SOTAVerified

Privacy Preserving

Papers

Showing 2650 of 2975 papers

TitleStatusHype
FedGH: Heterogeneous Federated Learning with Generalized Global HeaderCode2
A Synthetic Dataset for Personal Attribute InferenceCode2
FedCLIP: Fast Generalization and Personalization for CLIP in Federated LearningCode2
Investigating Affective Use and Emotional Well-being on ChatGPTCode2
Turning the Tables: Biased, Imbalanced, Dynamic Tabular Datasets for ML EvaluationCode2
Enhancing the Utility of Privacy-Preserving Cancer Classification using Synthetic DataCode2
Encrypted Vector Similarity Computations Using Partially Homomorphic Encryption: Applications and Performance AnalysisCode2
Evaluation of Bio-Inspired Models under Different Learning Settings For Energy Efficiency in Network Traffic PredictionCode2
Does Image Anonymization Impact Computer Vision Training?Code2
Differentially Private Synthetic Data via Foundation Model APIs 2: TextCode2
EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning and VotingCode2
Enhancing Privacy in Federated Learning: Secure Aggregation for Real-World Healthcare ApplicationsCode2
A Survey on Federated Fine-tuning of Large Language ModelsCode2
DensePose From WiFiCode2
AutoFi: Towards Automatic WiFi Human Sensing via Geometric Self-Supervised LearningCode2
Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic ForecastingCode2
Federated Learning with New Knowledge: Fundamentals, Advances, and FuturesCode2
Edit Away and My Face Will not Stay: Personal Biometric Defense against Malicious Generative EditingCode2
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual LearningCode2
FATE-LLM: A Industrial Grade Federated Learning Framework for Large Language ModelsCode2
Learnware of Language Models: Specialized Small Language Models Can Do BigCode2
CLEAR: A Fully User-side Image Search SystemCode2
Communication-Efficient Federated Learning with Binary Neural NetworksCode1
A Privacy-Preserving Distributed Architecture for Deep-Learning-as-a-ServiceCode1
COMODO: Cross-Modal Video-to-IMU Distillation for Efficient Egocentric Human Activity RecognitionCode1
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