Skip to main content
idi
Toggle navigation
0
You have 0 notifications
Site Visitor
Site Visitor
New To Inknowvation.com?
Register now to get an access to proprietary SBIR-STTR databases!
Registration is fast and free - start your access to business-actionable information today!
Login
Site Register
SBIR-STTR Award
You are here:
Home
Search Databases
Search SBIR-STTR Awards
SBIR-STTR Award
5
Quantum Adversarial Machine Learning
Award last edited on: 8/18/22
Sponsored Program
SBIR
Awarding Agency
DOD : OSD
Total Award Amount
$225,000
Award Phase
1
Solicitation Topic Code
SCO183-001
Principal Investigator
Vc Ramesh
Company Information
Vcrsoft LLC
3513 Napolean Court
Plano, TX 75023
(817) 213-6184
vcr@vcrsoft.com
www.vcrsoft.com
Location:
Single
Congr. District:
03
County:
Tarrant
Phase I
Contract Number:
HQ003419P0168
Start Date:
7/29/19
Completed:
1/28/20
Phase I year
2019
Phase I Amount
$225,000
We propose a quantum adversarial machine learning (QAML) approach that combines ideas from different classical AML techniques such as Defense-GAN and thermometer-encoding of inputs. We propose an implementation of Defense-GAN on the D-Wave Leap quantum computing environment. We also propose to leverage ideas from quantum information science such as noisy inputs/outputs/parameters to improve the robustness of the proposed QAML approach. We will use the MNIST dataset to demonstrate feasibility of the proposed approach.
Phase II
Contract Number:
----------
Start Date:
00/00/00
Completed:
00/00/00
Phase II year
----
Phase II Amount
----
×
Login to your account
Mail sent successfully.
Enter any username and password.
Username
Password
Remember me
Login
Forgot your username?
Click here for assistance
Forgot your password?
Request new password
Don't have an account?
Sign up
Forgot username?
Mail sent successfully.
Enter username and password.
Please enter email address that is associated with your account.
Back
Submit
Still Need Help?
If you need further assistance, send us an
e-mail
and we will assist you in resetting your account.
Forgot password?
Mail sent successfully.
Enter username and password.
Please enter email address that is associated with your account.
Back
Submit
Still Need Help?
If you need further assistance, send us an
e-mail
and we will assist you in resetting your account.