seabet app download :00-11:30
Report location: Information Building535Smart Academic Lecture Hall
Reporter and report introduction:
Liu Xinwang
，Professor, School of Computer Science, National University of Defense Technology，Doctoral Supervisor。National Outstanding Youth、 Excellent Youth Winner。Main research interests include machine learning、Data mining, etc.。Being the first or corresponding author in the past five yearsMore than 80 papers published in CCF Class A top journals and top conferences，Including 10 IEEE TPAMI papers，Contains 3 independent authors。12 ESI highly cited papers。More than 14,000 Google Scholar citations，Selected into the list of the world’s top 2% scientists in 2022。Served as IEEE TNNLS、seabet app download IEEE TCYB、Information Fusion and other journals AE and ICML、Senior program committee member/area chairperson of top conferences such as NeurIPS。Part of the research results have won the first prize of Hunan Province Natural Science Award twice (2/6、6/6）。
>>报告Title: Theoretical methods and applications of cluster analysis
>>报告Introduction
Aiming at the diversity of data characteristics in cluster analysis、Challenges such as non-completeness and weak learnability，This report will introduce the research group’s fusion mechanism in multi-view clustering、Non-complete multi-view clustering、A series of innovative results have been achieved in deep clustering and other aspects: a new theory on how to make full use of different types of features to improve clustering performance has been established、Proposed a new method for cluster filling to deal with non-complete multi-view clustering、Exploring new applications of learning features from raw data to optimally seabet online sports betting serve clustering。It is planned to carry out continuous cluster analysis to cope with dynamic changes in data。
Bai Liang，Director of the Institute of Intelligent Information Processing of Shanxi University，Professor，Doctoral Supervisor，Winner of National Outstanding Youth Fund。Main research direction is machine learning，Focus around cluster analysis、Semi-supervised learning、Self-supervised learning and other research projects have been carried out，Related research results published inAIJ、IEEE TPAMI、IEEE TKDE、DMKD、ICML、KDD、AAAI and other important international academic journals and conferences，Presided over the new generation of artificial intelligence major project of the Ministry of Science and Technology、National Natural Science Foundation of China Outstanding Youth、Superior items，Won the Outstanding Doctoral Thesis Award from the Chinese Society for Artificial seabet app download Intelligence、Shanxi Province Science and Technology Award (Natural Science Category) First Prize and other awards。
>>报告Title: Supervisory information enhancement guided by data relationships
>>报告Introduction
Inadequate supervision information is one of the key challenges facing machine learning。How to use the large amount of naturally existing unlabeled data to improve the generalization of the model is a key research topic in the field of machine learning and data mining。This report will mainly introduce how to mine and utilize the correlation of data to achieve supervisory information enhancement，And report to everyone on the research team’s progress in unsupervised learning、Related research progress in self-supervised learning and semi-supervised learning。
Zheng Kai
，Professor of University of Electronic Science and Technology of China，Doctoral Supervisor，National Youth Distinguished Expert。The main research field is spatiotemporal data analysis、Trajectory calculation、Automatic driving algorithm、Smart database (AI4DB）、Spatial Crowdsourcing、Recommendation system, etc.。In database、More than 200 papers published in important conferences and journals in data mining and other fields，More than 20 authorized invention patents，More than 11,000 Google Scholar citations, H index 53。IEEE Senior Member，Served as an editorial board member of TKDE and chairperson of several important international conferences、Program Chair and PC。Dedicated to the government for many years、Enterprise and personal applications provide intelligent data management、Efficient solutions for fusion and analysis，Has hosted and participated in a number of Australian and Chinese Natural Science Foundation projects。
>>报告Title: Large-scale vector search technology: trends and challenges
>>报告Introduction
The widespread application of deep learning technology and large models has generated massive amounts of vector data，Efficient vector indexing and search technology are not only the core competitiveness of vector seabet app download databases，It also plays a vital role in its upper large model application。This report will review the basic concepts and mainstream methods of large-scale vector search technology，Introducing the latest progress in vector search technology in recent years，And discuss its future development
