MLSP-L16.6
Linearly-involved Moreau-Enhanced-over-Subspace Model: Debiased Sparse Modeling and Stable Outlier-Robust Regression
Masahiro Yukawa, Hiroyuki Kaneko, Kyohei Suzuki, Keio University, Japan; Isao Yamada, Tokyo Institute of Technology, Japan
Session:
MLSP-L16: Robustness and Trustworthy Machine Learning II Lecture
Track:
Machine Learning for Signal Processing
Location:
Room 105
Presentation Time:
Thu, 18 Apr, 14:50 - 15:10 (UTC +9)
Session Co-Chairs:
Dionysis Kalogerias, Yale University and Amit Ranjan Trivedi, University of Illinois at Chicago
Presentation
Discussion
Resources
No resources available.
Session MLSP-L16
MLSP-L16.1: FEDERATED LEARNING UNDER RESTRICTED USER AVAILABILITY
Periklis Theodoropoulos, Konstantinos Nikolakakis, Dionysis Kalogerias, Yale University, United States of America
MLSP-L16.2: CONFORMALIZED MULTIMODAL UNCERTAINTY REGRESSION AND REASONING
Domenico Parente, Nastaran Darabi, Alex Stutts, Theja Tulabandhula, Amit Ranjan Trivedi, University of Illinois at Chicago, United States of America
MLSP-L16.3: Fixed Inter-Neuron Covariability Induces Adversarial Robustness
Muhammad Shah, Bhiksha Raj, Carnegie Mellon University, United States of America
MLSP-L16.4: NOISE-BERT: A UNIFIED PERTURBATION-ROBUST FRAMEWORK WITH NOISE ALIGNMENT PRE-TRAINING FOR NOISY SLOT FILLING TASK
Jinxu Zhao, Guanting Dong, Yueyan Qiu, Tingfeng Hui, Xiaoshuai Song, Daichi Guo, Weiran Xu, Beijing University of Posts and Telecommunications, China
MLSP-L16.5: ANALYZING ADVERSARIAL VULNERABILITIES OF GRAPH LOTTERY TICKETS
Subhajit Dutta Chowdhury, Zhiyu Ni, Qingyuan Peng, University of Southern California, United States of America; Souvik Kundu, Intel Labs, United States of America; Pierluigi Nuzzo, University of Southern California, United States of America
MLSP-L16.6: Linearly-involved Moreau-Enhanced-over-Subspace Model: Debiased Sparse Modeling and Stable Outlier-Robust Regression
Masahiro Yukawa, Hiroyuki Kaneko, Kyohei Suzuki, Keio University, Japan; Isao Yamada, Tokyo Institute of Technology, Japan
Contacts