IJCAI 2016 Workshop on
Deep Learning for Artificial Intelligence (DLAI)

New York Midtown Hilton Hotel | Room: Concourse A
10 July 2016 | New York, NY (USA)

Papers and Presentations | Description | Topics of Interest | Agenda | Speakers | Paper Submissions | Dates | Organizers | Links | FAQ | News


Deep Learning (DL) techniques have ignited a firestorm of attention from academia and industry due to their success on many benchmarks and applications, such as those pertaining to image recognition, automated caption generation, speech recognition, natural language processing, and game AI. To date, most DL efforts have focused on analysis tasks (e.g., classification, regression), and have not involved the use of symbolic representations and inference methods commonly used in AI. For example, few DL efforts have focused on synthesis tasks (e.g., planning, scheduling, and design), involved the use of logical or graphical models, or made other tight connections with AI. Much could be gained by investigating how best to integrate AI and DL techniques; this would interest researchers studying a variety of topics.

The DLAI workshop will provide a forum for describing and learning about promising methods that use DL techniques in AI processes, highlighting initial contributions/benefits, and encouraging further work, thereby fostering connections among two somewhat disparate groups of researchers. We intend it to interest AI researchers who investigate the use of DL techniques in their studies and DL researchers who seek to understand/explore the roles that DL techniques can perform in, for example, systems that can reason with interpreted sensor data.

This workshop will include three primary components. The first is invited talks by senior researchers who have investigated DLAI, can provide visions for what these types of integrations can accomplish, and can identify important open research issues. Second, we will host presentations of accepted papers (please see paper submissions for details). Finally, we will include a panel of active DLAI researchers who will be asked to discuss key issues that require attention, and speakers from industry (or government) who have interest in solving problems using DLAI techniques.

Topic Areas of Interest

The integration of AI and DL techniques could interest researchers studying the following topic areas (among others):

Invited Speakers

We will host presentations by two invited speakers, listed (alphabetically) below.

Paper Submissions

We welcome contributions that, for example, describe prior or ongoing work on DLAI, describe key issues that require further research, or highlight relevant challenges of interest to AI and DL researchers and practitioners, and plans for addressing them. In particular, we welcome four types of submissions:
  1. Theoretical and/or empirical analyses
  2. System demonstrations
  3. Planned research or application
  4. Position papers
Self-contained submissions must be no longer than seven pages (i.e., six pages for the main text of the paper, and one additional page for (only) references) in PDF format for letter-size (8.5 x 11) paper. Please use
IJCAI-16's templates, and include author names, affiliations, and email addresses on the first page. Submissions should be made through EasyChair.

Papers will be subject to peer review by the workshop program committee. Selection criteria include originality of ideas, correctness, clarity and significance of results, and quality of presentation.



Program Committee

Related Events

Related Work

The following is an incomplete list of related publications concerning DLAI that go beyond standard classification and regression tasks (e.g., object identification, action recognition, sentiment analysis). We welcome additional recommendations for this list.

While highly relevant, few (if any) DLAI publications related to reinforcement learning (RL) are listed here because Deep RL is the focal topic of a sibling workshop at IJCAI-16.