew Cook, Florian Jug, Christoph Krautz, Angel...
In this paper, we investigate a new machine learning framework called Online Transfer Learning (OTL) that aims to transfer knowledge from some source domain to an online learning ...
Predictive toxicology is the task of building models capable of determining, with a certain degree of accuracy, the toxicity of chemical compounds. Machine Learning (ML) in general...
This paper presents a method for learning a semantic parser from ambiguous supervision. Training data consists of natural language sentences annotated with multiple potential mean...