Meetings/Workshops on Applied Maths: Neural Networks and Artificial Intelligence, Machine Learning in the United States (USA)

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ITU K — 2018 ITU Kaleidoscope: Machine Learning for a 5G Future
26 Nov 2018 - 28 Nov 2018 • Santa Fe, United States
The aim of Kaleidoscope is to identify emerging developments in Information and Communication Technologies (ICTs) and, in particular, areas in need of international standards to support the development of successful products and services. K-2018 calls for original scientific papers addressing advances in research on machine learning and artificial intelligence techniques for future communication networks, covering all aspects of network design, management, implementation and optimization.
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AIW — AI World Conference & Expo
03 Dec 2018 - 05 Dec 2018 • Boston, United States
AI World Conference and Expo is focused on the state of the practice of artificial intelligence in the enterprise. Now in our third year, the 3-day conference and expo are designed for business and technology executives who want to learn about innovative implementations of AI in the enterprise. Enterprise organizations face conflicting priorities. Where do they turn to cut through the hype and determine how to prioritize AI strategies and technologies for their business? AI World is organized around this singular goal, enabling business leaders to learn how to use AI to build a competitive advantage, drive new business models and opportunities, reduce operational costs and accelerate your innovation efforts.
Phone: [7819725400];     Email:
Artificial Intelligence, Enterprise Deep Learning, IoT, Emerging Technologies, Big Data, AI, Cognitive computing, AI in Healthcare, AI in Pharma
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AAAI 2019 — Conference on Artificial Intelligence
27 Jan 2019 - 01 Feb 2019 • Honolulu, Hawaii, United States
The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19) will be held January 27 – February 1, 2019 at the Hilton Hawaiian Village, Honolulu, Hawaii, USA. The program chairs will be Pascal Van Hentenryck (University of Michigan, USA) and Zhi-Hua Zhou (Nanjing University, China). The purpose of the AAAI conference is to promote research in artificial intelligence (AI) and scientific exchange among AI researchers, practitioners, scientists, and engineers in affiliated disciplines.
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At the Crossroad of Physics and Machine Learning
11 Feb 2019 - 15 Feb 2019 • UC Santa Barbara, United States
The ongoing developments in machine learning are influencing physics research and offer the potential to open new routes to discovery. Simultaneously, concepts from physics are being used to better understand some of the machine learning methods and inspire new ones. This conference will gather researchers on the forefront of these developments to discuss existing key progress and promising new directions. We will highlight the use of machine learning in several areas of data-intensive physics including condensed matter, soft-matter, high-energy physics, cosmology, and astrophysics. We will also focus on the complementary developments in the application of physics concepts to the theory and practice of machine learning.
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Automating Insight: Pushing the Frontier of Quantum Physics with Machine Learning
16 Feb 2019 • UC Santa Barbara, United States
At this teachers' conference, we will hear from scientists using the techniques of artificial intelligence and machine learning to advance our understanding of the quantum behavior of such matter as magnets, metals and superconductors, as well as the constituents of atoms. We will also hear how insights from physics could be repurposed to advance the field of machine learning itself.
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ALT 2019 — 30th International Conference on Algorithmic Learning Theory
22 Mar 2019 - 24 Mar 2019 • Chicago, IL, United States
O’Reilly technology conference — Strata Data Conference
26 Mar 2019 - 28 Mar 2019 • San Francisco, California, United States
Strata Data Conference is where thousands of innovators, leaders, and practitioners gather to develop new skills, share best practices, and discover how tools and technologies are evolving to meet new challenges. Find out how big data, machine learning, and analytics are changing how we do business at Strata Data Conference.
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O’Reilly technology conference — Artificial Intelligence Conference
16 Apr 2019 - 18 Apr 2019 • New York, New York, United States
The AI Conference delivers an unsurpassed depth and breadth in technical content—with a laser-sharp focus on the most important AI developments for business. From apps and reinforcement learning to conversational interfaces and executive briefings, learn how to implement AI in real-world projects using machine learning, NLP, Tensorflow, and more. Delve into the latest research and explore what the future holds for applied artificial intelligence engineering.
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ICLR 2019 — International Conference on Learning Representations
06 May 2019 - 09 May 2019 • New Orleans, United States
The performance of machine learning methods is heavily dependent on the choice of data representation (or features) on which they are applied. The rapidly developing field of deep learning is concerned with questions surrounding how we can best learn meaningful and useful representations of data. We take a broad view of the field and include topics such as feature learning, metric learning, compositional modeling, structured prediction, reinforcement learning, and issues regarding large-scale learning and non-convex optimization.
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ICML 2019 — Thirty-sixth International Conference on Machine Learni
10 Jun 2019 - 15 Jun 2019 • Long Beach, CA, United States
ICML is the leading international machine learning conference and is supported by the International Machine Learning Society (IMLS).
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FUZZ-IEEE — 2019 IEEE International Conference on Fuzzy Systems
23 Jun 2019 - 26 Jun 2019 • New Orleans, LA, United States
FUZZ-IEEE is the foremost conference in the field of fuzzy systems. It covers all topics in fuzzy systems, from theory to applications.
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Machine Learning for Physics and the Physics of Learning
04 Sep 2019 - 08 Dec 2019 • Institute for Pure and Applied Mathematics (IPAM),, United States
Machine Learning (ML) is quickly providing new powerful tools for physicists and other natural scientists to extract essential information from large amounts of data, either from experiments or simulations. This IPAM long program will foster nontrivial research and provoke scientific discussion at the interface between ML and Physics. We aim to go beyond simple fitting of physical models from data and move the discussion to (i) using generative ML methods and active learning in order to generate and design complex and novel physical structures and objects, (ii) obtain models that are physically understable, e.g. by maintaining relations of the predictions to the microscopic physical quantities used as an input, (iii) using ML to learn the physical principles and mathematical structures underlying the data, and (iv) developing new ML methods inspired by methods and models developed in Physics.
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Last updated: 24 August 2018