[Corpora-List] EMNLP Workshop on Deep Learning for Low-resource NLP (DeepLo 2019) - CFP

Colin Cherry colin.a.cherry at gmail.com
Thu Jun 20 17:30:51 CEST 2019

EMNLP Workshop on Deep Learning for Low-resource NLP (DeepLo 2019) November 3/4, 2019, Hong Kong, China

www: https://sites.google.com/view/deeplo19 email: deeplo2019 at googlegroups.com

Key dates == Submission deadline: August 19, 2019 Notification of acceptance: September 16, 2019 Camera-ready papers due: September 30, 2019 Workshop Date: November 3 or 4, 2019

Deep Learning for Low-resource NLP == NLP is being revolutionized by deep learning with neural networks. However, deep learning requires large amounts of annotated data, and its advantage over traditional statistical methods typically diminishes when such data is not available. Even in high-resource languages, it can be difficult to find linguistically annotated data of sufficient size and quality to allow neural methods to excel. The workshop aims to bring together experts in deep learning and natural language processing whose research focuses on learning with scarce data. Specifically, it will provide attendees with an overview of existing approaches from various disciplines, and enable them to distill principles that can be more generally applicable. We will also discuss the main challenges arising in this setting and outline potential directions for future progress. The target audience consists of researchers and practitioners in related areas.

Topics of Interest: == Active learning Transfer learning Multi-task learning Few-shot learning Learning-to-Learn and Meta-Learning Semi-supervised learning Dual learning Unsupervised learning Bandit/Reinforcement learning to learn from weak/sparse supervision Domain adaptation Decipherment or zero-shot learning Language projections Universal representations and interlinguas Low resource structured prediction

Submission Guidelines: == Please submit your paper using START: https://www.softconf.com/emnlp2019/ws-DeepLo2019/ Submissions must be in PDF format, anonymized for review, written in English and follow the EMNLP 2019 formatting requirements, available here: https://www.emnlp-ijcnlp2019.org/calls/papers We strongly advise you use the LaTeX template files provided by EMNLP 2019.

Submissions consist of up to eight pages of content. There is no limit on the number of pages for references. There is no extra space for appendices. Accepted papers will be given one additional page for content.

Authors can also submit non-archival papers of up to eight pages of content. Non-archival papers will not be included in the proceedings. Thus, your work will retain the status of being unpublished and later submission at another venue (e.g., a journal) is not precluded. Likewise, you are free to re-present work that has been previously published elsewhere.

We anticipate most papers, both archival and non-archival, will be presented as posters and spotlight presentation, with only a few selected for contributed talks.

Tentative Program: == The program consists of 5 invited talks, spotlight presentations, contributed talks, and poster presentations of submitted papers.

Invited Talks: == Heng Ji (University of Illinois Urbana-Champaign) Barbara Plank (IT University of Copenhagen) Dan Roth (University of Pennsylvania) Kristina Toutanova (Google AI Language) Luke Zettlemoyer (University of Washington / Facebook AI Research)

Organizers: == Colin Cherry - Google Greg Durrett - University of Texas, Austin George Foster - Google Gholamreza (Reza) Haffari - Monash University Shahram Khadivi - eBay Nanyun Peng - University of Southern California Xiang Ren - University of Southern California Swabha Swayamdipta - Allen Institute of Artificial Intelligence -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type: text/html Size: 4176 bytes Desc: not available URL: <https://mailman.uib.no/public/corpora/attachments/20190620/c427c58f/attachment.txt>

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