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math.OC2019
Distributed Gradient Descent: Nonconvergence to Saddle Points and the Stable-Manifold Theorem
Brian Swenson, Ryan Murray, H. Vincent Poor +1
The paper studies a distributed gradient descent (DGD) process and considers the problem of showing that in nonconvex optimization problems, DGD typically converges to local minima…
stat.ML2019
A maximum principle argument for the uniform convergence of graph Laplacian regressors
Nicolas Garcia Trillos, Ryan Murray
This paper investigates the use of methods from partial differential equations and the Calculus of variations to study learning problems that are regularized using graph Laplacians…