Special Sessions

Special session on “Graph Machine Learning”

Special Session Organizer: Gianfranco Lombardo, Ph.D., University of Parma, Italy

Contact: gianfranco.lombardo@unipr.it

Paper Submission Deadline: Wednesday March 23, 2022 (AoE)

https://easychair.org/my/conference?conf=lod2022

Graphs and Networks are ubiquitous in a wide range of domains such as Computer Science, Biology, Sociology, Finance, and others in particular for their ability of modelling complex systems and expressing relational knowledge about interacting entities. At the same time, Machine learning methods have become a prominent technology of our time that enables us to solve complex tasks exploiting network structures and knowledge graphs. This special session provides a platform to share high-quality research ideas related to the novel domain of Graph Machine Learning and its applications.

Topics of interest include, but are not limited to:

●  Representation learning for graphs

●  Node and edge embedding

●  Graph Neural Networks

●  Node classification applications

●  Learning on large-scale graphs

●  Link prediction applications

●  Machine learning on temporal and dynamic graphs

●  Machine learning on Knowledge graphs

●  Machine learning for question and approximate query answering with graphs

●  Graph Machine learning applications

●  Continual learning in Graph Machine Learning

●  Transductive/Inductive learning methods for graphs

●  Hybrid models that combine text, graph structure and semantics

●  Adversarial and generative approaches for Graph Machine Learning

●  Social networks applications

●  Financial networks

 

Special session on “Machine Learning for Fintech”

Special Session Organizer: Gianfranco Lombardo, Ph.D., University of Parma, Italy

Contact: gianfranco.lombardo@unipr.it

Paper Submission Deadline: Wednesday March 23, 2022 (AoE)

https://easychair.org/my/conference?conf=lod2022

Fintech applications seek to improve and automate the delivery and use of financial services at several levels for different stakeholders. In particular it can help private investors, hedge funds, companies and business owners to better manage their financial operations. In this field, Machine Learning techniques play a key role in providing solutions for forecasts, document analysis, portfolio optimization and selection, trading strategies and others. Many open problems are becoming relevant in this domain, especially the ones related to data availability, continual learning approaches and Natural Language Processing techniques able to deep analyze and extract knowledge from financial documents and reports.

Topics of interest include, but are not limited to:

●  Continual Learning in the financial domain

●  Machine Learning-based trading strategies

●  Natural Language Processing for financial analysis

●  Machine Learning for Asset pricing

●  Graph Machine Learning for FinTech applications

●  Knowledge extraction from documents

●  Reinforcement learning approaches for FinTech

●  Financial networks analysis

●  Representation learning in the financial domain

●  Bankruptcy prediction

●  Machine learning for Portfolio selection

 

Tracks:

I) Track on “AI for Sustainability

https://easychair.org/my/conference?conf=lod2022

 

II) Track on “AI to help to fight Climate Change

World Economic Forum report, Harnessing Artificial Intelligence for the Earth.

https://easychair.org/my/conference?conf=lod2022

 

III) The 7 Tracks on “Machine Learning”

  • Multi-Task Learning
  • Reinforcement Learning
  • Deep Learning
  • Generative Adversarial Networks
  • Deep Neuroevolution
  • Networks with Memory
  • Learning from Less Data and Building Smaller Models

https://easychair.org/my/conference?conf=lod2022

 

IV) The 7 Tracks on “Data Science and Artificial Intelligence”

  • Simulation Environments to understand how AI Systems Learn
  • Chatbots and Conversational Agents
  • Data Science at Scale & Data in the Cloud
  • Urban Informatics & Data-Driven Modelling of Complex Systems
  • Data-centric Engineering
  • Data Security, Traceability of Information & GDPR
  • Economic Data Science

https://easychair.org/my/conference?conf=lod2022

 

V) Track on “Multi-Objective Optimization”

  • Comparative studies of various many-objective optimization techniques
  • Designing and constructing many-objective benchmark test problems
  • Designing quality/performance metrics for many-objective solutions/algorithms
  • Development of meta-heuristic algorithms for many-objective optimization problems
  • Evolutionary many-objective optimization methods in search-based software engineering
  • Evolutionary many-objective optimization methods applied to real-world problems
  • Exact methods from mathematical programming for many-objective optimization problems
  • Many-objective optimization in bi-level optimization problems
  • Many-objective optimization in combinatorial/discrete optimization problems
  • Many-objective optimization in computational expensive optimization problems
  • Many-objective optimization in constrained optimization problems
  • Many-objective optimization in dynamic environments
  • Many-objective optimization in large-scale optimization problems
  • Objective reduction techniques
  • Preference articulation in many-objective optimization
  • Preference-based search in many-objective optimization
  • Study of parameter sensitivity in many-objective optimization
  • Theoretical analysis and developments in many-objective optimization
  • Visualization for decision-making in many-objective optimization
  • Visualization for many-objective solution sets
  • Visualization for the search process of meta-heuristic algorithms
  • Multi-objective Optimization: new algorithms and concrete applications
  • Industrial problems, transportation and logistics problems
  • contributions to theoretical aspects of Multi-Objective Optimization (MOO) and Multi-Criteria Decision Aiding (MCDA)
  • descriptions of actual application cases
  • software contributions to MOO or MCDA
  • inter-disciplinary research, presenting the contributions of MOO and/or MCDA to other scientific disciplines, or integrating other disciplines into MOO or/and MCDA
  • decision aiding and multi-objective optimization for sustainability

https://easychair.org/my/conference?conf=lod2022