We analyze the convergence of \texttt{FedAvg} on non-iid data and establish a convergence rate of $\mathcal{O}(\frac{1}{T})$ for strongly convex and smooth problems, where $T$ is the number of SGDs.Expand

We establish a general error bound for the adaptive column/row sampling algorithm, based on which we propose more accurate CUR and Nystrom algorithms with expected relative-error bounds.Expand

For distributed computing environment, we consider the empirical risk minimization problem and propose a distributed and communication-efficient Newton-type optimization method.Expand

The prescription of diurnal radiation distribution and the consideration of topographic impact on canopy radiation interception are often required in ecological modelling studies. The most commonly… Expand

This paper proposes a novel approach to the colorization problem by formulating it as a matrix completion problem and resort to an augmented Lagrange multiplier algorithm for solving it.Expand

Abstract Surface albedo determines the distribution of solar radiation between the earth's surface and the atmosphere. It affects the global climate directly by altering surface energy balance, and… Expand

Kernel $k$-means clustering with rank-restricted Nystrom approximation can correctly identify and extract a far more varied collection of cluster structures than the linear $k$, but it is not a universal solution to all clustering problems.Expand

We analyze the Periodic Decentralized Stochastic Gradient Descent (PD-SGD), a straightforward combination of federated averaging and decentralized SGD.Expand