1 citations · 1 across the 2 of their papers we have counts for
4 papers · 1 filter
Optimistic Verifiable Training by Controlling Hardware Nondeterminism
Megha Srivastava, Simran Arora, Dan Boneh
The increasing compute demands of AI systems have led to the emergence of services that train models on behalf of clients lacking necessary resources. However, ensuring correctness…
FairProof : Confidential and Certifiable Fairness for Neural Networks
Chhavi Yadav, Amrita Roy Chowdhury, Dan Boneh +1
Machine learning models are increasingly used in societal applications, yet legal and privacy concerns demand that they very often be kept confidential. Consequently, there is a gr…
Open Problems in DAOs
Joshua Tan, Tara Merk, Sarah Hubbard +26
Decentralized autonomous organizations (DAOs) are a new, rapidly-growing class of organizations governed by smart contracts. Here we describe how researchers can contribute to the…
Vector Commitments with Efficient Updates
Ertem Nusret Tas, Dan Boneh
Dynamic vector commitments that enable local updates of opening proofs have applications ranging from verifiable databases with membership changes to stateless clients on blockchai…