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Privacy

2794 directly classified papers

Papers per year

Papers

Fine-Tuning Language Models with Differential Privacy through Adaptive Noise Allocation EMNLP 2024
PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model AISTATS 2024
Federated Experiment Design under Distributed Differential Privacy AISTATS 2024
UnSeg: One Universal Unlearnable Example Generator is Enough against All Image Segmentation NIPS 2024
Joint Selection: Adaptively Incorporating Public Information for Private Synthetic Data AISTATS 2024
A Privacy Preserving Federated Learning (PPFL) Based Cognitive Digital Twin (CDT) Framework for Smart Cities AAAI 2024
Risk Management in Image Generative Models through Model Fingerprinting AAAI 2024
Collaborative Learning across Heterogeneous Systems with Pre-Trained Models AAAI 2024
Blind-Touch: Homomorphic Encryption-Based Distributed Neural Network Inference for Privacy-Preserving Fingerprint Authentication AAAI 2024
Sample-Efficient Personalization: Modeling User Parameters as Low Rank Plus Sparse Components AISTATS 2024
Revisiting Differentially Private ReLU Regression NIPS 2024
Private and Personalized Frequency Estimation in a Federated Setting NIPS 2024
UMA: Facilitating Backdoor Scanning via Unlearning-Based Model Ablation AAAI 2024
Find the Lady: Permutation and Re-synchronization of Deep Neural Networks AAAI 2024
SAME: Sample Reconstruction against Model Extraction Attacks AAAI 2024
Towards Model Extraction Attacks in GAN-Based Image Translation via Domain Shift Mitigation AAAI 2024
Thompson Sampling Itself is Differentially Private AISTATS 2024
Complementary Knowledge Distillation for Robust and Privacy-Preserving Model Serving in Vertical Federated Learning AAAI 2024
Detection and Defense of Unlearnable Examples AAAI 2024
A Learnable Discrete-Prior Fusion Autoencoder with Contrastive Learning for Tabular Data Synthesis AAAI 2024
DP-AdamBC: Your DP-Adam Is Actually DP-SGD (Unless You Apply Bias Correction) AAAI 2024
WatME: Towards Lossless Watermarking Through Lexical Redundancy ACL 2024
On the Privacy of Selection Mechanisms with Gaussian Noise AISTATS 2024
On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift NIPS 2024
FedFixer: Mitigating Heterogeneous Label Noise in Federated Learning AAAI 2024