Dongdong Ge
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View article: Physicochemical properties and biocompatibility of 3D printed PVDF-TrFE-CPS composite bone scaffolds with piezoelectric properties
Physicochemical properties and biocompatibility of 3D printed PVDF-TrFE-CPS composite bone scaffolds with piezoelectric properties Open
View article: Ferric Tannate-Enhanced Electrochemical Conditioning Process for Improving Sludge Dewaterability
Ferric Tannate-Enhanced Electrochemical Conditioning Process for Improving Sludge Dewaterability Open
Sludge dewatering is a key step in the overall process of sludge treatment and disposal. In this study, ferric tannate was synthesized by chemically complexing tannic acid with Fe2(SO4)3 under various conditions and then was innovatively e…
View article: BenLOC: A Benchmark for Learning to Configure MIP Optimizers
BenLOC: A Benchmark for Learning to Configure MIP Optimizers Open
The automatic configuration of Mixed-Integer Programming (MIP) optimizers has become increasingly critical as the large number of configurations can significantly affect solver performance. Yet the lack of standardized evaluation framework…
View article: Solver-Informed RL: Grounding Large Language Models for Authentic Optimization Modeling
Solver-Informed RL: Grounding Large Language Models for Authentic Optimization Modeling Open
Optimization modeling is fundamental to decision-making across diverse domains. Despite progress in automating optimization formulation from natural language descriptions, Large Language Models (LLMs) often struggle to generate formally co…
View article: Does Construction of High-Standard Farmland Improve Total Factor Productivity of Grain? Evidence from China, 2000–2021
Does Construction of High-Standard Farmland Improve Total Factor Productivity of Grain? Evidence from China, 2000–2021 Open
This study investigates the impact of China’s construction of high-standard farmland (CHSF) initiatives on grain productivity, focusing on total factor productivity growth of grain (TFPG) from 2000 to 2021. Using a continuous Difference-in…
View article: Investigation of oral microbiome composition in elderly Chinese patients with hypertension: a cross-sectional study
Investigation of oral microbiome composition in elderly Chinese patients with hypertension: a cross-sectional study Open
This study identified distinct oral microbiota in elderly hypertensive patients, highlighting the role of the oral microbiome in hypertension pathogenesis.
View article: Does Financial Credit Obtained From Financial Institutions Influence Agricultural Productivity While Balancing Economic Growth and Sustainability? Empirical Evidence From Sierra Leone Using the VAR Approach
Does Financial Credit Obtained From Financial Institutions Influence Agricultural Productivity While Balancing Economic Growth and Sustainability? Empirical Evidence From Sierra Leone Using the VAR Approach Open
Agriculture dominates Sierra Leone’s economy, employing 75% of the labor force and contributing 64.5% of GDP. Despite its centrality, financial constraints persistently impede sectoral growth, necessitating evidence-based interventions. Th…
View article: Beyond $\mathcal{O}(\sqrt{T})$ Regret: Decoupling Learning and Decision-making in Online Linear Programming
Beyond $\mathcal{O}(\sqrt{T})$ Regret: Decoupling Learning and Decision-making in Online Linear Programming Open
Online linear programming plays an important role in both revenue management and resource allocation, and recent research has focused on developing efficient first-order online learning algorithms. Despite the empirical success of first-or…
View article: A Column-Generation-Based Framework for Dynamic Network Optimization with Service Customization
A Column-Generation-Based Framework for Dynamic Network Optimization with Service Customization Open
View article: Accelerating Low-Rank Factorization-Based Semidefinite Programming Algorithms on GPU
Accelerating Low-Rank Factorization-Based Semidefinite Programming Algorithms on GPU Open
In this paper, we address a long-standing challenge: how to achieve both efficiency and scalability in solving semidefinite programming problems. We propose breakthrough acceleration techniques for a wide range of low-rank factorization-ba…
View article: ORLM: A Customizable Framework in Training Large Models for Automated Optimization Modeling
ORLM: A Customizable Framework in Training Large Models for Automated Optimization Modeling Open
Optimization modeling plays a critical role in the application of Operations Research (OR) tools to address real-world problems, yet they pose challenges and require extensive expertise from OR experts. With the advent of large language mo…
View article: Sketched Newton Value Iteration for Large-Scale Markov Decision Processes
Sketched Newton Value Iteration for Large-Scale Markov Decision Processes Open
Value Iteration (VI) is one of the most classic algorithms for solving Markov Decision Processes (MDPs), which lays the foundations for various more advanced reinforcement learning algorithms, such as Q-learning. VI may take a large number…
View article: Trust Region Methods for Nonconvex Stochastic Optimization beyond Lipschitz Smoothness
Trust Region Methods for Nonconvex Stochastic Optimization beyond Lipschitz Smoothness Open
In many important machine learning applications, the standard assumption of having a globally Lipschitz continuous gradient may fail to hold. This paper delves into a more general (L0, L1)-smoothness setting, which gains particular signifi…
View article: A Low-Rank ADMM Splitting Approach for Semidefinite Programming
A Low-Rank ADMM Splitting Approach for Semidefinite Programming Open
We introduce a new first-order method for solving general semidefinite programming problems, based on the alternating direction method of multipliers (ADMM) and a matrix-splitting technique. Our algorithm has an advantage over the Burer-Mo…
View article: Decoupling Learning and Decision-Making: Breaking the $\mathcal{O}(\sqrt{T})$ Barrier in Online Resource Allocation with First-Order Methods
Decoupling Learning and Decision-Making: Breaking the $\mathcal{O}(\sqrt{T})$ Barrier in Online Resource Allocation with First-Order Methods Open
Online linear programming plays an important role in both revenue management and resource allocation, and recent research has focused on developing efficient first-order online learning algorithms. Despite the empirical success of first-or…
View article: Nonlinear modeling and interior point algorithm for the material flow optimization in petroleum refinery
Nonlinear modeling and interior point algorithm for the material flow optimization in petroleum refinery Open
This paper established a mathematical model with nonconvex bilinear terms. It formulated the complex material flow in the petroleum refinery scenario based on the concept of the "P model". The mathematical model described the nonlinear co…
View article: Dispatching Automated Guided Vehicles Using Efficient Data-Driven Optimization
Dispatching Automated Guided Vehicles Using Efficient Data-Driven Optimization Open
View article: Early Birds versus Last-Minute Arrivals: Empirical Evidence and Theoretical Analysis of Arrival Time Queueing Game
Early Birds versus Last-Minute Arrivals: Empirical Evidence and Theoretical Analysis of Arrival Time Queueing Game Open
View article: cuPDLP-C: A Strengthened Implementation of cuPDLP for Linear Programming by C language
cuPDLP-C: A Strengthened Implementation of cuPDLP for Linear Programming by C language Open
A recent GPU implementation of the Restarted Primal-Dual Hybrid Gradient Method for Linear Programming was proposed in Lu and Yang (2023). Its computational results demonstrate the significant computational advantages of the GPU-based firs…
View article: Beyond Nonconvexity: A Universal Trust-Region Method with New Analyses
Beyond Nonconvexity: A Universal Trust-Region Method with New Analyses Open
The trust-region (TR) method is renowned historically for its robustness in nonconvex problems and extraordinary numerical performance, but the study of its performance in convex optimization is somehow limited. This paper complements the …
View article: Trust Region Methods For Nonconvex Stochastic Optimization Beyond Lipschitz Smoothness
Trust Region Methods For Nonconvex Stochastic Optimization Beyond Lipschitz Smoothness Open
In many important machine learning applications, the standard assumption of having a globally Lipschitz continuous gradient may fail to hold. This paper delves into a more general $(L_0, L_1)$-smoothness setting, which gains particular sig…
View article: A Homogenization Approach for Gradient-Dominated Stochastic Optimization
A Homogenization Approach for Gradient-Dominated Stochastic Optimization Open
Gradient dominance property is a condition weaker than strong convexity, yet sufficiently ensures global convergence even in non-convex optimization. This property finds wide applications in machine learning, reinforcement learning (RL), a…
View article: Learning to Pivot as a Smart Expert
Learning to Pivot as a Smart Expert Open
Linear programming has been practically solved mainly by simplex and interior point methods. Compared with the weakly polynomial complexity obtained by the interior point methods, the existence of strongly polynomial bounds for the length …
View article: Effects of Biochar on Sludge Composting
Effects of Biochar on Sludge Composting Open
Sewage sludge will pose a serious threat to the environment and human health. The composting process can recycle sludge effectively, but it still has some drawbacks. Many studies suggest that biochar addition in sludge composting can effec…
View article: Homogeneous Second-Order Descent Framework: A Fast Alternative to Newton-Type Methods
Homogeneous Second-Order Descent Framework: A Fast Alternative to Newton-Type Methods Open
This paper proposes a homogeneous second-order descent framework (HSODF) for nonconvex and convex optimization based on the generalized homogeneous model (GHM). In comparison to the Newton steps, the GHM can be solved by extremal symmetric…
View article: Research on Spatial-Temporal Characteristics and Affecting Factors of Agricultural Green Total Factor Productivity in Jiangxi Province
Research on Spatial-Temporal Characteristics and Affecting Factors of Agricultural Green Total Factor Productivity in Jiangxi Province Open
Increasing green total factor productivity is the key to achieving green development in agriculture. This study measured the green total factor productivity of Jiangxi’s agriculture, and its regional and temporal evolution characteristics …
View article: Data-driven Mixed Integer Optimization through Probabilistic Multi-variable Branching
Data-driven Mixed Integer Optimization through Probabilistic Multi-variable Branching Open
In this paper, we propose a Pre-trained Mixed Integer Optimization framework (PreMIO) that accelerates online mixed integer program (MIP) solving with offline datasets and machine learning models. Our method is based on a data-driven multi…
View article: Research on Spatial-temporal Characteristics and Affecting Factors of Agricultural Green Total Factor Productivity in Jiangxi Province
Research on Spatial-temporal Characteristics and Affecting Factors of Agricultural Green Total Factor Productivity in Jiangxi Province Open
Increasing green total factor productivity is the key to achieving green development in agriculture. This study measured the green total factor productivity of Jiangxi’s agriculture, and its regional and temporal evolution characteristics …
View article: The Impact of Rural Households’ Part-Time Farming on Grain Output: Promotion or Inhibition?
The Impact of Rural Households’ Part-Time Farming on Grain Output: Promotion or Inhibition? Open
Given the prevalence of part-time farming behaviors in rural households, studying the impact of part-time farming behaviors on grain output is of great practical significance. Using a panel dataset of 5629 Chinese national rural fixed obse…
View article: Stochastic Dimension-reduced Second-order Methods for Policy Optimization
Stochastic Dimension-reduced Second-order Methods for Policy Optimization Open
In this paper, we propose several new stochastic second-order algorithms for policy optimization that only require gradient and Hessian-vector product in each iteration, making them computationally efficient and comparable to policy gradie…