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SUCAG: Stochastic Unbiased Curvature-aided Gradient Method for Distributed Optimization
We propose and analyze a new stochastic gradient method, which we call Stochastic Unbiased Curvature-aided Gradient (SUCAG), for finite sum optimization problems.
Curvature-aided Incremental Aggregated Gradient Method
We propose a new algorithm for finite sum optimization which we call the curvature-aided incremental aggregated gradient (CIAG) method.
On Projected Stochastic Gradient Descent Algorithm with Weighted Averaging for Least Squares Regression
The problem of least squares regression of a $d$-dimensional unknown parameter is considered.
Data Clustering and Graph Partitioning via Simulated Mixing
Several algorithms have been proposed in the recent past to accelerate spectral clustering, however they compromise on the accuracy of the spectral clustering to achieve faster speed.
Stochastic Gradient-Push for Strongly Convex Functions on Time-Varying Directed Graphs
We investigate the convergence rate of the recently proposed subgradient-push method for distributed optimization over time-varying directed graphs.
Optimization and Control Systems and Control
