41 citations · 80 across the 19 of their papers we have counts for
5 papers · 1 filter
AEGCN: An Autoencoder-Constrained Graph Convolutional Network
Mingyuan Ma, Sen Na, Hongyu Wang
We propose a novel neural network architecture, called autoencoder-constrained graph convolutional network, to solve node classification task on graph domains. As suggested by its…
Convergence Analysis of Accelerated Stochastic Gradient Descent under the Growth Condition
You-Lin Chen, Sen Na, Mladen Kolar
We study the convergence of accelerated stochastic gradient descent for strongly convex objectives under the growth condition, which states that the variance of stochastic gradient…
On the Convergence of Overlapping Schwarz Decomposition for Nonlinear Optimal Control
Sen Na, Sungho Shin, Mihai Anitescu +1
We study the convergence properties of an overlapping Schwarz decomposition algorithm for solving nonlinear optimal control problems (OCPs). The algorithm decomposes the time domai…
Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees
Sen Na, Yuwei Luo, Zhuoran Yang +2
Graph representation learning is a ubiquitous task in machine learning where the goal is to embed each vertex into a low-dimensional vector space. We consider the bipartite graph a…
Superconvergence of Online Optimization for Model Predictive Control
Sen Na, Mihai Anitescu
We develop a one-Newton-step-per-horizon, online, lag-, model predictive control (MPC) algorithm for solving discrete-time, equality-constrained, nonlinear dynamic programs. Bas…