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ICLR 2017 Schedule Registration CfP Committee FAQ Sponsors Toulon Other Years 5th International Conference on Learning Representations Overview The performance of machine learning methods is heavily dependent on the choice of data representation (or features) on which they are applied. The rapidly developing field of representation learning is concerned with questions surrounding how we can best learn meaningful and useful representations of data. We take a broad view of the field and include topics such as deep learning and feature learning, metric learning, compositional modeling, structured prediction, reinforcement learning, and issues regarding large-scale learning and non-convex optimization. The range of domains to which these techniques apply is also very broad, from vision to speech recognition, text understanding, gaming, music, etc. A non-exhaustive list of relevant topics:

  • Unsupervised, semi-supervised, and supervised representation learning
  • Representation learning for planning and reinforcement learning
  • Metric learning and kernel learning
  • Sparse coding and dimensionality expansion
  • Hierarchical models
  • Optimization for representation learning
  • Learning representations of outputs or states
  • Implementation issues, parallelization, software platforms, hardware
  • Applications in vision, audio, speech, natural language processing, robotics, neuroscience, or any other field
    • The program will include keynote presentations from invited speakers, oral presentations, and posters. When April 24 - 26, 2017 Where Palais des Congrès Neptune, Toulon, France Schedule The current schedule is here . Registration To register, go here . Registration is now CLOSED!! Internet Here is the Wi-Fi information for the confrence: Network Name: palais-neptune Password: neptune83 Live Streaming We will be streaming the oral sessions to our Facebook page at https://www.facebook.com/iclr.cc Submission of Conference Track Papers OpenReview ICLR 2017 Conference Track Submission of Workshop Track Abstracts OpenReview ICLR 2017 Workshop Track Important Dates Conference Track Submission Deadline: 5:00pm Eastern Daylight Time (EDT), November 4th 5th, 2016 Review Period: until December 16nd, 2016 Rebuttal/discussion: December 17th, 2016 to January 20th, 2017 Decision Notification: February 6th, 2017 Workshop Track Submission Deadline: 5:00pm Eastern Daylight Time (EDT), February 17th, 2017 Discussion Period: until March 10th, 2017 Decision notification: March 17th, 2017 Transportation, Hotels and Tourist Attractions For more information, click here . ICLR Awards The recipient of the ICLR Best Paper Awards have been selected. See the schedule for the 3 selected papers. Also this year, ICLR Best Review Awards were also given to the authors of reviews that were found to be of particularly high quality by the area chairs. For the recipients (and the reviews!) see here . External Pages ICLR Facebook Page : Discussion, Forum, and Pictures ICLR 2017 on Twitter Computational and Biological Learning Society (CBLS) Contact The organizers can be contacted at iclr2017.programchairs@gmail.com

    Executive Summary

    This article provides an overview of the 5th International Conference on Learning Representations (ICLR 2017), which focuses on representation learning in machine learning. The conference features keynote presentations, oral presentations, and posters, and covers a broad range of topics, including deep learning, feature learning, and metric learning. The article outlines the conference schedule, registration details, and important dates for submission and decision notification. Additionally, it highlights the ICLR awards for best paper and best review, as well as external pages for discussion and social media. The conference aims to bring together researchers and practitioners to advance the field of representation learning and its applications.

    Key Points

    • ▸ The ICLR 2017 conference focuses on representation learning in machine learning
    • ▸ The conference covers a broad range of topics, including deep learning, feature learning, and metric learning
    • ▸ The conference features keynote presentations, oral presentations, and posters

    Merits

    Interdisciplinary Approach

    The conference brings together researchers and practitioners from various fields, including computer science, engineering, and neuroscience, to advance the field of representation learning.

    Demerits

    Limited Audience

    The conference appears to be geared towards researchers and practitioners in the field of machine learning, which may limit its audience and impact on broader society.

    Expert Commentary

    The ICLR 2017 conference is a significant event in the field of machine learning, bringing together researchers and practitioners to advance the field of representation learning. The conference covers a broad range of topics, including deep learning, feature learning, and metric learning, which is relevant to the broader field of artificial intelligence. However, the conference appears to be geared towards researchers and practitioners in the field, which may limit its audience and impact on broader society. Nevertheless, the conference may lead to the development of new machine learning algorithms and techniques that can be applied in various fields, and may inform policy decisions related to the development and deployment of artificial intelligence systems.

    Recommendations

    • ✓ The organizers of the conference should consider expanding the audience and impact of the conference by incorporating more practical and policy-oriented topics.
    • ✓ The conference should continue to focus on advancing the field of representation learning and its applications, while also exploring its broader implications for society.

    Sources

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