1 code implementation • 22 Mar 2017 • Marc Goessling
The estimator that is employed for each conditional is LogitBoost.
no code implementations • 16 Feb 2017 • Marc Goessling, Yali Amit
We present a new approach for learning compact and intuitive distributed representations with binary encoding.
no code implementations • 15 Nov 2015 • Marc Goessling, Yali Amit
We consider high-dimensional distribution estimation through autoregressive networks.
no code implementations • 30 Aug 2015 • Marc Goessling, Shan Kang
In this paper we introduce a novel family of decision lists consisting of highly interpretable models which can be learned efficiently in a greedy manner.
no code implementations • 11 Dec 2014 • Marc Goessling, Yali Amit
Learning compact and interpretable representations is a very natural task, which has not been solved satisfactorily even for simple binary datasets.
