International Symposium on the Tsetlin Machine (ISTM) is a premier international symposia series which provides a high-quality networking and dissemination platform for emerging machine learning systems research and development, including the Tsetlin machine. This specialist series covers a wide variety of topics, ranging from software algorithms, data science to hardware accelerator designs. Check the Call for Papers for more details.
This year ISTM is taking place in the city of Pittsburgh (@ University of Pittsburgh), situated in the west of Pennsylvania, USA. It is being hosted by the University of Pittsburgh and sponsored by multiple academic and non-academic organizations – see our sponsors below.
What is Tsetlin Machine? The emerging paradigm of Tsetlin machine provides 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 accuracy, scalability, memory footprint, inference speed, and energy consumption across diverse tasks, including classification, convolution, regression, natural language processing (NLP), and speech understanding.
- Abstract submission: April 5
- Paper submission: April 12
- Notification: June 7
- Camera-ready: June 28