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Found 7 papers, 1 papers with code
RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable Guarantees
Subsequently, we employ a classifier that is jointly trained with the watermark to detect the presence of the watermark.
Demystifying Poisoning Backdoor Attacks from a Statistical Perspective
The growing dependence on machine learning in real-world applications emphasizes the importance of understanding and ensuring its safety.
Mitigating Group Bias in Federated Learning: Beyond Local Fairness
While many mitigation strategies have been proposed in centralized learning, many of these methods are not directly applicable in federated learning, where data is privately stored on multiple clients.
Provable Identifiability of Two-Layer ReLU Neural Networks via LASSO Regularization
In this paper, the territory of LASSO is extended to two-layer ReLU neural networks, a fashionable and powerful nonlinear regression model.
Pruning Deep Neural Networks from a Sparsity Perspective
Our extensive experiments corroborate the hypothesis that for a generic pruning procedure, PQI decreases first when a large model is being effectively regularized and then increases when its compressibility reaches a limit that appears to correspond to the beginning of underfitting.
A Theoretical Understanding of Neural Network Compression from Sparse Linear Approximation
One problem is understanding if a network is more compressible than another of the same structure.
Provable Identifiability of ReLU Neural Networks via Lasso Regularization
In this paper, the territory of LASSO is extended to the neural network model, a fashionable and powerful nonlinear regression model.
