December 2020
Beginner to intermediate
256 pages
5h 15m
Korean
Content preview from 안전한 인공지능 시스템을 위한 심층 신경망 강화
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154
2
부
적대적 입력 생성하기
그런 다음, 선택과 교차 그리고 변이가 반복되면서 차세대 샘플이 생성됩니다. 첫 번째, 기
존 세대의 하위 집합은 ‘부모’로 선택되며, 더 높은 체력 점수를 가진 사람들이 선호됩니다.
부모의 적대적 측면이 결합되고(크로스오버) 일부 랜덤 노이즈(돌연변이)가 추가되어 다음
세대를 형성할 자식을 만듭니다. 다시 한번, 새로운 세대의 각 구성원은 신경망에서 반환된
점수를 기반으로 적대적 적합성을 평가합니다.
적대적 사례가 생성되거나 유전자 알고리즘이 결과를 생성하지 못한 경우, 즉 세대 수가 최
대 임계값을 초과하는 경우에 과정이 완료됩니다.
이 시점에서 모델의 보안을 중시하는 조직이 점수를 제공하는 이유가 궁금할 것입니다. 예를
들어, 이미지가 소셜 미디어 웹 사이트에 부적절한 콘텐츠를 포함하는 것으로 자동 간주되어
제거 요건을 충족한 경우 이미지를 업로드한 개인은 이미지가 검열되었다는 경고 또는 알림을
받게 됩니다. 그들은
DNN
이 이미지에 할당한 분류 확률을 나타내는 상세한 출력 점수를 받지
못할 것입니다. 따라서 조직은 이와 같은 시나리오에서 점수 정보를 제공하지 않습니다. 그러
나 점수를 제공하는
DNN
기술을 소개하고 발전시키기 위해 이미 많은 개방형
API
가 만들어
졌습니다.
7
장에서 볼 수 있듯이 모델 자체의 보안을 ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.