cs.LG

Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching
We consider solving equality-constrained nonlinear, nonconvex optimization problems. This class of problems appears widely in a variety …
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Inequality Constrained Stochastic Nonlinear Optimization via Active-Set Sequential Quadratic Programming
We study nonlinear optimization problems with a stochastic objective and deterministic equality and inequality constraints, which …
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Hessian Averaging in Stochastic Newton Methods Achieves Superlinear Convergence
We consider minimizing a smooth and strongly convex objective function using a stochastic Newton method. At each iteration, the …
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On the Convergence of Overlapping Schwarz Decomposition for Nonlinear Optimal Control
We study the convergence properties of an overlapping Schwarz decomposition algorithm for solving nonlinear optimal control problems …
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Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming
We consider statistical inference of equality-constrained stochastic nonlinear optimization problems. We develop a fully online …
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The Graph-Based Behavior-Aware Recommendation for Interactive News
Interactive news recommendation has been launched and attracted much attention recently. In this scenario, user’s behavior evolves from …
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High-dimensional Index Volatility Models via Stein's Identity
We study the estimation of the parametric components of single and multiple index volatility models. Using the first- and second-order …
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AEGCN: An Autoencoder-Constrained Graph Convolutional Network
We propose a novel neural network architecture, called autoencoder-constrained graph convolutional network, to solve node …
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Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees
Graph representation learning is a ubiquitous task in machine learning where the goal is to embed each vertex into a low-dimensional …
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High-dimensional Varying Index Coefficient Models via Stein's Identity
We study the parameter estimation problem for a varying index coefficient model in high dimensions. Unlike the most existing works that …
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