no code implementations • 12 Jun 2018 • Artem Sokolov, Julian Hitschler, Mayumi Ohta, Stefan Riezler
Stochastic zeroth-order (SZO), or gradient-free, optimization allows to optimize arbitrary functions by relying only on function evaluations under parameter perturbations, however, the iteration complexity of SZO methods suffers a factor proportional to the dimensionality of the perturbed function.
no code implementations • WS 2017 • Julian Hitschler, Esther van den Berg, Ines Rehbein
We use a convolutional neural network to perform authorship identification on a very homogeneous dataset of scientific publications.
4 code implementations • EACL 2017 • Rico Sennrich, Orhan Firat, Kyunghyun Cho, Alexandra Birch, Barry Haddow, Julian Hitschler, Marcin Junczys-Dowmunt, Samuel Läubli, Antonio Valerio Miceli Barone, Jozef Mokry, Maria Nădejde
We present Nematus, a toolkit for Neural Machine Translation.
no code implementations • ACL 2016 • Julian Hitschler, Shigehiko Schamoni, Stefan Riezler
We present an approach to improve statistical machine translation of image descriptions by multimodal pivots defined in visual space.