TPDL2017

International Conference on Theory and Practice of Digital Libraries, TPDL2017
18-⁠21 September 2017, Grand Hotel Palace, Thessaloniki, Greece
http://www.tpdl.eu/tpdl2017

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An extension to the deadline of TPDL2017 has been granted. Authors wishing to submit their work in TPDL2017 can do so until April 21 for the categories of full & short papers, demonstrations and posters. For more information, as well as the full Call for Papers, you may visit http://www.tpdl.eu/tpdl2017/call-for-papers/.

We remind that TPDL2017 proceedings will be published by Springer-Verlag in the Lecture Notes in Computer Science series (LNCS, ISSN 0302-9743). Therefore all submissions should conform to the respective formatting instructions. All contributions must be submitted in electronic format (PDF) via the conference’s submission page at https://easychair.org/conferences/?conf=tpdl2017.

Finally, the call for contributions in the Doctoral Consortium is still open. You may find more information at http://www.tpdl.eu/tpdl2017/call-for-doctoral-consortium/.

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SLSP 2017

5th INTERNATIONAL CONFERENCE ON STATISTICAL LANGUAGE AND SPEECH PROCESSING

SLSP 2017

Le Mans, France

October 23-25, 2017

Organized by:

Computer Science Lab (LIUM)
University of Le Mans

Research Group on Mathematical Linguistics (GRLMC)
Rovira i Virgili University

http://grammars.grlmc.com/SLSP2017/

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PhD/MS positions in Data Science Lab of Ryerson University

Data Science Lab, Industrial Engineering Department, Ryerson University is looking for candidates for PhD/MS studentship.

Engineering graduates with passion to develop careers in Data Science please apply at the earliest.

Requirements: Expertise in programming (C++/Java/Python), sound understanding of databases (SQL/NoSQL) and data mining (clustering, classification and AR Mining).

Send your resume with cover letter to ayse.bener[]ryerson.ca, can.kavaklioglu[]ryerson.ca

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Final call for papers: Conference on Logic and Machine Learning in Natural Language (LaML)

Conference on Logic and Machine Learning in Natural Language (LaML)

Conference dates: June 12-14, 2017

Venue: Wallenberg Conference Centre, University of Gothenburg

Organised by CLASP, University of Gothenburg

The past two decades have seen impressive progress in a variety of areas of AI, particularly NLP, through the application of machine learning methods to a wide range of tasks. With the intensive use of deep learning methods in recent years this work has produced significant improvements in the coverage and accuracy of NLP systems in such domains as speech recognition, topic identification, semantic interpretation, and image description generation.

While deep learning is opening up exciting new approaches to longstanding, difficult problems in computational linguistics, it also raises important foundational questions. Specifically, we do not have a clear formal understanding of why multi-level recursive deep neural networks achieve the success in learning and classification that they are delivering. It is also not obvious whether they should displace more traditional, logically driven methods, or be combined with them. Finally, we need to explore the extent, if any, to which both logical models and machine learning methods offer insights into the cognitive foundations of natural language.

The Conference on Logic and Machine Learning in Natural Language will address these questions and related issues. It will feature invited talks by leading researchers in both fields, and high level contributed papers selected through open competition and rigorous review. Our aim is to initiated a genuine dialogue between these two approaches, where they have traditionally remained separate and in competition.

The conference proceedings will be published online, with an ISSN, on the CLASP website. Authors will retain the copyright of their papers and be free to publish them elsewhere, with acknowledgement.

Registration is free and participation is open. We warmly invite everyone to attend.

Invited Speakers:

Marco Baroni, Trento
Alexander Clark, King’s College London
Devdatt Dubhashi, Chalmers
Katrin Erk, University of Texas, Austin
Joakim Nivre, Uppsala
Aarne Ranta, Gothenburg
Mehrnoosh Sadrzadeh, Queen Mary University of London
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WildML: AI, Deep Learning, NLP

Очень хороший блог про современное машинное обучение, хорошие подробные тюториалы с примерами кода, много про NLP.

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Web Science Summer School

Приглашаем Вас принять участие в международной летней школе Web Science Summer School, которая в этом году состоится в Петербурге с 1 по 8 июля. В рамках школы проведут занятия и лекции хорошо известные в области исследователи и руководители ведущих научных коллективов. Для магистрантов и аспирантов российских вузов открыта возможность льготного участия.

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An Overview of Python Deep Learning Frameworks

By Madison May, indico.

I recently stumbled across an old Data Science Stack Exchange answer of mine on the topic of the “Best Python library for neural networks”, and it struck me how much the Python deep learning ecosystem has evolved over the course of the past 2.5 years. The library I recommended in July 2014, pylearn2, is no longer actively developed or maintained, but a whole host of deep learning libraries have sprung up to take its place. Each has its own strengths and weaknesses.

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GATE summer school

The 10th GATE summer school will be held from 26-30 June 2017 at the
University of Sheffield, UK.
Registration is now open, and the early registration deadline is 1 May 2017.

More information and registration details at
https://gate.ac.uk/conferences/fig/fig10.html

The focus this year will again be on mining social media and news
content with GATE. Many of the hands on exercises will be focused on
analysing tweets, blogs, news, and other social media content.

This event will follow a similar format to that of the 2016 course,
with one track Monday to Thursday, and two parallel tracks on Friday,
all delivered by the GATE development team. The course is suitable for
both programmers with Java expertise and for non-programmers.

For enquiries, please contact gate-fig[å]sheffield.ac.uk.

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CAMRL2017: Workshop on Computational Approaches to Morphologically Rich Languages

With Apologies for cross-posting
Please see below for information and submission deadlines for Workshop on Computational Approaches to Morphologically Rich Languages (#CAMRL2017), to be held at the University of Leeds, 5th of July 2017.
The Workshop is organised by the Leeds University Kartvelian Studies group and it aims to bring together established specialists and postgraduate researchstudents working in the field of computational morphology and morphosyntax.

The Workshop will feature plenary talks by Jost Gippert (Goethe University of Frankfurt), Andrew Hardie (Lancaster University) and Marina Beridze (Ivane Javakshishvili Tbilisi State University), talks and poster sessions, and a training event by Andrew Hardie focusing on Morphosyntactic Annotation Schemata.

We welcome submissions of abstracts for oral and poster presentations. Anonymous abstracts should not exceed 800 words (12-point Times New Roman font, with single spacing and margins of at least 2.54cm/1 inch), including examples and references. Each abstract should be submitted both  as a .doc, .docx or .rtf file and as an unprotected PDF file via  s.daraselia[a]leeds.ac.uk.

Deadline for abstract submission is March 31st 2017.

Please click on the link below for further details:

https://conferences.leeds.ac.uk/camrl/

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MA Computational Linguistics at the University of Wolverhampton

The Research Institute of Information and Language Processing at the University of Wolverhampton is pleased to announce its one-year MA programme in Computational Linguistics, starting in September 2017. The programme is interdisciplinary, and offers the following modules:

Python Programming
Corpus Linguistics with the R programming language
Machine Translation and other Natural Language Processing applications
Computational Linguistics
Machine Learning
Research Methods and Professional Skills
Project and Dissertation.

For further information, contact Dr. Michael Oakes (Course Leader) — Michael.Oakes[å]wlv.ac.uk or Mrs. April Harper (Course Administrator) — A.Harper2[å]wlv.ac.uk
The application link on our University website is — http://courses.wlv.ac.uk/course.asp?code=WL050P31UVD

Our Research Group page is — http://rgcl.wlv.ac.uk/compling/

Twitter: @RGCL_WLV

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