Search Results for author: Sen Na

Found 15 papers, 10 papers with code

Constrained Optimization via Exact Augmented Lagrangian and Randomized Iterative Sketching

1 code implementation28 May 2023 Ilgee Hong, Sen Na, Michael W. Mahoney, Mladen Kolar

Our method adaptively controls the accuracy of the randomized solver and the penalty parameters of the exact augmented Lagrangian, to ensure that the inexact Newton direction is a descent direction of the exact augmented Lagrangian.

Fully Stochastic Trust-Region Sequential Quadratic Programming for Equality-Constrained Optimization Problems

1 code implementation29 Nov 2022 Yuchen Fang, Sen Na, Michael W. Mahoney, Mladen Kolar

We propose a trust-region stochastic sequential quadratic programming algorithm (TR-StoSQP) to solve nonlinear optimization problems with stochastic objectives and deterministic equality constraints.

Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming

1 code implementation27 May 2022 Sen Na, Michael W. Mahoney

We analyze a plug-in limiting covariance matrix estimator, and demonstrate the performance of the method both on benchmark nonlinear problems in CUTEst test set and on linearly/nonlinearly constrained regression problems.

Second-order methods Stochastic Optimization

Hessian Averaging in Stochastic Newton Methods Achieves Superlinear Convergence

1 code implementation20 Apr 2022 Sen Na, Michał Dereziński, Michael W. Mahoney

Remarkably, we show that there exists a universal weighted averaging scheme that transitions to local convergence at an optimal stage, and still exhibits a superlinear convergence rate nearly (up to a logarithmic factor) matching that of uniform Hessian averaging.

Global Convergence of Online Optimization for Nonlinear Model Predictive Control

no code implementations NeurIPS 2021 Sen Na

We study a real-time iteration (RTI) scheme for solving online optimization problem appeared in nonlinear optimal control.

Model Predictive Control

Inequality Constrained Stochastic Nonlinear Optimization via Active-Set Sequential Quadratic Programming

1 code implementation23 Sep 2021 Sen Na, Mihai Anitescu, Mladen Kolar

We study nonlinear optimization problems with a stochastic objective and deterministic equality and inequality constraints, which emerge in numerous applications including finance, manufacturing, power systems and, recently, deep neural networks.

An Adaptive Stochastic Sequential Quadratic Programming with Differentiable Exact Augmented Lagrangians

1 code implementation10 Feb 2021 Sen Na, Mihai Anitescu, Mladen Kolar

Based on the simplified deterministic algorithm, we then propose a non-adaptive SQP for dealing with stochastic objective, where the gradient and Hessian are replaced by stochastic estimates but the stepsizes are deterministic and prespecified.

AEGCN: An Autoencoder-Constrained Graph Convolutional Network

1 code implementation3 Jul 2020 Mingyuan Ma, Sen Na, Hongyu Wang

In extensive experiments on citation networks and other heterogeneous graphs, we demonstrate that adding autoencoder constraints significantly improves the performance of graph convolutional networks.

Graph Attention Node Classification

On the Convergence of Overlapping Schwarz Decomposition for Nonlinear Optimal Control

no code implementations14 May 2020 Sen Na, Sungho Shin, Mihai Anitescu, Victor M. Zavala

We study the convergence properties of an overlapping Schwarz decomposition algorithm for solving nonlinear optimal control problems (OCPs).

Motion Planning

Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees

no code implementations ICML 2020 Sen Na, Yuwei Luo, Zhuoran Yang, Zhaoran Wang, Mladen Kolar

We consider the bipartite graph and formalize its representation learning problem as a statistical estimation problem of parameters in a semiparametric exponential family distribution.

Graph Representation Learning

Estimating Differential Latent Variable Graphical Models with Applications to Brain Connectivity

1 code implementation12 Sep 2019 Sen Na, Mladen Kolar, Oluwasanmi Koyejo

Differential graphical models are designed to represent the difference between the conditional dependence structures of two groups, thus are of particular interest for scientific investigation.

High-dimensional Index Volatility Models via Stein's Identity

no code implementations27 Nov 2018 Sen Na, Mladen Kolar

We study the estimation of the parametric components of single and multiple index volatility models.

Vocal Bursts Intensity Prediction

High-dimensional Varying Index Coefficient Models via Stein's Identity

1 code implementation16 Oct 2018 Sen Na, Zhuoran Yang, Zhaoran Wang, Mladen Kolar

We study the parameter estimation problem for a varying index coefficient model in high dimensions.

Vocal Bursts Intensity Prediction

Scalable Peaceman-Rachford Splitting Method with Proximal Terms

no code implementations14 Nov 2017 Sen Na, Mingyuan Ma, Mladen Kolar

Along with developing of Peaceman-Rachford Splittling Method (PRSM), many batch algorithms based on it have been studied very deeply.

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