The CAAI-AIDL workshop is hosted by the Chinese Association for Artificial Intelligence (CAAI) and led by academician Tieniu TIAN, vice chairman of the CAAI. It aims to help students concentrate on the basic theory, latest developments and landing directions in this field in a short time, and promotes the mutual exchange of related practitioners in AI industry, academia and research institutions.
This workshop is of great significance to masters, doctors, young teachers, relevant practitioners of enterprises and institutions, and enthusiasts who are expected to switch to the field of AI.
CAAI-AIDL has been successfully held three times. The first three themes were "How Deep Learning Promotes AI Development" (Academic Director: Jianhua TAO), "Machine Learning Frontier" (Academic Director: Zhihua ZHOU), and "Big Data: Theory and Application" ( Academic Director: Xueqi CHENG).
AIDL4 "Intelligent Perception and Interaction"
The third wave of artificial intelligence has actually arrived. Artificial intelligence is no longer a concept, but is actually affecting people's lives. One of the main development directions of artificial intelligence is perception intelligence. Perceived intelligence, that is, perception, hearing, touch, etc. What level of perception intelligence has developed to? Has artificial intelligence approached or surpassed humans? How will machines interact with the world after they perceive it? This workshop aims to help students concentrate on the basic theory, latest developments and landing directions in this field in a short time, and promotes the mutual exchange of related practitioners in AI industry, academia and research institutions. It is of great significance to masters, doctors, young teachers, relevant practitioners of enterprises and institutions, and enthusiasts who are expected to switch to the field of AI. Professor Yunhong WANG, vice president of computer college in Beihang University, will attend as the academic director of this workshop!
September 22-24, 2017, Beijing. Institute of Automation, Chinese Academy of Sciences
Yunhong WANG is professor and deputy dean of the School of Computer Science and Engineering, Beihang University, director of the China Computer Federation (CCF), executive director of the CAAI and China Society of Image and Graphics (CSIG), and director of the Intelligent Interaction Professional Committee of the CAAI. He is also the editorial board member of "Transactions on Information Forensics and Security", an A recommended academic journal of IEEE, and IEEE Senior Member. He has done deep research on pattern recognition and image understanding, and his achievements in face recognition, gait recognition, object recognition and information hiding detection are widely cited. He has presided over 16 academic projects including the National Natural Science Foundation, the National High Technology Research and Development Program of China (863 Program), and National Basic Research Program of China（973 Program). He has published more than 200 papers in IEEE Transactions on PAMI and other authoritative domestic and international academic journals and conferences, and his papers have been cited more than 10,000 times by Google Scholar. In 2005, he was selected by the Ministry of Education as one of the outstanding talents of the new century. He was awarded the Second National Technological Invention Award, the first Beijing Science and Technology Award, and the China Youth Science and Technology Award in 2013.
Computer Vision++: Where Do We Go from Here?
Abstract: With the huge successes of deep learning in computer vision, many computer vision problems are seemingly being solved. Where do we go from here? We will discuss a few directions where computer vision can be either further pushed to deal with data scarcity and data noise, or synergistically integrated with other disciplines such as NLP and data mining, to continue to advance the frontiers of artificial intelligence. Introduction: Professor Jiebo LUO is a Fellow of IEEE, SPIE and IAPR. He is a famous international scholar in image processing, computer vision, machine learning, data mining and so on. Professor Jiebo LUO has been a principal scientist at Kodak laboratories for more than 15 years. In the fall of 2011, he joined the Computer Science Department at the University of Rochester.
ProfessorJiebo LUO is the co-chair of some international top conferences like ACM Multimedia 2010, CVPR 2012, and ICIP 2017, editor of the Journal of Multimedia. He also serves as members of the editorial board of top international academic journals like IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), IEEE Transactions on Multimedia (TMM), IEEE On Circuits and Systems for Video Technology (CSVT), Pattern Recognition (PR), and Machine Vision and Applications (MVA). Professor Jiebo LUO'research covers many frontier fields such as image processing, computer vision, machine learning, data mining, medical image analysis, and pervasive computing. He has published more than 300 academic papers, and holds more than 80 U.S. patents.
In recent years, Professor Jiebo LUO has made significant contributions to the study of social multimedia and its social applications.
Sunchun ZHU: A Cognitive Architecture for Human-Machine Teaming
Abstract: The recent advances in fields, such as vision, language and learning have inspired renewed interest in academics and the public for developing general AI machines that are capable of communicating and collaborating with humans. In the first half of this talk, I will discuss my personal assessment of the current state of AI. In short, AI is entering an era of big integration, embracing six areas:
vision, NLP, cognition, learning, robotics and social ethics (game theories). It calls for a unified representation and inference framework for a wide range of tasks. I propose my own solution --- the spatial, temporal and causal and-or graph (STC-AOG) as a unifying representation, and review some ongoing work in these areas. In the second part, I will discuss the layered infrastructures underneath human communication and collaborations, and propose a paradigm called communicative learning to formulate the complexity of human learning and communication, including the theory of mind, i.e. the beliefs and intents of others. Then I will discuss the challenges for constructing a cognitive architecture for human-machine communication and teaming, and the fundamental limit of learning. I will show a few examples of human robot collaborations.
Introduction: He is a global famous computer vision expert, statistic and applied mathematician, and artificial intelligence expert.
He is a professor in the Department of Statistics and Computer Science at the University of California, Los Angeles and the director of the Center for Computer Vision and Image Science. He also serves as a Changjiang Scholar and an IEEE Fellow.
He has published more than 140 papers in computer vision, statistical modeling and reasoning. He has received numerous national and world-class awards in the United States, including three Marr Prize awards from the International Computer Vision Congress (ICCV) and the 2008 Aggarwal Prize from the International Institute for Pattern Recognition (IAPR) , and currently presides over major research projects in the United States.
Chen Enhong: Data Mining Technology and Application for Smart Education
Introduction: Doctor, professor, doctoral supervisor, winner of the National Outstanding Youth Fund, head of the innovation team in key areas of the Ministry of Science and Technology, CCF fellow. He is currently Vice Dean of School of computer Science and Technology, University of Science and Technology of China, Deputy Director of National Engineering Laboratory for speech and language Information processing, and Director of big data key Laboratory for Analysis and Application in Anhui Province. He is a member of the teaching steering committee of computer science of the Ministry of Education, chairman of Anhui computer society, director of China Computer Federation, member of artificial intelligence and pattern recognition special committee, member of database special committee, and member of big data expert committee. He is the vice chairman of knowledge engineering and distributed intelligence professional committee of Chinese Association for Artificial Intelligence and standing member of machine learning special committee. He was the first chairman of the YOCSEF Hefei sub Forum (2011). He is in charge of WWW Journal, IEEE Transactions on System, Man and Cybernetics: System, computer research and development, pattern recognition and artificial intelligence, computer application and other domestic and foreign academic journals, He is also the member of the procedure committee of important international academic conferences such as KDD, AAAI, ICDM, PAKDD, SDM, etc., and chairman of the procedure Committee of national academic conferences NDBC'2012, CCDM'2014, CNCC'2015, etc. He has undertaken the National Natural Science Foundation of China Outstanding Youth Fund Projects, General Projects, Joint Key Fund Projects, 863 Project, National Key R&D Projects and other projects, as well as cooperation projects with Nokia, Alibaba, Huawei, and IFLYTEK. He has published more than 100 academic papers in important academic journals at home and abroad, such as TKDE, TKDD, TMC, TIST, TC and important international academic conferences in the field of data mining, such as KDD, WWW, SIGIR, ICDM, NIPS, ECML-PKDD, CIKM, etc. He won the best applied paper award of KDD2008, the best research paper award of ICDM2011, and the best paper nomination award of SDM2015. He has won the second prize of Natural Science of the Ministry of Education in 2012, and won the Outstanding Mentor Award of the Chinese Academy of Sciences and the Zhu Liyuehua Outstanding Teacher Award of the Chinese Academy of Sciences. The doctoral students under his guidance won Excellent Doctoral Thesis Awards from the Chinese Academy of Sciences, China Computer Federation and Chinese Association for Artificial Intelligence, as well as the Special Award and Excellent Award of the president of the Chinese Academy of Sciences.
Gu Jiawei: The Man-Machine Symbiosis World With Animism
Introduction: CEO and co-founder of Ling. It is committed to create innovative products and experiences based on the combination of artificial intelligence technology and relational human-computer interaction, and build an intelligent life of "all things have spirit". Through creating a sense of life AI-IOT consumer brand, it ultimately achieves a spiritual world of human and machine symbiosis. Gu Jiawei graduated from Tsinghua University, and he is former head of human-computer interaction of Baidu Artificial Intelligence Research Institute and former researcher of Microsoft Research Institute. He has 22 U.S. invention patents covering hardware and software, and more than 120 domestic patents. He is a guest supervisor of Stanford University's ME310 international innovation course. In 2016, he was selected as MIT TR35's world's 35 science and technology innovators by technology review of MIT. In 2015, he was rated as China's most potential designer by Forbes Forbes.
Lu Jiwen: Depth Measurement Learning For Visual Content Understanding
Abstract: Deep metric learning is a hot topic in the field of deep learning, which has achieved good performance in multiple visual content understanding. The report will first introduce the basic concepts and related research progress of deep metric learning, and then focus on a series of representative deep metric learning methods. It includes discriminant depth metric learning, deep migration metric learning, deep coupling metric learning, deep local metric learning, multi view deep metric learning, deep hashing metric learning and multi manifold deep metric learning. And their applications in face and attribute recognition, pedestrian tracking and recognition, cross modal recognition and retrieval of multiple visual content understanding tasks.
Introduction: associate professor and doctoral supervisor of Automation Department of Tsinghua University. His main research interests are computer vision, pattern recognition and machine learning, His research specifically include deep learning, metric learning, face recognition and video analysis. He has published more than 50 papers on CCF class a journals (including 7 papers on PAMI). He was cited more than 1000 times in SCI and 3700 times in Google Scholar. He is a member of the Technical Committee on multimedia systems and applications of IEEE Institute of circuits and systems, a member of the Technical Committee on information forensics and security of IEEE Institute of signal processing He is the editorial board member of 4 international journals such as pattern recognition, guest editorial member of 5 special international journals such as computer vision and image understanding, and field chairman of 10 international conferences such as ICIP.
Mei Tao: Deep Visual Understanding
Abstract: Since the 1960, computer vision scientists have been working to make machines understand and describe what they see. In recent years, the rise of deep learning promotes the rapid development of computer vision research. Some scientists believe that computer vision has acquired the visual ability equivalent to that of young people (such as three years old), which makes the visual based dialogue between human and computer possible. In this report, we will review the development of computer vision, especially visual understanding in the past 50 years, including fine-grained image recognition, video feature learning and recognition, as well as the latest research results of vision and language. His research team is currently working on the in-depth understanding, analysis and application of videos and images. He is also the editorial board member of IEEE and ACM Multimedia (IEEE TMM and ACM TOMM), Pattern Recognition and other academic journals, and is the conference chairman and program committee chairman of several international multimedia conferences (such as ACM Multimedia, IEEE ICME, IEEE MMSP, etc.).
Introduction: Researcher, Institute of computing, Chinese Academy of Sciences. Mainly engaged in image processing and understanding, computer vision, pattern recognition, intelligent human-computer interface research. More than 100 papers have been published in academic journals and conferences at home and abroad, including IEEE Trans. on PAMI, IEEE Trans. on image processing, CVPR, ICCV, ECCV, etc. The paper on manifold distance completed in cooperation with doctoral students won the CPVR2008 Best Student Poster Award Runner-up. He is currently the editorial board member (AE) of Neurocomputing, an international academic journal. He has been the reviewer of more than ten important international journals and domestic primary journals (computer field) for a long time.
Tao Hianhua: Multi-Channel Natural Man-Machine Dialogue
Abstract: The goal of multi-channel natural man-machine dialogue is to make the communication between computer system and users as natural and smooth as that between people. In addition to oral interaction, people will naturally use multimodal information such as expressions and gestures to assist in dialogue. The difficulty of multi-channel natural man-machine dialogue is to effectively receive, fuse and analyze the user behavior information from different channels, and accurately judge the user's intention. The report mainly introduces the development and current progress of multi-channel natural human-computer dialogue, and also discusses the future development of multi-channel natural human-computer dialogue. Introduction: Researcher and doctoral supervisor of Institute of Automation, Chinese Academy of Sciences; Deputy director of State Key Laboratory of Pattern Recognition; winner of National Science Fund for Distinguished Young Scholars. He obtained a bachelor's degree and a master's degree from the Department of Electronics of Nanjing University In 1993 and 1996, and a doctor's degree from the Computer Department of Tsinghua University in 2001. His main research includes: speech synthesis and recognition, speech coding, human-computer interaction, multimedia information processing and pattern recognition. He is the subject editor of
Yao Li: Intelligent Interaction and Application Based on Neurophysiological Information
Introduction: Dean of School of Information Science and Technology, Beijing Normal University, main member of State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University. He is also a member of the China Education Society of Electronics (CESE) and a member of the medical neuro-engineering branch of Chinese Society of Biomedical Engineering (CSBME). He has presided over a number of National Natural Science Foundation projects (including key projects, major research projects, overseas young scholars cooperative research fund projects, general projects), one 863 project, and key projects of Beijing Natural Science Foundation. More than 20 SCI papers and more than 40 EI papers have been published in recent five years.