Konferenzen  >  Mathematik  >  Neuronale Netze und Künstliche Intelligenz, Maschinelles Lernen  >  Vereinigte Staaten

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1
AI Con USA
02. Jun 2024 - 07. Jun 2024 • Las Vegas, Vereinigte Staaten
Veranstalter:
TechWell
Zusammenfassung:
Welcome to the cutting-edge world of artificial intelligence and machine learning. AI Con USA brings together leading experts, researchers, innovators, and companies from around the globe to explore the latest developments in AI and machine learning. Whether you are a seasoned professional, a researcher, or an enthusiast eager to stay at the forefront of AI and machine learning, AI Con USA provides a dynamic environment for knowledge exchange, collaboration, and inspiration.
Kontakt:
Event Support;     Tel.: [9042780524];     Email: clientsupport@techwell.com
Themen:
AI, Machine Learning, AI Ethics, LLMs, GitHub, MLOps, GenAI
Eintrags-ID:
1607091
2
Ai4 2024
12. Aug 2024 - 14. Aug 2024 • Las Vegas, Vereinigte Staaten
Veranstalter:
Ai4
Zusammenfassung:
Over two and a half days, join thousands of executives and technology innovators at the epicenter of the AI community. Discover the latest applications, advancements, and best practices shaping the future of AI. Enjoy dedicated content & unbeatable networking for both business & technical leaders from every major industry and job function, from leading AI startups, investors, and government organizations.
Kontakt:
Email: info@ai4conferences.com
Themen:
artificial intelligence, AI, machine learning, innovation, startup, AI Ethics, AI governance, AI transformation, data, data strategy, generative AI, Productivity Tools, Machine Learning, NLP, Computer Vision, Neural Networks, Education, Finance, Financial Services, Government, Healthcare, Technology, Tech, Manufacturing, Retail, Cyber, Cybersecurity, Data Analytics, Data Engineering, Data Science, Marketing, CX, Advertising, Sales, AI Research, Blockchain, Generative Models, ML Ops, Recommender Systems
Eintrags-ID:
1600960
3
Workshop I — Analyzing High-dimensional Traces of Intelligent Behavior
23. Sep 2024 - 27. Sep 2024 • Los Angeles, CA, Vereinigte Staaten
Veranstalter:
Institute for Pure and Applied Mathematics (IPAM), UCLA
Zusammenfassung:
The study of biological intelligences has been transformed by breakthroughs in experimental and observational methods. New data have expanded our appreciation of the sophisticated behaviors exhibited by human and non-human animals across a range of taxa. Traces of intelligent behavior are typically high-dimensional, with complex structure in space and time. They often involve multiple data streams: for example, positional information from individual members of a bird flock, as well as “point-of-view” recordings showing what birds are looking at, moment by moment; or electrocorticographic recordings of human brain activity, as well as detailed traces of motor behavior. These traces are often buried beneath complex noise environments: individual animal movements must be pulled out of extensive visual clutter; whale song must be isolated from ocean noise. This complex, high-dimensional data requires entirely new approaches to data representation, integration, and analysis. This workshop will focus on the challenges raised by high-throughput, high-dimensional studies of intelligent behavior. It will bring together experts in animal cognition, computational neuroscience, and cognitive science with mathematicians and computer scientists focused on relevant methods in machine learning, network science, high-dimensional statistics, and information theory.
Themen:
Part of the Long Program Mathematics of Intelligences
Eintrags-ID:
1572578
4
Workshop II — Theory and Practice of Deep Learning
14. Okt 2024 - 18. Okt 2024 • Los Angeles, CA, Vereinigte Staaten
Veranstalter:
Institute for Pure and Applied Mathematics (IPAM), UCLA
Zusammenfassung:
Neural networks have confounded traditional ML beliefs about the dangers of overfitting and the need for regularization. They have also given rise to many new empirical findings around transfer learning, adversarial examples, compressibility, scaling laws (relating the size of datasets, models, and compute), grokking, and so on. What is needed to explain and predict all this is a rich new theory of learning capable of addressing the delicate interplay between model, data, and optimizers at large scale. This workshop will bring together top researchers driving the frontiers of this work with experts in both theory and experiment for natural intelligence. The result will be a scholarly discussion on how to frame questions about learning and how to distill the similarities and differences between learning with biological and artificial systems.
Themen:
Part of the Long Program Mathematics of Intelligences
Eintrags-ID:
1572522
5
Workshop III — Naturalistic Approaches to Artificial Intelligence
04. Nov 2024 - 08. Nov 2024 • Los Angeles, CA, Vereinigte Staaten
Veranstalter:
Institute for Pure and Applied Mathematics (IPAM), UCLA
Zusammenfassung:
This workshop will draw together researchers creating new algorithms and architectures (e.g., active symbol architectures, evolutionary programming approaches, neural program synthesis) with mathematicians and theoretical computer scientists who specialize in non-convex optimization, the theory of programming languages, type theory, proof theory, and category theory. It aims to promote cross-fertilization between these paradigms and more traditional approaches, while stimulating the development of rigorous foundations for evolutionary computing, program synthesis, and other naturalistic approaches to AI.
Themen:
Part of the Long Program Mathematics of Intelligences
Eintrags-ID:
1572554
6
Workshop IV — Modeling Multi-Scale Collective Intelligences
18. Nov 2024 - 22. Nov 2024 • Los Angeles, CA, Vereinigte Staaten
Veranstalter:
Institute for Pure and Applied Mathematics (IPAM), UCLA
Zusammenfassung:
This workshop will bring together leading experts in the mathematical modeling of collective intelligence. While the workshop will explore collective intelligence in many different systems, substrates (both natural and artificial), and scales, it will focus on three broadly applicable modeling frameworks: dynamical systems, which have been applied to systems as various as brains and insect swarms; statistical physics, which has illuminated the behavior of flocking birds and deep learning architectures; and game theory, which has been applied to animal, human, and AI collectives. The collective intelligence domain cultivates the further development of formal tools for treating compositionality; the emergence of new capacities and collective degrees of freedom at multiple scales; and the higher-level institutions that coordinate the intelligent behavior of lower-level parts.
Themen:
Part of the Long Program Mathematics of Intelligences
Eintrags-ID:
1572608


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