conftrace_

gradient clipping

54 papers

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Co-occurring keywords

differential privacy (1016) stochastic gradient descent (1091) neural network optimization (1293) convergence analysis (395) stochastic optimization (1060) non-convex optimization (547) federated learning (1333) heavy-tailed noise (23) heavy-tailed distribution (98) gradient descent (1144)

Papers

FedNAR: Federated Optimization with Normalized Annealing Regularization NIPS 2023
Differentially Private Sharpness-Aware Training ICML 2023
Scalable and Efficient Training of Large Convolutional Neural Networks with Differential Privacy NIPS 2022
High Probability Guarantees for Nonconvex Stochastic Gradient Descent with Heavy Tails ICML 2022
Private Stochastic Convex Optimization and Sparse Learning with Heavy-tailed Data Revisited IJCAI 2022
SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification AISTATS 2022
Detecting Unintended Memorization in Language-Model-Fused ASR INTERSPEECH 2022
Differentially Private Coordinate Descent for Composite Empirical Risk Minimization ICML 2022
Robustness to Unbounded Smoothness of Generalized SignSGD NIPS 2022
Understanding Clipping for Federated Learning: Convergence and Client-Level Differential Privacy ICML 2022
Differentially Private Normalizing Flows for Synthetic Tabular Data Generation AAAI 2022
A Communication-Efficient Distributed Gradient Clipping Algorithm for Training Deep Neural Networks NIPS 2022
On Proximal Policy Optimization’s Heavy-tailed Gradients ICML 2021
Reverse engineering learned optimizers reveals known and novel mechanisms NIPS 2021
Understanding Gradient Clipping In Incremental Gradient Methods AISTATS 2021
Tempered Sigmoid Activations for Deep Learning with Differential Privacy AAAI 2021
High-probability Bounds for Non-Convex Stochastic Optimization with Heavy Tails NIPS 2021
Stability and Convergence of Stochastic Gradient Clipping: Beyond Lipschitz Continuity and Smoothness ICML 2021
Why are Adaptive Methods Good for Attention Models? NIPS 2020
Stochastic Optimization with Heavy-Tailed Noise via Accelerated Gradient Clipping NIPS 2020
Understanding Gradient Clipping in Private SGD: A Geometric Perspective NIPS 2020
Improved Analysis of Clipping Algorithms for Non-convex Optimization NIPS 2020
Fractional Underdamped Langevin Dynamics: Retargeting SGD with Momentum under Heavy-Tailed Gradient Noise ICML 2020
Exploring Fast and Communication-Efficient Algorithms in Large-Scale Distributed Networks AISTATS 2019
Differential Privacy Has Disparate Impact on Model Accuracy NIPS 2019