31 citations · 31 across the 4 of their papers we have counts for
3 papers · 1 filter
Learning Abstract Task Representations
Mikhail M. Meskhi, Adriano Rivolli, Rafael G. Mantovani +1
A proper form of data characterization can guide the process of learning-algorithm selection and model-performance estimation. The field of meta-learning has provided a rich body o…
A General Approach to Domain Adaptation with Applications in Astronomy
Ricardo Vilalta, Kinjal Dhar Gupta, Dainis Boumber +1
The ability to build a model on a source task and subsequently adapt such model on a new target task is a pervasive need in many astronomical applications. The problem is generally…
Conceptual Domain Adaptation Using Deep Learning
Behrang Mehrparvar, Ricardo Vilalta
Deep learning has recently been shown to be instrumental in the problem of domain adaptation, where the goal is to learn a model on a target domain using a similar --but not identi…