Conferences and Meetings on Neural Networks and Artificial Intelligence, Machine Learning

Soft Computing, Evolutionary Computation, Metaheuristic Optimization, Fuzzy Logic,    Software Agents and Intelligent Agents in Artificial Intelligence

In the recent decade, we have witnessed rapid progress in machine learning in general and deep learning in particular, mostly driven by tremendous data. As these intelligent algorithms, systems, and applications are deployed in real-world scenarios, we are now facing new challenges, such as scalability, security, privacy, trust, cost, regulation, and environmental and societal impacts. In the meantime, data privacy and ownership has become more and more critical in many domains, such as finance, health, government, and social networks. Federated learning (FL) has emerged to address data privacy issues. To make FL practically scalable, useful, efficient, and effective on security and privacy mechanisms and policies, it calls for joint efforts from the community, academia, and industry. More challenges, interplays, and tradeoffs in scalability, privacy, and security need to be investigated in a more holistic and comprehensive manner by the community. We are expecting broader, deeper, and greater evolution of these concepts and technologies, and confluence towards holistic trustworthy AI ecosystems. This workshop provides an open forum for researchers, practitioners, and system builders to exchange ideas, discuss, and shape roadmaps towards scalable and privacy-preserving federated learning in particular, and scalable and trustworthy AI ecosystems in general.

The purpose of the Neural Information Processing Systems annual meeting is to foster the exchange of research on neural information processing systems in their biological, technological, mathematical, and theoretical aspects. The core focus is peer-reviewed novel research which is presented and discussed in the general session, along with invited talks by leaders in their field. On Sunday is an Expo, where our top industry sponsors give talks, panels, demos, and workshops on topics that are of academic interest. On Monday are tutorials, which cover a broad background on current lines of inquiry, affinity group meetings, and the opening talk & reception. The general sessions are held Tuesday - Thursday, and include talks, posters, and demonstrations. Friday - Saturday are the workshops, which are smaller meetings focused on current topics, and provide an informal, cutting edge venue for discussion.

We invite submissions for the Thirty-Fourth Annual Conference on Neural Information Processing Systems (NeurIPS 2020), a multi-track, interdisciplinary conference that brings together researchers in machine learning, computational neuroscience, and their applications.

ODSC

AI plays an essential role in businesses and potential will be utilized across a wide variety of industries in the future. Join us at the Virtual AI Expo @ODSC APAC 2020, on December 8-9th 2020 to learn about the latest industry trends, stay on top of innovations, and create new opportunities for your business. This is a unique opportunity to access and interact with industry leaders from wherever you are in the world!

Email: info@odsc.com

Data Science, ODSC APAC, AI, Artificial Intellgence

TextGraphs, now going on for more than a decade, is a workshop series promoting the synergies between methods of the field of Graph Theory and Natural Language Processing. The fourteenth edition of the TextGraphs workshop aims to extend the focus on issues and solutions for large-scale graphs, such as those derived for Web-scale knowledge acquisition or social networks, and graph-based and graph-supported machine learning and deep learning methods. TextGraphs is organized online in 2020.

TextGraphs Organizing Committee;     Email: textgraphsoc@gmail.com

natural language processing, graphs, machine learning, semantic networks

Natural Language Processing, Computational Linguistics,    Graph Theory and Combinatorics

Banff International Research Station for Mathematical Innovation and Discovery (BIRS)

Banff's new workshop on Continuum models and optimisation for deep neural networks brings together scientists to discuss the foundations of our digital revolution, and to investigate the reliability of their results. As often, mathematics is the fundamental tool to examine today's challenges. Mathematics structures knowledge and identifies the strengths and limitations of deep learning algorithms. A better understanding of the maths behind deep learning helps us to develop more efficient algorithms and to put safety critical industrial areas such as autonomous driving on a firm ground.

Institute of Information Technology, Vietnam

In the past years, Vietnam Fuzzy Systems Society (VFSS) organized successfully many artificial intelligence and fuzzy systems in such as VJFUZZY'98, MIF'99, VJFUZZY'2001, VJMEDIMAG'2001, Intech/VJFuzzy'2002, AFSS'2004, VN-KR MEDINFO'2005. In January of 2020, we organized successfully AICI’2020 at the Thang Long University, Vietnam. In the next year, the Second International Conference on Artificial Intelligence and Computational Intelligence (AICI 2021), 15-16 January, 2021, will be organized by Institute of Information Technology, Vietnam Academy of Science and Technology with the sponsor of the International Fuzzy Systems Association (IFSA). This conference aims at bringing together researchers in Artificial Intelligence and Computational Intelligence and related topics for an opportunity to present and discuss theoretical and applied research problems as well as to foster research collaborations.

Artificial Intelligence, Big Data, Deep Learning with Biomedical & other Applications

Soft Computing, Evolutionary Computation, Metaheuristic Optimization, Fuzzy Logic,    Natural Language Processing, Computational Linguistics

Association for the Advancement of Artificial Intelligence (AAAI)

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.

The International Conference on Pattern Recognition Applications and Methods is a major point of contact between researchers, engineers and practitioners on the areas of Pattern Recognition and Machine Learning, both from theoretical and application perspectives. Contributions describing applications of Pattern Recognition techniques to real-world problems, interdisciplinary research, experimental and/or theoretical studies yielding new insights that advance Pattern Recognition methods are especially encouraged. Papers describing original work are invited in any of the areas listed below. Accepted papers, presented at the conference by one of the authors, will be published in the proceedings of ICPRAM with an ISBN. Acceptance will be based on quality, relevance and originality. There will be both oral and poster sessions. Special sessions, dedicated to case-studies and commercial presentations, as well as technical tutorials, dedicated to technical/scientific topics, are also envisaged: companies interested in presenting their products/methodologies or researchers interested in presenting a demo or lecturing a tutorial are invited to contact the conference secretariat.

Phone: [+351 265 520 185];     Email: icpram.secretariat@insticc.org

Modeling and Simulation,    Pattern Recognition and Image Processing, Machine Vision

The purpose of the International Conference on Agents and Artificial Intelligence is to bring together researchers, engineers and practitioners interested in the theory and applications in the areas of Agents and Artificial Intelligence. Two simultaneous related tracks will be held, covering both applications and current research work. One track focuses on Agents, Multi-Agent Systems and Software Platforms, Distributed Problem Solving and Distributed AI in general. The other track focuses mainly on Artificial Intelligence, Knowledge Representation, Planning, Learning, Scheduling, Perception Reactive AI Systems, and Evolutionary Computing and other topics related to Intelligent Systems and Computational Intelligence.

The Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-21) is a venue for papers describing highly innovative realizations of AI technology. The objective of the conference is to showcase successful applications and novel uses of AI. The conference will use technical papers, best practice papers, invited talks, and panel discussions to explore issues, methods, and lessons learned in the development and deployment of AI applications; and to promote an interchange of ideas between basic and applied AI and the discourse on the actual deployment of AI in practice.

Institute of Pure and Applied Mathematics (IPAM), UCLA

In recent years, deep learning has significantly improved the fields of computer vision, natural language processing and speech recognition. Beyond these traditional fields, deep learning has been expended to quantum chemistry, physics, neuroscience, and more recently to combinatorial optimization (CO). Well-known CO problems are Travelling Salesman Problem, assignment problems, routing, planning, Bayesian search, and scheduling. CO is basically used every day in finance and revenue management, transportation, manufacturing, supply chain, public policy, hardware design, computing and information technology. The workshop will bring together experts in mathematics (optimization, graph theory, sparsity, combinatorics, statistics), CO (assignment problems, routing, planning, Bayesian search, scheduling), machine learning (deep learning, supervised, self-supervised and reinforcement learning) and specific applicative domains (e.g. finance, transportation, hardware design, computing and information technology) to establish the current state of these emerging techniques and discuss the next directions. Besides, such generalization of deep learning techniques to CO problems will also push forward the mathematical analysis of the properties of these learning systems like generalization and transfer, stochastic optimization and dynamic predictivity that make the success of these techniques.

Graph Theory and Combinatorics,    Operational research

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Courses and Events for Math Students and Early Career Researchers,    Analysis

SEG - Society of Exploration Geophysicists

The most significant contribution of this event is the Emergence of the utilization of data analytics and machine learning for geoscience. This workshop is designed to showcase the successes and challenges of practicing machine learning and data analytics in the geoscience domain to improve accuracy and efficiency of algorithms and/or workflows. For example, in addition to existing applications such as seismic geobody identification and well log data analysis, what other challenging geoscience problems can be formulated and solved effectively by machine learning? How can machine learning algorithms and workflows be tailored to meet the specific physical constraints of geoscience data? How can we fully exploit the power of machine learning and physics-based approaches?

Geophysics and Geology,    Metrology and Instrumentation

Lake Como School of Advanced Studies

The school brings together experts in emerging photonic technologies, machine learning techniques, and fundamental physics who will share with young researchers their knowledge and interdisciplinary approaches for understanding and designing complex photonic systems and their practical applications. In the new era of artificial intelligence, algorithms and computational interfaces are broadly emerging as novel tools to do scientific research. The paradigms of machine learning also inspire interpretations and methodologies, in both theories and experiments. Nonlinear, quantum and bio-photonics, as well as optical communications, are surprisingly influenced by these new ideas. The summer school is aimed to explore machine learning applications in the specific fields of nonlinear optics and photonics.

machine learning methods and complexity of optical communication systems, including topics such as the nonlinear Fourier transform and transmission over multimode fibres; complexity in quantum systems emulated in photonics (including optical computing); complexity of emerging novel materials, device and components such as micro-resonators and plasmonic nanostructures. Importantly, the complexity in bio-medical photonic applications will be also considered as a high priority topic

Optics and Lasers,    Photonics, Optoelectronics and Display Devices

DLU organizers

DLU is a new format for an online-only conference focusing on Deep Learning. You do not only submit your paper, but also your presentation video. Both your paper AND your talk will be reviewed by two independent reviewers. The goal is not only to filter for very good papers, but also to encourage submissions that provide an excellent presentation of their work in a talk. If your paper AND your talk are of good to excellent quality, both will be published on the DLU website in a digital lecture hall.

DLU organizers;     Phone: [0049(0)831-2523-9250];     Email: dlu@deep-learning-update.org

Deep Learning, Machine Learning, Pattern Recognition, Artificial Intelligence, Computer Vision, Natural Language Processing, AI Accelerators

Natural Language Processing, Computational Linguistics,    Computing Hardware

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

ICERM - The Institute for Computational and Experimental Research in Mathematics

Deep learning is profoundly reshaping the research directions of entire scientific communities across mathematics, computer science, and statistics, as well as the physical, biological and medical sciences . Yet, despite their indisputable success, deep neural networks are known to be universally unstable. That is, small changes in the input that are almost undetectable produce significant changes in the output. This happens in applications such as image recognition and classification, speech and audio recognition, automatic diagnosis in medicine, image reconstruction and medical imaging as well as inverse problems in general. This phenomenon is now very well documented and yields non-human-like behaviour of neural networks in the cases where they replace humans, and unexpected and unreliable behaviour where they replace standard algorithms in the sciences.

Phone: [4018635030];     Email: programstaff@icerm.brown.edu

Banff International Research Station for Mathematical Innovation and Discovery (BIRS)

Recently a variety of state-of-the-art methods in machine learning and artificial intelligence have been developed motivated by techniques from Stein’s method, a successful tool from the field of probability theory. These methods have enabled efficient analysis of the large amounts of data being produced in several scientific fields, like neuroscience, information technology, and finance. Motivated by this success, there has been an ever increasing interest in exploring further connections between Stein’s method and machine learning. The focus of this workshop is to consolidate isolated efforts and develop a theoretically principled inferential and computational framework via Stein's method for analyzing increasingly complex models and data objects. This workshop is intended to bring together prominent and promising young and diverse researchers working on Stein’s method and machine learning, and to charter the path for future development in the field.

Kavli Institute for Theoretical Physics (KITP)

The Large Hadron Collider (LHC) is the world’s facility for probing fundamental physics at the electroweak scale and well beyond. As it enters a new phase of extended data accumulation, two broad challenges emerge: how to fulfill the potential for percent-level precision with the large dataset, and how to maximise the information that can be extracted from each event about the underlying scattering process, in particular with machine learning. Solving these problems will have an impact across a wide range of physics topics: establishing the properties of the newly discovered interactions of the Higgs sector and understanding electroweak symmetry breaking, enhancing the sensitivity of searches for physics beyond the Standard Model (BSM), and precision measurements of a range of fundamental parameters in the Standard Model.

MRSI – Mathematical Sciences Research Institute, Berkeley

The talks in this workshop will present a wide array of current applications of topology in neuroscience, including classification and synthesis of neuron morphologies, analysis of synaptic plasticity, algebraic analysis of the neural code, topological analysis of neural networks and their dynamics, topological decoding of neural activity, diagnosis of traumatic brain injuries, and topological biomarkers for psychiatric disease. Some of the talks will be devoted to promising new directions in algebraic topology that have been inspired by neuroscience.

Geometry and Topology,    Neurology

Ai4

The Ai4 2021 Healthcare Summit gathers business leaders and data practitioners to facilitate the adoption of artificial intelligence and machine learning within the healthcare industry.

Email: jessica@ai4.co

healthcare, medical devices, drug discovery, biotech, artificial intelligence, machine learning

Healthcare Technologies,    Pharmacology and Drug Development

The Fields Institute for Research in Mathematical Sciences

Graph Theory and Combinatorics,    Geometry and Topology

EURO Working Group on Decision Support Systems

The EURO Working Group on Decision Support Systems invites you to participate in the ICDSST 2021 International Conference on Decision Support System Technology on Decision Support Systems, Analytics and Technologies in response to Global Crisis Management in Loughborough, UK. The Conference will be hosted at the School of Business and Economics of the Loughborough University, during the period of May 26th to May 28th, 2021.

Operational research,    Multidisciplinary or General Events in Informatics

The AIBC Summit brings together thousands of investors and innovators in Blockchain, Artificial Intelligence, Quantum Technology, Big Data and the Internet of Things.

The state-of-the-art image processing research works are dedicated to cover a wide range of computational intelligence techniques with a completely new way of neural networks organization concept called Capsule Networks [CapsNets] that opens up a new era of advanced image-processing applications. It is being organized on May 27-28, 2021 in association with King Mongkut’s University of Technology Thonburi, Thailand, Dayeh University, Taiwan, and Tribhuvan University, Nepal. Moreover, the 2nd International Conference on Image Processing and Capsule Networks [ICIPCN 2021] initiates a capsule network perspective to leverage an authoritative and detailed representation to deliver an enhanced image and video recognition and adaptive processing mechanisms which were closely related to the humanistic way of thinking. This extended ICIPCN 2021 conference will be a dedicated platform for researchers, academicians and scholars to share and exchange their valuable research insights, which may clearly define the image and the family of image processing techniques and applications. Henceforth, this premier International conference motivates the researchers to discover more information from images and perform innovative image analysis procedures by efficiently utilizing the evolving capsule network models.

Phone: [09600368297];     Email: icipcn.conf@gmail.com

Image Processing Image recognition and Analysis Image Registration Image segmentation and edge detection Image texture analysis Medical imaging systems Image acquisition, reconstruction and synthesis Feature Extraction techniques Medical image diagnosis Image reconstructions and losses Medical interpretability and explainable deep learning frameworks Image processing for multispectral images Image enhancement and restoration Image formation principles Pattern recognition and capsule networks in object tracking Face and gesture recognition techniques Genetic algorithms Signal identification and representation Speech and audio processing Optical signal processing Capsule based biometric technologies Cognitive vision of image processing Multi-fusion imaging Capsule Networks Capsules in image analysis Deep learning in image analysis Pattern recognition Machine Learning Data mining Big data analytics and imaging Visual content analysis Fuzzy systems Human-visual systems Robotic vision of image processing Capsules in adaptive image processing Machine learning in capsule neural networks Capsule implementation in image systems Capsules and digital image processing techniques Routing mechanisms Machine Intelligence Artificial neural networks Artificial Intelligence Techniques

Barcelona GSE Data Science Center

The meeting aims to bring together leading experts from diverse areas of mathematical statistics and machine learning who are interested in the mathematical foundations of our fields. The common theme of the meeting is modelling and statistical analysis of data from large complex systems, which leads to high-dimensional and structured problems.

The Fields Institute for Research in Mathematical Sciences

Scheduled as part of the Focus Program on Data Science, Approximation Theory, and Harmonic Analysis

ICAS

Since 2015, the LOD Conference brings academics, researchers and industrial researchers together in a unique interdisciplinary community to discuss and present the state of the art and the latest advances in the integration of machine learning, optimization and data science to provide and support the scientific and technological foundations for interpretable, explainable and trustworthy AI. Since 2017, LOD adopted the Asilomar AI Principles.

Event Secretariat;     Email: lod@icas.cc

artificial intelligence, deep learning, machine learning, optimization, big data, data science, optimization, nonlinear optimization, multi-objective optimization

Virtue Insight

IOT is changing the world around us and with ‘Digital India’ and the ‘Smart Cities Mission,’ is using technologies to offer a slew of smart services that are efficient, sustainable, accessible and affordable. Smart city solutions such as smart transportation, smart infrastructure, smart energy, smart communications, smart lighting etc… According to markets, the global blockchain technology is expected to rise upto $2.31bn by 2021. Research provides strong evidence that blockchain applications could transform existing business models and invent new forms of business in a profound way. Function using integrated technologies, such as IoT, cloud computing and artificial intelligence. These solutions reduce costs for governments, citizens and enterprises alike. Enterprise and industrial markets are poised to become the biggest areas where the Internet of Things will be implemented. This summit will explore the impact of the Internet of Things (IoT), AI & Blockchain on industries, such as manufacturing, transport, supply chain, insurance, logistics, government, energy and automotive.

Email: kavitha@virtueinsight.co.in

Blockchain, Artificial Intelligence, IoT, AI, interntet of things, BigData, technology, Sensors, Wireless

Internet of Things (IoT) and Sensor Networks,    Cryptography, Blockchain and Information Security

The Society for Imprecise Probability: Theories and Applications

ISIPTA is the primary international forum about theories and applications of imprecise probability. The symposium is open to contributions on all aspects of imprecise probability, which is a generic term for the many mathematical and statistical models and methods that allow us to measure chance or uncertainty without the restriction of sharp probabilities. This includes (but is not limited to) sets of probability measures, partial preference orderings, game-theoretic probability, choice functions, interval probabilities, belief functions, and possibility theory.

Probability and Statistics, Game Theory,    Applied Mathematics (in general)

ICAS

The Advanced Course is not a summer school suited only for younger scholars. Rather, a significant proportion of seasoned investigators are regularly present among the attendees, often senior and junior faculty at their own institutions. The balanced audience that we strive to maintain in each Advanced Course greatly contributes to the development of intense cross-disciplinary debates among faculty and participants that typically address the most advanced and emerging areas of each topic. Each faculty member presents lectures and discusses with the participants for one entire day. Such long interaction together with the small, exclusive Course size provides the uncommon opportunity to fully explore the expertise of each faculty, often through one-to-one mentoring. This is unparalleled and priceless. The Certosa di Pontignano provides the perfect setting to a relaxed yet intense learning atmosphere, with the stunning backdrop of the Tuscan landscapes. World-class wines and traditional foods will make the Advanced Course on Data Science and Machine Learning the experience of a lifetime.

Course Secretariat;     Email: acdl@icas.cc

Artificial Intelligence, Big Data, Cognitive Computing, Computational Cognitive Science, Constraint-Based Approaches to Machine Learning, Data Science, Deep Learning, Explainable Artificial Intelligence, General Reinforcement Learning Algorithms, Generative Adversarial Networks, Machine Learning, Probabilistic Generative Models, Probabilistic Programming, Reinforcement Learning, Robotics, Theory of Deep Learning,

Software Agents and Intelligent Agents in Artificial Intelligence,    Training in Computer Science, Courses

Mathematisches Forschungsinstitut Oberwolfach (MFO, Oberwolfach Research Institute for Mathematics)

Rohini College of Engineering & Technology, Tamil Nadu, India.

The emerging modern mobile robotic systems and intelligent information systems are becoming increasingly ubiquitous and distributed, where it is intended to operate in a highly dynamic and continuously fluctuating societal and economic environments. Moreover, the introduction of autonomous systems has revolutionized wide range of applications like agriculture, healthcare, education, military, industries, and so on. The incorporation of machine learning algorithms will make these autonomous system to become more robust and efficient under diverse societal and environment conditions. This International Conference on Machine Learning and Autonomous Systems [ICMLAS 2021] hosted and organized by Rohini College of Engineering and Technology, Tamilnadu India on 24-25 September 2021 will be an interdisciplinary platform for the researchers to contribute their research works that address the state-of-the-art technologies, development, and methodologies for the futuristic intelligent autonomous system developments and applications.

Conference Chair & Convener Principal,;     Phone: [+91-9600368297];     Email: icmlas.conf@gmail.com

Machine Learning: Computational learning theory and applications, Knowledge discovery and acquisition, Cognitive modelling and data analysis techniques, Hybrid learning algorithms, Data and knowledge representation models, Deep learning approaches, Mutli-agent systems and learning models, Support vector machine, Intelligent information retrieval techniques, Reinforcement learning approaches, Fuzzy-based learning approaches, Machine learning for web and social network mining, Intelligent feature extraction techniques, Mobile data mining and analysis, Parallel and distributed learning algorithms, Statistical and analytical learning, Scalability and reliability of learning algorithms. Autonomous Systems: Theoretical foundations for autonomous systems, Complex and adaptive autonomous systems, Autonomous computing platforms and applications, Cognition-inspired autonomous systems, Multi-autonomous systems and applications, Autonomous algorithms and models, Adaptive and autonomous robots, Real-time autonomous systems, Smart and distributed autonomous systems, Autonomous software and operating systems, Autonomous sensors and embedded systems, Optimization and control algorithms for autonomous systems, Novel control models and structures for autonomous systems, Learning, adaptation, and estimation methods for autonomous systems, Innovative applications of autonomous systems: healthcare, agriculture, industries, military, smart cities, smart home, education, and so on.

CIRM – Centre International de Rencontres Mathématiques

Probability and Statistics, Game Theory,    Algorithms

Casa Matemática Oaxaca (CMO) in Mexico, and the Banff International Research Station for Mathematical Innovation and Discovery (BIRS) in Banff, Canada

The incredible advances in artificial intelligence applied to images need to be combined with geometric tools to be applied in higher dimensional data and for applications to 3D objects, such as those in Augmented Reality, Virtual Reality environments, data from sensors of self-driving cars, computational anatomy, and other domains of technological applications. In this workshop we will bring together experts from academia, government stakeholders, applied researchers from industry, as well as graduate students and early career scientist to interact and develop novel solutions that apply abstract tools from high dimensional geometry to contribute to the solution of these problems.

CIRM – Centre International de Rencontres Mathématiques

Banff International Research Station for Mathematical Innovation and Discovery (BIRS)

The workshop focuses on the novel mathematical challenges of statistics and machine learning. The spectacular success of machine learning in a wide range of applications opens many exciting theoretical challenges in a number of mathematical fields, including probability, statistics, combinatorics, optimization, and geometry. BIRS will bring together researchers of machine learning and mathematical statistics to discuss these problems. The principal topics include combinatorial statistics, online learning, and deep neural networks.

Courses and Events for Math Students and Early Career Researchers,    Pattern Recognition and Image Processing, Machine Vision