PPML 2024

August 18, 2024

 

 

Santa Barbara, USA

Affiliated Event: The 6th Privacy-Preserving Machine Learning Workshop 2024

About

Artificial intelligence is progressing rapidly. Systems based on machine learning algorithms approach and sometimes even exceed the abilities of human experts. Applications of machine learning involve almost every aspect of our lives, from health care and DNA sequence classification, to financial markets, computer networks and many more. Machine learning algorithms perform better when being exposed to more and more data, but such data is not always accessible due to privacy constraints. Can we train machine learning algorithms on confidential data without ever being exposed to it? Can my model classify your sample without ever seeing it?

The workshop aims to strengthen collaborations among the machine learning and cryptography communities. The scope includes privacy preserving techniques for training, inference, and disclosure. The workshop will consist of few invited talks, together with contributed talks.

Date of Event

August 18, 2024 (Sunday)

Registration

The workshop is an affiliated event of CRYPTO 2024. To register to the workshop, please register to CRYPTO 2024, and mark in the registration form the PPML workshop.

Location

University of Santa Barbara, California

The workshop will be in-person.

Invited Speakers

  • Nishanth Chandran (Microsoft Research, India)
  • Sanjam Garg (UC Berkley, USA)
  • Kunal Talwar (Apple, USA) More invited speakers will be added.

(Tentative) Program

The time displayed is in Pacific Daylight Time (GMT-7).

Abstracts – Invited Speakers

Contributed Talks

Call for Contributed Talks

There will be a session of contributed talks.

We encourage submissions exploring a range of techniques and applications for privacy preserving machine learning, including, but not limited to:

  • Multiparty computation
  • Homomorphic encryption
  • Differential privacy
  • Adversarial machine learning
  • Model stealing
  • Fairness and accountability
  • Federated Learning
  • Synthetic data generation

Submission deadline:

Wednesday, June 12th, 2024, 11:59pm EST.

Notifications: Friday, June 21st, 2024.

Submission server: https://easychair.org/my/conference?conf=cryptoppml2024

Submissions must comply with the following rules:

  • We encourage submitting full papers. Abstracts can also be provided.
  • Submissions must be non-anonymous and must clearly specify which author will give the talk.
  • The submission should provide sufficient detail to explain what the talk will be about.
  • As the workshop does not have formal proceedings, we accept contributed talk proposals which correspond to papers that are under submission or already published elsewhere (parallel submissions are allowed).

The committee will follow COI standards according to the IACR policy. Contributed Talks Committee members are allowed to submit as well.

Contributed Talks Committee

Organizers

Contact email: CRYPTO.PPML@gmail.com