Call for papers

The emerging paradigm of Tsetlin machines makes a fundamental shift from arithmetic-based to logic-based machine learning. At the core, finite-state machines, based on learning automata, learn patterns using logical clauses, and these constitute a global description of the task learnt. In this way, the Tsetlin machine introduces the concept of logical interpretable learning, where both the learned model and the process of learning are easy to follow and explain. As a result, it reduces the expertise needed to apply ML techniques efficiently in various domains. The paradigm has enabled competitive accuracey, scalability, memory footprint, inference speed, and energy consumption across diverse tasks, including classification, regression, natural language processing (NLP), and speech understanding.

Topics of Interest

Topics of interest include (but are not limited to):

• Tsetlin Machines
• Learning Automata
• Novel AI Algorithms
• Explainable and Interpretable AI
• Energy-efficient AI Systems Design
• New AI Applications, including signal- and image processing
• Intelligent Data Preprocessing
• Tsetlin Machines and Quantum Computing

Committees

General Co-Chairs

• Linga Reddy Cenkeramaddi, University of Agder, Norway
• Phaneendra K. Yalavarthy, Indian Institute of Science, Bengaluru, India

Program Co-Chairs

• Rebekka Olsson Omslandseter, University of Agder, Norway
• Vaanathi Sundaresan, Indian Institute of Science, Bengaluru, India

Financial Chair

• Anne Lene Fjeldavlie, University of Agder, Norway
• Shivangi Garg, TANUH, Bengaluru, India

Publicity Chair

• Pål Grandal, University of Agder, Norway
• Tarini Naik, TANUH, Bengaluru, India

Web Chair

• Elisabeth Rasmussen, University of Agder, Norway
• Tarini Naik, TANUH, Bengaluru, India

Sponsors

• University of Agder
• Newcastle University
• University of Pittsburgh
• Literal Labs
• NORA.ai
• Anzyz Technologies
• Translational AI for Networked Universal Healthcare Foundation (TANUH)

Technical Co-Sponsors

• IEEE Computer Society
• IEEE
• TCDE