Search Results for author: Shuzhong Zhang

Found 16 papers, 1 papers with code

A Unified Analysis for the Subgradient Methods Minimizing Composite Nonconvex, Nonsmooth and Non-Lipschitz Functions

no code implementations30 Aug 2023 Daoli Zhu, Lei Zhao, Shuzhong Zhang

In this paper we propose a proximal subgradient method (Prox-SubGrad) for solving nonconvex and nonsmooth optimization problems without assuming Lipschitz continuity conditions.

Stochastic Optimization

An Augmented Lagrangian Approach to Conically Constrained Non-monotone Variational Inequality Problems

no code implementations2 Jun 2023 Lei Zhao, Daoli Zhu, Shuzhong Zhang

Under an assumption, to be called the primal-dual variational coherence condition in the paper, we prove the convergence of ALAVI.

Cubic-Regularized Newton for Spectral Constrained Matrix Optimization and its Application to Fairness

no code implementations2 Sep 2022 Casey Garner, Gilad Lerman, Shuzhong Zhang

Matrix functions are utilized to rewrite smooth spectral constrained matrix optimization problems as smooth unconstrained problems over the set of symmetric matrices which are then solved via the cubic-regularized Newton method.

Fairness

Distributionally Robust Newsvendor with Moment Constraints

no code implementations30 Oct 2020 Derek Singh, Shuzhong Zhang

This paper expands the work on distributionally robust newsvendor to incorporate moment constraints.

Binary Random Projections with Controllable Sparsity Patterns

no code implementations29 Jun 2020 Wenye Li, Shuzhong Zhang

Random projection is often used to project higher-dimensional vectors onto a lower-dimensional space, while approximately preserving their pairwise distances.

Distributionally Robust Profit Opportunities

no code implementations18 Jun 2020 Derek Singh, Shuzhong Zhang

This paper expands the notion of robust profit opportunities in financial markets to incorporate distributional uncertainty using Wasserstein distance as the ambiguity measure.

Robust Arbitrage Conditions for Financial Markets

no code implementations20 Apr 2020 Derek Singh, Shuzhong Zhang

A relaxation is introduced for which we coin the term statistical arbitrage.

Distributionally Robust XVA via Wasserstein Distance: Wrong Way Counterparty Credit and Funding Risk

no code implementations4 Oct 2019 Derek Singh, Shuzhong Zhang

This paper investigates calculations of robust XVA, in particular, credit valuation adjustment (CVA) and funding valuation adjustment (FVA) for over-the-counter derivatives under distributional uncertainty using Wasserstein distance as the ambiguity measure.

An ADMM-Based Interior-Point Method for Large-Scale Linear Programming

1 code implementation31 May 2018 Tianyi Lin, Shiqian Ma, Yinyu Ye, Shuzhong Zhang

Due its connection to Newton's method, IPM is often classified as second-order method -- a genre that is attached with stability and accuracy at the expense of scalability.

Optimization and Control

Highly accurate model for prediction of lung nodule malignancy with CT scans

no code implementations6 Feb 2018 Jason Causey, Junyu Zhang, Shiqian Ma, Bo Jiang, Jake Qualls, David G. Politte, Fred Prior, Shuzhong Zhang, Xiuzhen Huang

Here we present NoduleX, a systematic approach to predict lung nodule malignancy from CT data, based on deep learning convolutional neural networks (CNN).

Computed Tomography (CT)

Primal-Dual Optimization Algorithms over Riemannian Manifolds: an Iteration Complexity Analysis

no code implementations5 Oct 2017 Junyu Zhang, Shiqian Ma, Shuzhong Zhang

For prohibitively large-size tensor or machine learning models, we present a sampling-based stochastic algorithm with the same iteration complexity bound in expectation.

BIG-bench Machine Learning Community Detection +1

Accelerated Primal-Dual Proximal Block Coordinate Updating Methods for Constrained Convex Optimization

no code implementations17 Feb 2017 Yangyang Xu, Shuzhong Zhang

We show that the rate can be accelerated to $O(1/t^2)$ if the objective is strongly convex.

Randomized Primal-Dual Proximal Block Coordinate Updates

no code implementations19 May 2016 Xiang Gao, Yangyang Xu, Shuzhong Zhang

Assuming mere convexity, we establish its $O(1/t)$ convergence rate in terms of the objective value and feasibility measure.

Structured Nonconvex and Nonsmooth Optimization: Algorithms and Iteration Complexity Analysis

no code implementations9 May 2016 Bo Jiang, Tianyi Lin, Shiqian Ma, Shuzhong Zhang

In particular, we consider in this paper some constrained nonconvex optimization models in block decision variables, with or without coupled affine constraints.

Global Convergence of Unmodified 3-Block ADMM for a Class of Convex Minimization Problems

no code implementations16 May 2015 Tianyi Lin, Shiqian Ma, Shuzhong Zhang

The alternating direction method of multipliers (ADMM) has been successfully applied to solve structured convex optimization problems due to its superior practical performance.

An Extragradient-Based Alternating Direction Method for Convex Minimization

no code implementations27 Jan 2013 Tianyi Lin, Shiqian Ma, Shuzhong Zhang

The classical alternating direction type methods usually assume that the two convex functions have relatively easy proximal mappings.

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