Meetings/Workshops on Soft Computing, Evolutionary Computation, Metaheuristic Optimization, Fuzzy Logic in the United States (USA)
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ICTAI 2019 — 31st International Conference on Tools with Artificial Intelligence
04 Nov 2019 - 06 Nov 2019 • Portland, Oregon, United States
ICTAI 2019: The IEEE International Conference on Tools with Artificial Intelligence (ICTAI) is a leading Conference of AI in the Computer Society providing a major international forum where the creation and exchange of ideas related to artificial intelligence are fostered among academia, industry, and government agencies.
ICRC — IEEE Rebooting Computing Week 2019
04 Nov 2019 - 08 Nov 2019 • San Mateo, California, United States
IEEE Rebooting Computing Week 2019 is the premier venue for novel computing approaches, including algorithms and languages, system software, system and network architectures, new devices and circuits, and applications of new materials and physics. Join us for another exciting week of events focusing on the next era of computing.
Novel computing approaches, algorithms, languages, system software, system and network architectures, new devices and circuits, applications of new materials and physics, quantum
18 Feb 2020 - 21 Feb 2020 • Los Angeles, CA, United States
Institute for Pure and Applied Mathematics (IPAM), UCLA
Psychiatric disorders are typically diagnosed and evaluated using subjective psychological exams that assess symptoms, thoughts, feelings and behavioral patterns. Ongoing and recent advances in measurements provide EEG, functional MRI, optogenetic, genomic, and metabolic data. Along with mathematical methods developed to analyze these data, a more physiological and quantitative approach for diagnosis and treatment can be envisioned. This workshop will explore how modern computational tools and mathematical modeling can be integrated with measurements to improve psychiatric diagnosis and treatment.
Intersections between Control, Learning and Optimization
24 Feb 2020 - 28 Feb 2020 • Los Angeles, CA, United States
Relationships between the areas of control, learning, and optimization have always been strong, but have recently been expanding and deepening in surprising ways. Optimization formulations and algorithms have historically been vital to solving problems in control and learning, while conversely, control and learning have provided interesting perspectives on optimization methods. Intersections that have been explored recently include relationships between reinforcement learning and model predictive control, and the use of control techniques to analyze the convergence of optimization algorithms. This workshop will bring together researchers who work in Control, Learning, and Optimization to discuss current areas of interaction and explore possibilities for future areas of collaboration.
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Last updated: 23 September 2019