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Peptide-Cation Systems: Conformational Search, Benchmark Evaluation, and Force Field Parameter Adjustment Using Regularized Linear Regression

Stochastic Three-Composite Convex Minimization with a Linear Operator

A Distributed Second-Order Algorithm You Can Trust

High-dimensional peaks-over-threshold inference

A coordinator-driven communication reduction scheme for distributed optimization using the projected gradient method

A coordinator-driven communication reduction scheme for distributed optimization using the projected gradient method

3D Reconstruction of Optical Diffraction Tomography Based on a Neural Network Model

Optimal Rates for Spectral Algorithms with Least-Squares Regression over Hilbert Spaces

On the linear convergence of the stochastic gradient method with constant step-size

General Proximal Gradient Method: A Case for Non-Euclidean Norms

Peptide-Cation Systems: Conformational Search, Benchmark Evaluation, and Force Field Parameter Adjustment Using Regularized Linear Regression

3D Reconstruction of Optical Diffraction Tomography Based on a Neural Network Model

Optimal Rates for Spectral Algorithms with Least-Squares Regression over Hilbert Spaces

On the linear convergence of the stochastic gradient method with constant step-size

A Distributed Second-Order Algorithm You Can Trust

High-dimensional peaks-over-threshold inference

A coordinator-driven communication reduction scheme for distributed optimization using the projected gradient method

General Proximal Gradient Method: A Case for Non-Euclidean Norms

Stochastic Three-Composite Convex Minimization with a Linear Operator

A coordinator-driven communication reduction scheme for distributed optimization using the projected gradient method