data reconstruction

A Multi-Focus-Driven Multi-Branch Network for Robust Multimodal Sentiment Analysis AAAI 2025 Gradient Inversion Attacks on Parameter-Efficient Fine-Tuning CVPR 2025 MMGIA: Gradient Inversion Attack Against Multimodal Federated Learning via Intermodal Correlation IJCAI 2025 Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks ICLR 2025 Textual Unlearning Gives a False Sense of Unlearning ICML 2025 Leak and Learn: An Attacker's Cookbook to Train Using Leaked Data from Federated Learning CVPR 2024 Leave-one-out Distinguishability in Machine Learning ICLR 2024 Maximum Knowledge Orthogonality Reconstruction With Gradients in Federated Learning WACV 2024 PolarRec: Improving Radio Interferometric Data Reconstruction Using Polar Coordinates CVPR 2024 Pseudo-Private Data Guided Model Inversion Attacks NeurIPS 2024 Towards Eliminating Hard Label Constraints in Gradient Inversion Attacks ICLR 2024 Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses NeurIPS 2023 PrimeNet: Pre-training for Irregular Multivariate Time Series AAAI 2023 Reconstructing Training Data From Trained Neural Networks NeurIPS 2022 Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models ICLR 2022 Unsupervised Active Learning via Subspace Learning AAAI 2021 Frame-based Data Factorizations ICML 2017 Latent Multi-View Subspace Clustering CVPR 2017 Reconstruction-based Unsupervised Feature Selection: An Embedded Approach IJCAI 2017