Fast Adversarial Robustness Certification of Nearest Prototype Classifiers for Arbitrary Seminorms
–Neural Information Processing Systems
Adversarial robustness of a classifier describes its stability in classification under adversarial manipulations of the input.
Neural Information Processing Systems
Aug-15-2025, 10:16:12 GMT
- Country:
- Asia
- Japan > Kyūshū & Okinawa
- Okinawa (0.04)
- Middle East > Jordan (0.04)
- South Korea > Seoul
- Seoul (0.04)
- Japan > Kyūshū & Okinawa
- Europe
- Austria > Vienna (0.14)
- Germany > Baden-Württemberg
- Karlsruhe Region > Heidelberg (0.04)
- Stuttgart Region > Weissach (0.04)
- Netherlands > North Holland
- Amsterdam (0.04)
- Spain > Catalonia
- Barcelona Province > Barcelona (0.04)
- Sweden > Stockholm
- Stockholm (0.04)
- North America
- Canada
- Alberta > Census Division No. 15
- Improvement District No. 9 > Banff (0.04)
- British Columbia > Vancouver (0.05)
- Ontario > Toronto (0.14)
- Quebec > Montreal (0.04)
- Alberta > Census Division No. 15
- United States
- California
- Los Angeles County > Long Beach (0.04)
- San Diego County > San Diego (0.04)
- San Francisco County > San Francisco (0.14)
- Santa Clara County > San Jose (0.04)
- Colorado > Denver County
- Denver (0.04)
- Florida > Miami-Dade County
- Miami (0.04)
- Louisiana > Orleans Parish
- New Orleans (0.04)
- Utah > Salt Lake County
- Salt Lake City (0.04)
- Wisconsin (0.04)
- California
- Canada
- Oceania > Australia
- New South Wales > Sydney (0.04)
- Asia
- Genre:
- Research Report (0.46)
- Industry:
- Health & Medicine > Therapeutic Area (0.68)
- Information Technology > Security & Privacy (0.47)
- Technology: