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

Institute for Pure and Applied Mathematics (IPAM), UCLA

In recent years, the use of Machine Learning techniques to Operations Research (OR) problems, especially in the Discrete Optimization (DO) a.k.a. Combinatorial Optimization context, opens very interesting scenarios because DO is the “home” of an endless list of decision-making problems that are of fundamental importance in multitude applications. The workshop will bring together experts in mathematics (optimization, graph theory, sparsity, combinatorics, statistics), operations research (assignment problems, routing, planning, Bayesian search, automation, scheduling), machine learning (deep learning, supervised, self-supervised and reinforcement learning) and artificial intelligence at large (including multi-agent systems, interpretability, fairness, etc.).

Graphentheorie und Kombinatorik,    Optimierungsrechnung, Entscheidungsunterstützung

Open Data Science Conference

ODSC East 2023 is a conference dedicated to the latest languages, tools, and frameworks in data science, AI, ML and DL.

Event lasts 3 days, including an extra day for the mini-bootcamp. Choose from in-person or virtual tracks based on your needs. Please be advised agendas are different for each tracks.

Accelerate your ML/DL, NLP and Data Engineering knowledge, training, and network all in one event. ODSC is community-based event and everyone can find something useful and interesting for themselves.

If you need corporate team advance sales or looking for advance ticket purchases , email us at info@odsc.com

Email: iryna@odsc.com

Data Science, Machine Learning, AI

ICERM

MSML2023 is the third edition of a newly established conference, with emphasis on promoting the study of mathematical theory and algorithms of machine learning, as well as applications of machine learning in scientific computing and engineering disciplines. This conference aims to bring together the communities of machine learning, applied mathematics, and computational science and engineering, to exchange ideas and progress in the fast-growing field of scientific machine learning (SciML).

Program Staff;     Tel.: [1-401-863-5030];     Email: programstaff@icerm.brown.edu

The objective of this annual conference series is to promote the study of: Theory and algorithms of machine learning. Applications in scientific and engineering disciplines such as physics, chemistry, material sciences, fluid and solid mechanics, etc. To provide hands-on tutorials for students and new researchers in the field.

Mathematical Sciences Research Institute (MSRI)

The overarching goal of this summer school is to expose the students both to modern forms of unsupervised learning — in the form of geometrical and topological data analysis — and to supervised learning — in the form of (deep) neural networks applied to regression/classification problems. The organizers have opted for a lighter exposure to a broader range of topics. Using the metaphor of a meal, we are offering 2 + 2 samplers — geometry and topology for data analysis + theoretical and practical deep learning — rather than 1 + 1 main dishes. The main goal, thus, is to inspire the students to learn more about one or several of the topics covered in the school.

Mathematical Sciences Research Institute (MSRI)

UC Santa Barbara, Kavli Institute for Theoretical Physics (KITP)

A long-standing question in the neurobiology of learning is that of timescales. The brain can associate events that are separated by seconds, minutes, hours, days, weeks, or longer. Yet, the known biological mechanisms for inducing changes in the synaptic connections between neurons are driven by neural events that are separated by typically no more than a few tens or hundreds of milliseconds. This conference will convene scientists studying the molecular, cellular, and circuit-level mechanisms used by the brain to bridge the multiple timescales across which events play out in the experience of an individual. The goal will be to assemble an up-to-date understanding of the set of biological mechanisms available in the brain to support associative learning across different timescales. The conference's emphasis on biological mechanisms will complement and support the main program’s more computational focus, and encourage an integrated analysis of statistical learning spanning molecular, cellular, circuit, and behavioral-level phenomena.

Molekularbiologie,    Neurologie

Fora Group

Over three days, Ai4 2023 gathers 1700+ business leaders and data practitioners and 250+ speakers to facilitate the responsible adoption of artificial intelligence and machine learning technology. Join us at the industry’s most impactful AI event.

Customer Service;     Tel.: [(929) 376-7732];     Email: info@ai4conferences.com

artificial intelligence, machine learning, ai, ml, neural network, finance, healthcare, retail, cybersecurity, technology, tech

Are you ready to experience the leading data science & AI conference as it returns to San Francisco? Accelerate your career with hands-on training, demo talks, workshops, networking events, nine tracks, and more. The ODSC West in-person conference will feature expert-led, hands-on instruction in in-demand topics and tools, including: NLP | Python | Responsible AI | TensorFlow | PyTorch | Conversational AI | OpenAI | Cybersecurity | Data Visualization | scikit-learn | MLOps | Data Engineering | Machine Learning | and much more

Email: iryna@odsc.com