93
Voted
PKDD
2015
Springer
9 years 11 months ago
2015
Springer
Abstract. Astrophysical experiments produce Big Data which need efficient and e↵ective data analytics. In this paper we present a general data analysis process which has been su...
93
Voted
PKDD
2015
Springer
9 years 11 months ago
2015
Springer
We present a general formulation of metric learning for co-embedding, where the goal is to relate objects from different sets. The framework allows metric learning to be applied to...
105
Voted
PKDD
2015
Springer
9 years 11 months ago
2015
Springer
Abstract. We introduce an adaptive output-sensitive Metropolis-Hastings algorithm for probabilistic models expressed as programs, Adaptive Lightweight Metropolis-Hastings (AdLMH). ...
95
Voted
PKDD
2015
Springer
9 years 11 months ago
2015
Springer
In standard supervised learning, each training instance is associated with an outcome from a corresponding output space (e.g., a class label in classification or a real number in ...