GCLR 2021: AAAI 2021 Workshop on Graphs and more Complex structures for Learning and Reasoning |
Website | https://sites.google.com/view/gclr2021/ |
Submission link | https://easychair.org/conferences/?conf=gclr2021 |
Abstract registration deadline | November 9, 2020 |
Submission deadline | November 9, 2020 |
The study of complex graphs is a highly interdisciplinary field that aims to study complex systems by using mathematical models, physical laws, inference and learning algorithms, etc. Complex systems are often characterized by several components that interact in multiple ways among each other. Such systems are better modeled by complex graph structures such as edge and vertex labelled graphs (e.g., knowledge graphs), attributed graphs, multilayer graphs, hypergraphs, etc. In this GCLR (Graphs and more Complex structures for Learning and Reasoning) workshop, we will focus on various complex structures along with inference and learning algorithms for these structures. The current research in this area is focused on extending existing ML algorithms as well as network science measures to these complex structures. This workshop aims to bring researchers from these diverse but related fields together and embark interesting discussions on new challenging applications that require complex system modeling and discovering ingenious reasoning methods. We have invited several distinguished speakers with their research interest spanning from the theoretical to experimental aspects of complex networks.
More information can be accessed from https://sites.google.com/view/gclr2021/.
Important Dates
- Extended Abstract Submission Deadline: Nov 9, 2020 (AoE)
- Full Paper Submission Deadline: Nov 9, 2020 (AoE)
- Paper Notification: Nov 30, 2020
Call For Papers
We invite submission from participants who can contribute to the theory and applications of modeling complex graph structures such as hypergraphs, multilayer networks, knowledge graphs, etc. The topics of interest include, but not limited to, the following:
- Constraint satisfaction and programming (CP), (inductive) logic programming (LP and ILP)
- Learning with Multi-relational graphs (alignment, knowledge graph construction, completion, reasoning with knowledge graphs, etc.)
- Learning with algebraic or combinatorial structure
- Link analysis/prediction, node classification, clustering for complex graph structures
- Network representation learning
- Theoretical analysis of graph algorithms or models
- Optimization methods for graphs/manifolds
- Probabilistic and graphical models for structured data
- Social network analysis and measures
- Unsupervised graph/manifold embedding methods
Papers will be presented in poster format and some will be selected for oral presentation. Through invited talks and presentations by the participants, this workshop will bring together current advances in Network Science as well as Machine Learning, and set the stage for continuing interdisciplinary research discussions.
Submission Guidelines
We invite submissions to the AAAI workshop on Learning and Reasoning with Complex Graphs to be held virtually on 8th or 9th Feb 2021 virtually. We welcome the submissions in the following two formats:
- Extended abstracts: We encourage participants to submit preliminary but interesting ideas that have not been published before as extended abstracts. These submissions would benefit from additional exposure and discussion that can shape a better future publication. We also invite papers that have been published at other venues to spark discussions and foster new collaborations. Submissions may consist of up to 4 pages plus one additional page solely for references.
- Full papers: Submissions must represent original material that has not appeared elsewhere for publication and that is not under review for another refereed publication. Submissions may consist of up to 7 pages of technical content plus up to two additional pages solely for references.
The submissions should adhere to the AAAI paper guidelines available at (https://aaai.org/Conferences/AAAI-21/aaai21call/)
Accepted submissions will have the option of being published on the workshop website. For authors who do not wish their papers to be posted online, please mention this in the workshop submission. The submissions need not be anonymized.
Speakers
- Phil Chodrow (UCLA)
- Ginestra Bianconi (Queen Mary University of London)
- Christopher Ré (Stanford University)
- William L. Hamilton (McGill University)
- Manlio De Domenico (CoMuNe Lab, FBK)
- Stephen Bach (Brown University)
- Anima Anandkumar (Caltech and Nvidia)
- Gesine Reinert (University of Oxford)
Organizing Committee
Organizers
- Tarun Kumar (IIT Madras)
- Deepak Maurya (IIT Madras)
- Nikita Moghe (Univ. of Edinburgh)
- Naganand Yadati (IISc Bangalore)
- Jeshuren C. (IIT Madras)
- Aparna Rai (IIT Guwahati)
Advisors
- Balaraman Ravindran (IIT Madras)
- Kristian Kersting (TU Darmstadt)
- Sarika Jalan (IIT Indore)
- Partha P. Talukdar (IISc Bangalore)
- Sriraam Natarajan (Univ. of Texas Dallas)
Venue
The workshop will be held virtually.
Contact
All questions about submissions can be emailed to gclr2021organizers@gmail.com.