題目:

人工智慧在音樂的應用

時間:

Oct. 7, 2021 (Thursday) 14:00-15:00

大綱:

深度學習在2012年之後又再一次點燃人工智慧的第三波革命。這一波的進展影響既廣且深，到現在還沒有趨緩的跡象。本演講將以深度學習在音樂的應用為主軸，說明如何將該類型的學習方式適切地融入相關應用中，並讓所設計的系統，達到最令人滿意的效果。

簡介:

廖弘源1981年由國立清華大學取得物理學士，並於1990年取得美國西北大學電機博士。1991年7月應聘回中央研究院資訊所，2012年升為特聘研究員。他於1997年至2000年間擔任資訊所副所長，並於2018年8月受聘為資訊所所長。

廖博士致力於多媒體訊號處理、影像處理、以視訊為主的人類行為分析、三維圖形的分割及辨識等研究領域超過25年。曾任IEEE Signal Processing Magazine、 IEEE Transactions on Image Processing (2009-2013)、IEEE Transactions on Information Forensics and Security(2009-2012)等期刊的編輯，目前亦擔任ACM Computing Survey的副編輯。

廖博士曾獲得許多獎項，包括中央研究院年輕學者著作獎（1998，國科會傑出研究獎(2003、2010及2013)，以及中央研究院深耕計畫獎(2010)。他也獲得中華民國資訊學會博士論文指導獎。 2016年他獲得東元科技獎；他因在image and video forensics and security的貢獻，於2013 年獲選為 IEEE Fellow。廖博士另於2020年獲得教育部第六十三屆學術獎。

題目:

Design-Thinking for Artificial Intelligence

時間:

Oct. 7, 2021 (Thursday) 15:30-16:10

簡介:

Trista is a tech executive, entrepreneur, and AI scientist. She is currently the Chief AI Officer at Inventec Corp., a world-leading computer and electronics manufacturer with annual revenue of more than 16 billion USD. She leads Inventec in smart manufacturing, health and medical AI, robotics, and autonomous machines. Previously, Trista held leadership positions at startups and research labs. At Cognitive Networks, which was later acquired, she led the algorithm and data team. At Intel, she conducted research on computer-vision (CV) algorithm and hardware co-design. With the Intel team, she also developed the world's most widely adopted CV software, OpenCV, which has been downloaded 18 million times as of now. At Nvidia, she architected Nvidia's first video processor. Trista received her Ph.D. from Carnegie Mellon University. She co-authored 30+ publications, 50+ issued and pending patents, gave keynotes and invited lectures at conferences and universities, and frequently received media interviews.

題目:

Exploration Through Reward Biasing: Bandit Learning via Reward-Biased Maximum Likelihood Estimation

時間:
Oct. 7, 2021 (Thursday) 16:20-17:00

簡介:

Dr. Ping-Chun Hsieh joined the Department of Computer Science at National Chiao Tung University (NCTU) as an assistant professor in August 2019. He received his Ph.D. degree in Electrical and Computer Engineering at Texas A&M University in August 2018. Prior to his Ph.D., he received his B.S. in Electrical Engineering and his M.S. in Electronics Engineering from National Taiwan University in 2011 and 2013, respectively. His research interests include reinforcement learning, multi-armed bandits, Bayesian optimization, and wireless networks. His research received the Best Paper Awards from ACM MobiHoc 2020 and ACM MobiHoc 2017. He is a recipient of Junior Faculty Award (黃培城青年講座) from NCTU in 2020, Young Scholar Fellowship from the Ministry of Science and Technology (MOST) in 2019, the Outstanding Ph.D. Student Award from the ECE Department at Texas A&M University in 2016, and the Government Scholarship to Study Abroad from the Ministry of Education, Taiwan.

題目:

Unbiased risk estimators can mislead: A case study of learning with complementary labels

時間:
Oct. 8, 2021 (Friday) 9:20-10:00

簡介:

Prof. Hsuan-Tien Lin received a B.S. in Computer Science and Information Engineering from National Taiwan University in 2001, an M.S. and a Ph.D. in Computer Science from California Institute of Technology in 2005 and 2008, respectively. He joined the Department of Computer Science and Information Engineering at National Taiwan University as an assistant professor in 2008, and was promoted to an associate professor in 2012, and has been a professor since August 2017. Between 2016 and 2019, he worked as the Chief Data Scientist of Appier, a startup company that specializes in making AI easier in various domains, such as digital marketing and business intelligence. Currently, he keeps growing with Appier as its Chief Data Science Consultant.

From the university, Prof. Lin received the Distinguished Teaching Award in 2011, the Outstanding Mentoring Award in 2013, and the Outstanding Teaching Award in 2016, 2017 and 2018. He co-authored the introductory machine learning textbook Learning from Data and offered two popular Mandarin-teaching MOOCs Machine Learning Foundations and Machine Learning Techniques based on the textbook. His research interests include mathematical foundations of machine learning, studies on new learning problems, and improvements on learning algorithms. He received the 2012 K.-T. Li Young Researcher Award from the ACM Taipei Chapter, the 2013 D.-Y. Wu Memorial Award from National Science Council of Taiwan, and the 2017 Creative Young Scholar Award from Foundation for the Advancement of Outstanding Scholarship in Taiwan. He co-led the teams that won the third place of KDDCup 2009 slow track, the champion of KDDCup 2010, the double-champion of the two tracks in KDDCup 2011, the champion of track 2 in KDDCup 2012, and the double-champion of the two tracks in KDDCup 2013. He served as the Secretary General of Taiwanese Association for Artificial Intelligence between 2013 and 2014.

題目:

Learning Interaction Representations and Its Applications

時間:
Oct. 8, 2021 (Friday) 10:20-11:00

簡介:

Cheng-Te Li is an Associate Professor at Institute of Data Science and Department of Statistics, National Cheng Kung University (NCKU), Tainan, Taiwan. He received his Ph.D. degree (2013) from Graduate Institute of Networking and Multimedia, National Taiwan University. Before joining NCKU, he was an Assistant Research Fellow (2014-2016) at CITI, Academia Sinica. His research interests target at Machine Learning, Deep Learning, Data Mining, Social Networks and Social Media Analysis, Recommender Systems, and Natural Language Processing. Problems he aims to tackle are inspired by real-world applications with Massive Datasets. He leads Networked Artificial Intelligence Laboratory (NetAI Lab) at NCKU.

題目:

智慧工廠AI-AOI落地與維運案例分享

時間:
Oct. 8, 2021 (Friday) 14:20-15:00

簡介:

Aaron has focused on image processing, medical imaging, deep learning, neural networks, fuzzy systems and AI for more than 10 years. In recent years, he has published 7 papers in international seminars and 4 SCI journals in the field of electronics and motors. He has eight Taiwanese invention patents and six new patents. In 2016, Aaron founded AIWin, which focuses on providing deep learning image recognition technology, B2B service models, and AI solutions for the smart city and smart factory. Aaron believes that deep learning and AI will bring about significant changes, and only the people-oriented design concept can bring the highest value of AI.

題目:

Machine Learning as a Service: the challenge and opportunity

時間:
Oct. 8, 2021 (Friday) 15:20-16:00

簡介:

Dr. Shou-De Lin is the Chief Machine Learning (ML) Scientist in Appier since February 2020 with 20+ years of experience in AI, machine learning, data mining and natural language processing. Prior to joining Appier, he served as a full-time professor at the National Taiwan University (NTU) Department of Computer Science and Information Engineering. Dr. Lin is the recipient of several prestigious research awards and brings a mix of both academic and industry expertise to Appier. He has advised more than 50 global companies in the research and application of AI, winning awards from Microsoft, Google and IBM for his work. He led or co-led the NTU team to win 7 ACM KDD Cup championships. He has over 100 publications in top-tier journals and conferences, winning various dissertation awards. After joining Appier, Dr. Lin led the AiDeal team to win the Best Overall AI-based Analytics Solution in the 2020 Artificial Intelligence Breakthrough Awards. Dr. Lin holds a BS-EE degree from NTU and an MS-EECS degree from the University of Michigan. He also holds an MS degree in Computational Linguistics and a Ph.D. in Computer Science, both from the University of Southern California.