MLSP-L1.6
BOUNDARY-DRIVEN ACTIVE LEARNING FOR ANOMALY DETECTION IN TIME SERIES DATA STREAMS
Xiaohui Zhou, Yijie Wang, Hongzuo Xu, Mingyu Liu, National University of Defense Technology, China
Session:
MLSP-L1: Deep Learning Techniques I Lecture
Track:
Machine Learning for Signal Processing
Location:
Room 102
Presentation Time:
Tue, 16 Apr, 14:50 - 15:10 (UTC +9)
Session Co-Chairs:
Yik-Chung Wu, The University of Hong Kong and Vidhyasaharan Sethu, The University of New South Wales
Session MLSP-L1
MLSP-L1.1: LEARNING A LOW-RANK FEATURE REPRESENTATION: ACHIEVING BETTER TRADE-OFF BETWEEN STABILITY AND PLASTICITY IN CONTINUAL LEARNING
Zhenrong Liu, Southern University of Science and Technology & The University of Hong Kong, China; Yang Li, Shenzhen Research Institute of Big Data, China; Yi Gong, Southern University of Science and Technology, China; Yik-Chung Wu, The University of Hong Kong, Hong Kong
MLSP-L1.2: A PROBABILITY GRADIENT BASED APPROACH FOR SAMPLING BOUNDARIES OF IN-DOMAIN DATA
Miao JING, Vidhyasaharan Sethu, Beena Ahmed, The University of New South Wales, Australia
MLSP-L1.3: MVITP: MULTI-VIEW IMAGE-TEXT PERCEPTION FOR FEW-SHOT REMOTE SENSING IMAGE CLASSIFICATION
Chen Yang, Tongtong Liu, Didi Jiao, Wenhui Li, Jilin University, China
MLSP-L1.4: DYNAMIC REPLAY TRAINING FOR CLASS-INCREMENTAL LEARNING
Yan Yang, Dongdong Ren, Chenglei Peng, Jing Huo, Wenbin Li, Yang Gao, Nanjing University, China
MLSP-L1.5: G-SharP: Globally Shared Kernel with Pruning for Efficient CNNs
Eunseop Shin, Incheon Cho, Kyung-Hee University, South Korea, Korea, Republic of; Awais Muhammad, MBZ University of Artificial Intelligence, United Arab Emirates; A F M Shahab Uddin, YounHo Jang, Sung-Ho Bae, Kyung-Hee University, South Korea, Korea, Republic of
MLSP-L1.6: BOUNDARY-DRIVEN ACTIVE LEARNING FOR ANOMALY DETECTION IN TIME SERIES DATA STREAMS
Xiaohui Zhou, Yijie Wang, Hongzuo Xu, Mingyu Liu, National University of Defense Technology, China
Contacts