What’s coming up at IJCAI-PRICAI 2020?


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07 January 2021

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IJCAI-PRICAI2020 LOGO
IJCAI-PRICAI2020, the 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence starts today and will run until 15 January. Find out what’s happening during the event.

The conference schedule is here and includes tutorials, workshops, invited talks and technical sessions. There are also competitions, early career spotlight talks, panel discussions and social events.

Invited talks

There will be eight invited talks on a wide variety of topics. The speakers and titles are as follows:
Elisabeth André (Universität Augsburg)
Socially interactive artificial intelligence: challenges and perspectives

Craig Boutilier (Google Research)
On user utility and social welfare in recommender ecosystems

Hiroshi Ishiguro (Osaka University and ATR Hiroshi Ishiguro Laboratories)
Studies on avatars and our future society

Mykel Kochenderfer (Stanford University)
Automated decision making for safety critical applications

Stéphane Mallat (Collège de France, PSL University)
A mathematics view of deep neural networks

Yukie Nagai (University of Tokyo)
Does predictive coding provide a unified theory of artificial intelligence?

Peter Stone (University of Texas at Austin and Sony AI)
Ad hoc autonomous agent teams: collaboration without pre-coordination

Tinne Tuytelaars (KU Leuven)
The quest for the perfect image representation

Workshops

Here is the list of workshops with links to the associated webpages.
2020 Principle and Practice of Data and Knowledge Acquisition Workshop (PKAW2020)
8th Artificial Intelligence for Knowledge Management (AI4KM)
Disease Computational Modeling
5th International Workshop on Biomedical Informatics with Optimization and Machine learning (BOOM 2020)
1st Workshop on Artificial Intelligence for Function, Disability, and Health (AI4Function)
Joint Workshop on Human Brain and Artificial Intelligence (HBAI 2020)
4th Workshop on Artificial Intelligence in Affective Computing (AffComp)
AI for Social Good
2nd AI-based Multimodal Analytics for Understanding Human Learning in Real-World Educational Contexts (AIMA4Edu)
4th International Workshop on Multi-Agent Path Finding
Data Science Meets Optimization (DSO)
Monte Carlo Search 2020
1st International Workshop on Heuristic Search in Industry
AI for Internet of Things (AI4IoT 2020)
1st International Workshop on Harmonious and Symbiotic Interaction in AI & Robotics (HSIAR2020)
Robot Dialogues – Dialogue Models for Human-Robot Interaction
Artificial Intelligence for Anomalies and Novelties
2nd International Workshop on Bringing Semantic Knowledge into Vision and Text Understanding
2nd Workshop on Financial Technology and Natural Language Processing (FinNLP)
Linguistic and Cognitive Approaches to Dialogue Agents (LACATODA)
AI4Narratives
Neuro-Cognitive Modeling of Humans and Environments
Tensor Network Representations in Machine Learning
Knowledge-Based Reinforcement Learning (KBRL)
6th Workshop on Semantic Deep Learning
Learning Data Representation for Clustering
2nd International Workshop on Deep Learning for Human Activity Recognition
Federated Machine Learning for Data Privacy and Confidentiality
Applied Mechanism Design
3D Artificial Intelligence Challenge through 3D-FUTURE Benchmark
Workshop on AI and Blockchains
Workshop on Artificial Intelligence Safety (AISafety)
2nd Workshop on AI & Food (AIxFood)
Explainable Artificial Intelligence (XAI)

Tutorials

The tutorial schedule can be found here. Below is a list of the tutorials with links to the related webpages.
Adversarial Machine Learning: On The Deeper Secrets of Deep Learning
Algorithm Configuration: Challenges, Methods and Perspectives
Bayesian Optimization for Balancing Metrics in Recommender Systems
Belief and Opinion Dynamics and Aggregation in Multi-Agent Systems
Causal Inference and Stable Learning
Combinatorial Approaches for Data Feature Topic Selection and Summarization
Compressed Communication for Large-scale Distributed Deep Learning
Compression of Deep Learning Models for NLP
Computational Game Theory and Its Applications
Current and Future Trends of Neural Knowledge Graph Representation and Reasoning
Conscious AI: Significance and Development
Ethics in Sociotechnical Systems
Exploring Attention, Dynamic Information Flow, and Modularity as Ingredients for Generalization in Deep Learning
Exploring Rare Categories on Graphs: Representation, Inference, and Generalization
Fact-Checking, Fake News, Propaganda, and Media Bias: Truth Seeking in the Post-Truth Era
Fair AI in a Nutshell: Can Algorithms be Fair?
Federated Learning Systems: Comparative Studies and Hand-on Demonstrations
Federated Recommender Systems
From Data Independence to Ontology Based Data Access (and back)
Goal Recognition Design
Heterogeneous Information Network Embedding and Applications
Logic-Enabled Verification and Explanation of ML Models
Machine Ethics State-of-the art and interdisciplinary challenges
Machine Learning and Game Theory
Machine Learning for Combinatorial Optimization
Machine learning for data streams with scikit-multiflow
Machine Learning for Drug Development
Making Your Research Reproducible – Practical Advice on How to Implement the General Guidelines for Making Empirical AI Research Reproducible
Meta-learning and Automated Machine Learning: Approaches and Applications
Mining User Interests from Social Media
Multimodal Learning in K-12 Education: Promise, Progress and Challenges
Music AI
Next-Generation Recommender Systems and Their Advanced Applications
Optimization & Learning Approaches to Resource Allocation for Social Good
Probabilistic Circuits: Representations, Inference, Learning and Applications
Robust Multi-view Visual Learning: A Knowledge Flow Perspective
Rule-based Stream Reasoning
Scalable Deep Learning: How far is one billion neurons?
Theoretical Foundations of multi-agent Flexible Temporal Epistemic and Contingent Aspects of Planning
The role of AI in developing persistent personalized privacy and online deception awareness
The Role of Knowledge Repositories in Information Retrieval
Towards Deep Explanation in Machine Learning Supported by Visual Methods
Trusting AI by Testing and Rating Third Party Offerings
Trustworthiness of Interpretable Machine Learning
Tutorial on Robot Audition Open Source Software HARK
Video-based Data Collection for Sports Tactical Analysis

Technical sessions

You can find details of the technical sessions here, including links to the articles.
The list of accepted papers is here.



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Lucy Smith , Managing Editor for AIhub.




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