Charlie Hou

发表

SquirRL: Automating Attack Analysis on Blockchain Incentive Mechanisms with Deep Reinforcement Learning

A. Juels, Florian Tramèr, Yan Ji, 2021, NDSS.

FedChain: Chained Algorithms for Near-optimal Communication Cost in Federated Learning

G. Fanti, Sewoong Oh, K. K. Thekumparampil, 2021, International Conference on Learning Representations.

SquirRL: Automating Attack Discovery on Blockchain Incentive Mechanisms with Deep Reinforcement Learning pdf

Ari Juels, Yan Ji, Giulia Fanti, 2019, Proceedings 2021 Network and Distributed System Security Symposium.

Efficient Algorithms for Federated Saddle Point Optimization pdf

Sewoong Oh, Giulia Fanti, Charlie Hou, 2021, ArXiv.

FedChain: Chained Algorithms for Near-optimal Communication Cost in Federated Learning

G. Fanti, Sewoong Oh, K. K. Thekumparampil, 2021, ICLR.

SquirRL: Automating Attack Discovery on Blockchain Incentive Mechanisms with Deep Reinforcement Learning pdf

Ari Juels, Florian Tramer, Giulia Fanti, 2019, ArXiv.

Pretrained deep models outperform GBDTs in Learning-To-Rank under label scarcity

Sujay Sanghavi, K. K. Thekumparampil, Michael Shavlovsky, 2023, ArXiv.

Pretrained deep models outperform GBDTs in Learning-To-Rank under label scarcity

Sujay Sanghavi, K. K. Thekumparampil, Michael Shavlovsky, 2023, ArXiv.

Privately Customizing Prefinetuning to Better Match User Data in Federated Learning

Sida I. Wang, G. Fanti, Hongyuan Zhan, 2023, ArXiv.

PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs

Charlie Hou, Akshat Shrivastava, Adithya Sagar, 2024, ArXiv.