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ACMSC

2023 5th International Conference on Information Technology and Computer Communications (ITCC 2023) will be held during June 15-17, 2023 in Tianjin, China.

ITCC 2023 is supported by Tianjin University of Technology and Education and ACM Singapore Chapter and some other universities and Societies.

Email: amychou2020@163.com

Information Technology; Information Theory; Automata Theory; Artificial & Computational Intelligence; Control Theory; Communication Technologies; Digital communication technologies; Satellite communication technologies; Wireless network communication technologies;

CZES-nd

2023 The 3rd International Conference on Computer Vision and Information Engineering (CVIE 2023) will be held in Guiyang, China during July 20-22, 2023.

Email: Nazal@sina.com

Active and robot vision; Invariance in pattern recognition; Biometric authentication; Knowledge-based recognition; Camera networks and vision; Statistical pattern recognition; Face and gesture recognition; Algorithms and bioinformatics; Geographical information systems; Artificial intelligence; Global navigation satellite systems; Automated software engineering; Grid and scalable computing;

Institute for Advanced Study in Mathematics (IASM) in Hangzhou, China

We have lately witnessed one-after-another ground-breaking developments in the AI world. Data science is the essence of this world and perhaps the fastest expanding domain. At the same time, data science is born from the interaction of multiple research areas including statistics and machine learning. The fundamental statistical principles formed a pillar of data science in the beginning and remain pivotal for its healthy growth. The powerful algorithms developed in computer science keep data science practically relevant and central in Big Data analytics. Promoting the interactions between these two areas will undoubtedly further advance the development of data science. Latent structure models are powerful products of statistical principles and offer a simple yet effective platform to capture the complexity and heterogeneity in big data. Their usage goes beyond any single discipline, and naturally integrates the advantages of various areas such as statistics, economics and machine learning. This workshop brings together researchers with expertise in latent structure learning and provides a platform to share their achievements, exchange research ideas, and build new collaborations. We wish to promote the use of latent model techniques and simulate further development of highly interpretable, reproducible, and powerful AI methods. The workshop covers a broad range of topics in the latent structure model: theory, algorithms, and applications. We will also set eyes on future research trends and interdisciplinary directions.