Invention Grant
- Patent Title: Interpretation maps with guaranteed robustness
-
Application No.: US16894343Application Date: 2020-06-05
-
Publication No.: US11341598B2Publication Date: 2022-05-24
- Inventor: Ao Liu , Sijia Liu , Abhishek Bhandwaldar , Chuang Gan , Lirong Xia , Qi Cheng Li
- Applicant: International Business Machines Corporation , Rensselaer Polytechnic Institute
- Applicant Address: US NY Armonk; US NY Troy
- Assignee: International Business Machines Corporation,Rensselaer Polytechnic Institute
- Current Assignee: International Business Machines Corporation,Rensselaer Polytechnic Institute
- Current Assignee Address: US NY Armonk; US NY Troy
- Agency: Michael J. Chang, LLC
- Agent Anthony Curro
- Main IPC: G06T1/00
- IPC: G06T1/00 ; G06T5/00 ; G06T5/20 ; G06N3/02 ; G06T5/50

Abstract:
Interpretation maps of deep neural networks are provided that use Renyi differential privacy to guarantee the robustness of the interpretation. In one aspect, a method for generating interpretation maps with guaranteed robustness includes: perturbing an original digital image by adding Gaussian noise to the original digital image to obtain m noisy images; providing the m noisy images as input to a deep neural network; interpreting output from the deep neural network to obtain m noisy interpretations corresponding to the m noisy images; thresholding the m noisy interpretations to obtain a top-k of the m noisy interpretations; and averaging the top-k of the m noisy interpretations to produce an interpretation map with certifiable robustness.
Public/Granted literature
- US20210383497A1 Interpretation Maps with Guaranteed Robustness Public/Granted day:2021-12-09
Information query