Christopher A. Choquette-Choo
25 papers · 2021–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π Renaissance Researcher (6) πΊοΈ Taxonomy Completionist (19) π§ Keyword Pioneer π Interdisciplinary Bridge
π
Conference Polyglot
(7)
π
Cross-Pollinator
(11)
β‘
Prolific Year
(5)
β
The Questioner
π
Century Club
(25)
Conferences
ICLR (9)
ICML (8)
NIPS (4)
ACL (1)
ALT (1)
EMNLP (1)
NAACL (1)
Top co-authors
Research topics
Keywords
differential privacy
(5)
privacy attack
(3)
large language model
(3)
federated learning
(3)
membership inference
(3)
secure aggregation
(2)
training datum
(2)
adversarial perturbation
(2)
matrix factorization
(2)
communication efficiency
(1)
machine learning
(1)
model robustness
(1)
secure multi-party computation
(1)
collaborative learning
(1)
data attribution
(1)
privacy-preserving learning
(1)
communication compression
(1)
language model
(1)
model distillation
(1)
adversarial attack
(1)
Papers
Measuring memorization in language models via probabilistic extraction
NAACL 2025
Privacy Ripple Effects from Adding or Removing Personal Information in Language Model Training
ACL 2025
Near-Optimal Rates for O(1)-Smooth DP-SCO with a Single Epoch and Large Batches
ALT 2025
The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD
ICLR 2025
Scalable Extraction of Training Data from Aligned, Production Language Models
ICLR 2025
Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon
ICLR 2025
Near-Exact Privacy Amplification for Matrix Mechanisms
ICLR 2025
Privacy Auditing of Large Language Models
ICLR 2025
Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards
ICML 2025
Language Models May Verbatim Complete Text They Were Not Explicitly Trained On
ICML 2025
Scaling Laws for Differentially Private Language Models
ICML 2025
Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs
ICML 2025
Auditing Private Prediction
ICML 2024
User Inference Attacks on Large Language Models
EMNLP 2024
Teach LLMs to Phish: Stealing Private Information from Language Models
ICLR 2024
Correlated Noise Provably Beats Independent Noise for Differentially Private Learning
ICLR 2024
Privacy Amplification for Matrix Mechanisms
ICLR 2024
Robust and Actively Secure Serverless Collaborative Learning
NIPS 2023
Multi-Epoch Matrix Factorization Mechanisms for Private Machine Learning
ICML 2023
Private Federated Learning with Autotuned Compression
ICML 2023
Students Parrot Their Teachers: Membership Inference on Model Distillation
NIPS 2023
Are aligned neural networks adversarially aligned?
NIPS 2023
(Amplified) Banded Matrix Factorization: A unified approach to private training
NIPS 2023
CaPC Learning: Confidential and Private Collaborative Learning
ICLR 2021
Label-Only Membership Inference Attacks
ICML 2021