MLSP-L9: Robustness and Trustworthy Machine Learning I
Wed, 17 Apr, 13:10 - 15:10 (UTC +9)
Location: Room E3
Session Type: Lecture
Session Co-Chairs: Jayaraman J. Thiagarajan, Lawrence Livermore National Laboratory and Jennifer Williams, University of Southampton
Track: Machine Learning for Signal Processing
Click the to view the manuscript on IEEE Xplore Open Preview
Wed, 17 Apr, 13:10 - 13:30 (UTC +9)
 

MLSP-L9.1: UNDERSTANDING DATA AUGMENTATION FROM A ROBUSTNESS PERSPECTIVE
Zhendong Liu, Jie Zhang, Qiangqiang He, Chongjun Wang, Nanjing University, China
Wed, 17 Apr, 13:30 - 13:50 (UTC +9)
 

MLSP-L9.2: ON ESTIMATING LINK PREDICTION UNCERTAINTY USING STOCHASTIC CENTERING
Puja Trivedi, Danai Koutra, University of Michigan, United States of America; Jayaraman J. Thiagarajan, Lawrence Livermore National Laboratory, United States of America
Wed, 17 Apr, 13:50 - 14:10 (UTC +9)
 

MLSP-L9.3: DEEPGRE: GLOBAL ROBUSTNESS EVALUATION OF DEEP NEURAL NETWORKS
Tianle Zhang, Jiaxu Liu, Yanghao Zhang, Ronghui Mu, Wenjie Ruan, University of Liverpool, United Kingdom of Great Britain and Northern Ireland
Wed, 17 Apr, 14:10 - 14:30 (UTC +9)
 

MLSP-L9.4: Adversarial Robustness of Convolutional Models Learned in the Frequency Domain
Subhajit Chaudhury, IBM Research, United States of America; Toshihiko Yamasaki, The University of Tokyo, Japan
Wed, 17 Apr, 14:30 - 14:50 (UTC +9)
 

MLSP-L9.5: NOISE-RESISTANT GRAPH NEURAL NETWORK FOR NODE CLASSIFICATION
Zichao Deng, Nanyang Technological University and Alibaba Group, Singapore; Han Yu, Nanyang Technological University, Singapore
Wed, 17 Apr, 14:50 - 15:10 (UTC +9)
 

MLSP-L9.6: THE DOUBLE-EDGED SWORD OF AI SAFETY: BALANCING ANOMALY DETECTION AND OOD GENERALIZATION VIA MODEL ANCHORING
Vivek Narayanaswamy, Rushil Anirudh, Jayaraman J. Thiagarajan, Lawrence Livermore National Laboratory, United States of America