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Dive into the research topics where Karol Kurach is active.

Publication


Featured researches published by Karol Kurach.


knowledge discovery and data mining | 2016

Smart Reply: Automated Response Suggestion for Email

Anjuli Kannan; Karol Kurach; Sujith Ravi; Tobias Kaufmann; Andrew Tomkins; Balint Miklos; Greg Corrado; László Lukács; Marina Ganea; Peter Young; Vivek Ramavajjala

In this paper we propose and investigate a novel end-to-end method for automatically generating short email responses, called Smart Reply. It generates semantically diverse suggestions that can be used as complete email responses with just one tap on mobile. The system is currently used in Inbox by Gmail and is responsible for assisting with 10% of all mobile responses. It is designed to work at very high throughput and process hundreds of millions of messages daily. The system exploits state-of-the-art, large-scale deep learning. We describe the architecture of the system as well as the challenges that we faced while building it, like response diversity and scalability. We also introduce a new method for semantic clustering of user-generated content that requires only a modest amount of explicitly labeled data.


arXiv: Machine Learning | 2017

Adding Gradient Noise Improves Learning for Very Deep Networks

Arvind Neelakantan; Luke Vilnis; Quoc V. Le; Lukasz Kaiser; Karol Kurach; Ilya Sutskever; James Martens


international conference on learning representations | 2016

Neural Random-Access Machines

Karol Kurach; Marcin Andrychowicz; Ilya Sutskever


neural information processing systems | 2018

Are GANs Created Equal? A Large-Scale Study

Mario Lucic; Karol Kurach; Marcin Michalski; Sylvain Gelly; Olivier Bousquet


arXiv: Learning | 2017

Learning Efficient Algorithms with Hierarchical Attentive Memory

Marcin Andrychowicz; Karol Kurach


Archive | 2014

SYSTEMS AND METHODS FOR ESTIMATING MESSAGE SIMILARITY

Ivo Krka; Itamar Gilad; Karol Kurach; Andrew M. Dai; Liam MacDermed; Peter J. Liu; Balint Miklos; Alexandru Damian


arXiv: Learning | 2018

The GAN Landscape: Losses, Architectures, Regularization, and Normalization.

Karol Kurach; Mario Lucic; Xiaohua Zhai; Marcin Michalski; Sylvain Gelly


arXiv: Computation and Language | 2017

Better Text Understanding Through Image-To-Text Transfer

Karol Kurach; Sylvain Gelly; Michal Jastrzebski; Philip Haeusser; Olivier Teytaud; Damien Vincent; Olivier Bousquet


Ercim News | 2016

Neural Random Access Machines.

Karol Kurach; Marcin Andrychowicz; Ilya Sutskever


arXiv: Learning | 2018

MemGEN: Memory is All You Need.

Sylvain Gelly; Karol Kurach; Marcin Michalski; Xiaohua Zhai

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