Da Yu
13 papers · 2019–2025 · 8 conferences · across top CS/AI conferences
Achievements
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🌍 Conference Polyglot (8) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (6)
🐝
Cross-Pollinator
(13)
🌈
Renaissance Researcher
(7)
🌍
Conference Polyglot
(8)
💎
Century Club
(13)
🔥
Unstoppable
(7)
❓
The Questioner
Conferences
ICML (4)
ICLR (3)
AAAI (1)
AACL (1)
AISTATS (1)
IJCAI (1)
IJCNLP (1)
NSDI (1)
Top co-authors
Research topics
Keywords
large language model
(2)
logical reasoning
(2)
neural network
(2)
gradient perturbation
(2)
differential privacy
(2)
data augmentation
(1)
bert model
(1)
network monitoring
(1)
network diagnosis
(1)
set classification
(1)
adversarial attack
(1)
adversarial example
(1)
information leakage
(1)
privacy leakage
(1)
privacy risk
(1)
membership inference
(1)
generalization performance
(1)
reasoning benchmark
(1)
distributed system
(1)
distributed packet trace
(1)
Papers
On Memorization of Large Language Models in Logical Reasoning
AACL 2025
Scaling Laws for Differentially Private Language Models
ICML 2025
On Memorization of Large Language Models in Logical Reasoning
IJCNLP 2025
Privacy-Preserving Instructions for Aligning Large Language Models
ICML 2024
Differentially Private Synthetic Data via Foundation Model APIs 2: Text
ICML 2024
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
ICLR 2023
Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks
AISTATS 2023
Differentially Private Fine-tuning of Language Models
ICLR 2022
How Does Data Augmentation Affect Privacy in Machine Learning?
AAAI 2021
Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning
ICLR 2021
Large Scale Private Learning via Low-rank Reparametrization
ICML 2021
Gradient Perturbation is Underrated for Differentially Private Convex Optimization
IJCAI 2020
dShark: A General, Easy to Program and Scalable Framework for Analyzing In-network Packet Traces
NSDI 2019