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researcher

Jason Pacheco

3 papers hereh-index 218 citations6 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG3
same name
  • Jason Pacheco — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedDifferentially Private Stochastic Gradient Descent with Fixed-Size Minibatches: Tighter RDP Guarantees with or without Replacement

1 citations · 1 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2026

Information Theoretic Adversarial Training of Large Language Models

Yiwei Zhang, Jeremiah Birrell, Reza Ebrahimi +3

Large language models (LLMs) remain vulnerable to adversarial prompting despite advances in alignment and safety, often exhibiting harmful behaviors under novel attack strategies.…

cs.LG2025

An Interactive Framework for Implementing Privacy-Preserving Federated Learning: Experiments on Large Language Models

Kasra Ahmadi, Rouzbeh Behnia, Reza Ebrahimi +4

Federated learning (FL) enhances privacy by keeping user data on local devices. However, emerging attacks have demonstrated that the updates shared by users during training can rev…

cs.LG2024★ 1 cited

Differentially Private Stochastic Gradient Descent with Fixed-Size Minibatches: Tighter RDP Guarantees with or without Replacement

Jeremiah Birrell, Reza Ebrahimi, Rouzbeh Behnia +1

Differentially private stochastic gradient descent (DP-SGD) has been instrumental in privately training deep learning models by providing a framework to control and track the priva…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.