posted by user: wslmm2013 || 4645 views || tracked by 13 users: [display]

AAAI WSLMM 2013 : AAAI 2013 Spring Symposium on Weakly Supervised Learning from Multimedia


When Mar 25, 2013 - Mar 27, 2013
Where Stanford, CA
Submission Deadline Oct 5, 2012
Notification Due Nov 2, 2012
Final Version Due Jan 18, 2013
Categories    machine learning   artificial intelligence   computer vision   multimedia

Call For Papers

What can computers learn about the real world from large quantities of audio-visual data, with minimal human supervision? While weakly supervised learning has been an active research topic in the natural language community, learning from large multimedia collections (and video in particular) is a field that is still in its infancy. Early efforts in this direction include learning models of objects and actions from internet video, humans in images and localizing sounds in audio.

* Scaling weakly supervised learning to very large collections (e.g., internet video);
* Features and representations;
* Weakly supervised learning algorithms and connections to related topics, such as multiple instance learning and semi-supervised learning;
* Learning in the presence of significant label noise;
* Value of "seeding" weakly supervised learning with small amounts of strongly supervised data;
* Datasets to enable direct comparison of approaches, including challenges in obtaining reliable groundtruth annotations;
* Transfer learning (e.g., learning from video and testing in the image domain);
* Weakly supervised approaches in robotics;
* Combining audio/visual content with text;
* Challenge problems in audio, image, video and multimodal domains.

Symposium Format

The symposium will consist of presentations from several invited speakers, presentations selected from position papers, an open poster session, and panel discussions about key issues (such as publicly available datasets). The sessions will be organized so as to provide ample opportunities for unstructured discussion.

Submission Requirements

Participants should submit, by email to Rahul Sukthankar (, a concise summary of their research interests (limited to 2 pages) that includes pointers to relevant published work. The organizers will select a subset of submissions to supplement the invited talks and will encourage all participants to present a poster about their research.

The symposium will not generate any proceedings; however, participants will be encouraged to submit articles for a journal special issue on this topic.

Primary Contact:
Rahul Sukthankar, Google Research and Carnegie Mellon. Email:

Organizing Committee:
Omid Madani, Google Research
James M. Rehg, Georgia Tech
Rahul Sukthankar, Google Research and Carnegie Mellon

Related Resources

ECCV 2018   European Conference on Computer Vision
AAAI 2017   The Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17)
AAAI 2018   The Thirty-Second AAAI Conference on Artificial Intelligence
ICPR 2018   24th International Conference on Pattern Recognition
ETHE Blearning 2017   Blended learning in higher education: research findings
IJCAI 2018   International Joint Conferences on Artificial Intelligence Organization
ICWSM 2017   11th International AAAI Conference on Web and Social Media
ACL 2018   56th Annual Meeting of the Association for Computational Linguistics
AAAI-ATSE 2018   AAAI-18 Workshop on artificial intelligence applied to assistive technologies and smart environments
ICAISC 2018   International Conference on Artificial Intelligence and Soft Computing