Recent Papers
For most recent papers see my Google Scholar Link.
Online Linear Programming for Multi-Objective Routing in LLM Serving (2026)
Solver-Informed RL: Grounding Large Language Models for Authentic Optimization Modeling (2026)
A Universal Load Balancing Principle and Its Application to Large Language Model Serving (2026)
Computations and complexities of Tarski;s fixed points and supermodular games (2026)
A Restarted Primal-Dual Hybrid Conjugate Gradient Method for Large-Scale Quadratic Programming (2025)
Robustifying Conditional Portfolio Decisions via Optimal Transport (2025)
A Low-Rank ADMM Splitting Approach for Semidefinite Programming (2025)
Accelerating Low-Rank Factorization-Based Semidefinite Programming Algorithms on GPU
(2025)
Adam-mini: Use Fewer Learning Rates To Gain More (2025)
HDSDP: Software for Semidefinite Programming (2025)
Optimal Diagonal Preconditioning (2025)
From an Interior Point to a Corner Point: Smart Crossover (2025)
An Alternating Direction Method of Multipliers-Based Interior Point Method for Linear and Conic Optimization (2025)
Decoupling Learning and Decision-Making: Breaking the \mathcalO(\sqrtT)
Barrier in Online Resource Allocation with First-Order Methods (2024)
SOLNP+: A Derivative-Free Solver for Constrained Nonlinear Optimization (2024)
Data-driven aerodynamic shape design with distributionally robust optimization approaches (2024)
An Improved Analysis of LP-Based Control for Revenue Management (2024)
Diffusion Model for Data-Driven Black-Box Optimization (2024)
Sample Complexity for Constrained Markov Decision Process (2024)
A Riemannian Dimention-reduced Second Order Method with Application in Sensor Network Localization (2024)
Scalable Approximate Optimal Diagonal Preconditioning (2024)
A Universal Trust-Region Method for Convex and Nonconvex Optimization (2024)
Trust Region Methods For Nonconvex Stochastic Optimization Beyond Lipschitz Smoothness (2024)
Learning to Pivot as a Smart Expert (2024)
cuPDLP-C: A Strengthened Implementation of cuPDLP for Linear Programming by C language (2023)
A Homogenization Approach for Gradient-Dominated Stochastic Optimization (2023)
Solving Linear Programs with Fast Online Learning Algorithms (2023)
Homogeneous Second-Order Descent Framework: A Fast Alternative to Newton-Type Methods (2023)
Variance reduced value iteration and faster algorithms for solving Markov decision processes (2023)
A Homogenization Approach for Gradient-Dominated Stochastic Optimization (2023)
Solving Linear Programs with Fast Online Learning Algorithms (2023)
Pre-trained Mixed Integer Optimization through Multi-variable Cardinality Branching (2023)
A gradient descent akin method for constrained optimization: algorithms and applications (2023)
DIMENSION-REDUCED ADAPTIVE GRADIENT METHOD (2023)
Stochastic Dimension-reduced Second-order Methods for Policy Optimization (2023)
A Homogenous Second-Order Descent Method for Nonconvex Optimization (2022)
How Small Amount of Data Sharing Benefits Distributed Optimization and Learning (2022)
DRSOM: A Dimension Reduced Second-Order Method and Preliminary Analyses (2022)
Fairer LP-based Online Allocation via Analytic Center (2022)
A Second-Order Path-Following Algorithm for
Unconstrained Convex Optimization (2017)
Market Making with Model Uncertainty (2015)
On a First-Order Potential Reduction Algorithm for
Linear Programming (2015)
Online Allocation Rules in Display Advertising (2014)
Sparse Portfolio Selection via Quasi-Norm Regularization (2013)
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