147 citations · 201 across the 4 of their papers we have counts for
4 papers
Can LLM Agents Price Competitively? A Dynamic Multi-Attribute Auction Benchmark for Agentic Commerce
Shimaa Ahmed, Yiwei Cai, Mohsen Minaei +1
Agentic commerce is moving from concept to deployed infrastructure: payment networks, retailers, and AI platforms are setting the stage for agents to transact on behalf of merchant…
Covert Attacks on Machine Learning Training in Passively Secure MPC
Matthew Jagielski, Daniel Escudero, Rahul Rachuri +1
Secure multiparty computation (MPC) allows data owners to train machine learning models on combined data while keeping the underlying training data private. The MPC threat model ei…
Tetrad: Actively Secure 4PC for Secure Training and Inference
Nishat Koti, Arpita Patra, Rahul Rachuri +1
Mixing arithmetic and boolean circuits to perform privacy-preserving machine learning has become increasingly popular. Towards this, we propose a framework for the case of four par…
Trident: Efficient 4PC Framework for Privacy Preserving Machine Learning
Harsh Chaudhari, Rahul Rachuri, Ajith Suresh
Machine learning has started to be deployed in fields such as healthcare and finance, which propelled the need for and growth of privacy-preserving machine learning (PPML). We prop…