WA-P.PZ3.4
Neuro-Inspired Deep Neural Networks with Sparse, Strong Activations
Metehan Cekic, Can Bakiskan, Upamanyu Madhow, University of California, Santa Barbara, United States of America
Session:
Adversarial Robustness
Track:
Applications of Machine Learning
Location:
Poster Zone 3
Presentation Time:
Wed, 19 Oct, 16:00 - 18:30 China Standard Time (UTC +8)
Wed, 19 Oct, 10:00 - 12:30 Central European Time (UTC +2)
Wed, 19 Oct, 08:00 - 10:30 UTC
Wed, 19 Oct, 04:00 - 06:30 Eastern Time (UTC -4)
Wed, 19 Oct, 10:00 - 12:30 Central European Time (UTC +2)
Wed, 19 Oct, 08:00 - 10:30 UTC
Wed, 19 Oct, 04:00 - 06:30 Eastern Time (UTC -4)
Session Co-Chairs:
Andrea Cavallaro, Queen Mary University of London and Jean-Christophe Pesquet, CentraleSupélec and Rebecca Willett, University of Chicago
Presentation
Discussion
Resources
No resources available.
Session WA-P.PZ3
WA-P.PZ3.1: ADVERSARIAL TRAINING WITH CHANNEL ATTENTION REGULARIZATION
Seungju Cho, Junyoung Byun, Myung-Joon Kwon, Yoonji Kim, Changick Kim, Korea Advanced Institute of Science and Technology, Korea, Republic of
WA-P.PZ3.2: ADAPTIVE WARPING NETWORK FOR TRANSFERABLE ADVERSARIAL ATTACKS
Minji Son, Myung-Joon Kwon, Hee-Seon Kim, Junyoung Byun, Seungju Cho, Changick Kim, Korea Advanced Institute of Science and Technology (KAIST), Korea, Republic of
WA-P.PZ3.3: IMPACT OF DOWNSCALING ON ADVERSARIAL IMAGES
Benoit Bonnet, Teddy Furon, INRIA, France; Patrick Bas, CNRS, France
WA-P.PZ3.4: Neuro-Inspired Deep Neural Networks with Sparse, Strong Activations
Metehan Cekic, Can Bakiskan, Upamanyu Madhow, University of California, Santa Barbara, United States of America
WA-P.PZ3.5: EXPLOITING DOUBLY ADVERSARIAL EXAMPLES FOR IMPROVING ADVERSARIAL ROBUSTNESS
Junyoung Byun, Hyojun Go, Seungju Cho, Changick Kim, Korea Advanced Institute of Science and Technology, Korea, Republic of
WA-P.PZ3.6: HIDDEN CONDITIONAL ADVERSARIAL ATTACKS
Junyoung Byun, Kyujin Shim, Hyojun Go, Changick Kim, Korea Advanced Institute of Science and Technology, Korea, Republic of