stochastic gradient descent

Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent ICLR 2021 Domain-Independent Dominance of Adaptive Methods CVPR 2021 Dynamics of Stochastic Momentum Methods on Large-scale, Quadratic Models NeurIPS 2021 Efficient Generalization with Distributionally Robust Learning NeurIPS 2021 Efficient Truncated Linear Regression with Unknown Noise Variance NeurIPS 2021 Elastic Consistency: A Practical Consistency Model for Distributed Stochastic Gradient Descent AAAI 2021 Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization NeurIPS 2021 Ensembling With a Fixed Parameter Budget: When Does It Help and Why? ACML 2021 Error Compensated Distributed SGD Can Be Accelerated NeurIPS 2021 Escaping Saddle Points with Compressed SGD NeurIPS 2021 Explicit Regularization of Stochastic Gradient Methods through Duality AISTATS 2021 Exponential Convergence Rates of Classification Errors on Learning with SGD and Random Features AISTATS 2021 Fast and Memory Efficient Differentially Private-SGD via JL Projections NeurIPS 2021 Faster Neural Network Training with Approximate Tensor Operations NeurIPS 2021 Fast Stochastic Kalman Gradient Descent for Reinforcement Learning L4DC 2021 Fine-grained Generalization Analysis of Vector-Valued Learning AAAI 2021 Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms NeurIPS 2021 Generalization Guarantee of SGD for Pairwise Learning NeurIPS 2021 Generalization Performance of Multi-pass Stochastic Gradient Descent with Convex Loss Functions JMLR 2021 Generalized Linear Bandits with Local Differential Privacy NeurIPS 2021 Global Convergence of Three-layer Neural Networks in the Mean Field Regime ICLR 2021 Gradient Methods Never Overfit On Separable Data JMLR 2021 GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training NeurIPS 2021 Heavy Tails in SGD and Compressibility of Overparametrized Neural Networks NeurIPS 2021 Hogwild! over Distributed Local Data Sets with Linearly Increasing Mini-Batch Sizes AISTATS 2021