MLSP-L14.4

Adversarial Learning with a Uniformly Distributed Cost Bound

Jarrod Hoge Hollis, Jinsub Kim, Raviv Raich, Oregon State University, United States of America
Session:
MLSP-L14: Adversarial Attacks and Robust Learning Oral
Track:
Machine Learning for Signal Processing [ML]
Location:
Room 120+121
Presentation Time:
Wed, 6 May, 15:00 - 15:20
Presentation
Discussion
Resources
No resources available.
Session MLSP-L14
MLSP-L14.1: BadViM: Backdoor Attack against Vision Mamba
Yinghao Wu, Liyan Zhang, Nanjing University of Aeronautics and Astronautics, China
MLSP-L14.2: BLINDDET: TOWARDS ROBUST PHYSICAL-WORLD BACKDOOR ATTACK IN LOW-LIGHT SCENARIOS AGAINST OBJECT DETECTION
Yuxi Li, Tong Chen, Haiquan Wang, Beihang University, China; Jiejie Zhao, Zhongguancun Laboratory, China; Bowen Du, Beihang University, China
MLSP-L14.3: ALFM: ADAPTIVE LOCAL FEATURE MINING OF VISION-LANGUAGE MODELS FOR OUT-OF-DISTRIBUTION DETECTION
Yuxin Ge, Shuai Feng, Baoming Zhang, Shuangjie Li, Boqiang Bao, Chongjun Wang, Nanjing University, China
MLSP-L14.4: Adversarial Learning with a Uniformly Distributed Cost Bound
Jarrod Hoge Hollis, Jinsub Kim, Raviv Raich, Oregon State University, United States of America
MLSP-L14.5: MATHHALU: A BENCHMARK FOR MATHEMATICAL REASONING PROCESS HALLUCINATION DETECTION IN LARGE REASONING MODELS
Bo Zhang, Rocket Force University of Engineering, China; Cong Gao, Nankai University, China; Bingxu Han, Shandong University, China; Minghao Hu, Zhunchen Luo, Jun Zhang, AMS, Center of Information Research, China; Wen Yao, AMS, Defense Innovation Institute, China; Xiaoying Bai, Guotong Geng, AMS, Center of Information Research, China; Zhong Wang, Rocket Force University of Engineering, China
MLSP-L14.6: PROTOLENS: A FINE-GRAINED AND ADAPTIVE INTERPRETATION FRAMEWORK FOR TIME SERIES DATA CLASSIFICATION WITH PROTOTYPES
Rucheng Wu, Zehua Sun, Weitao Xu, City University of Hong Kong, China
Contacts