Rieken Luo

PhD Student, Institute of Science and Technology Austria (ISTA)

Am Campus 1, 3400 Klosterneuburg, Austria · rluo@ist.ac.at

Research

My research focuses on the intersection of optimization, games, and machine learning. Specifically, I have been working on:

• Communication-efficient algorithms for distributed consensus optimization
  • Revisiting LocalSGD and SCAFFOLD: Improved Rates and Missing Analysis. AISTATS'25
  • On the Convergence of Local SGD under Third-Order Smoothness and Hessian Similarity. OPT'23
• Efficient protocols for multiplayer games
  • Monotone Near-Zero-Sum Games. ICLR'26
  • Efficient Gradient Methods for Distributed Saddle Problems. Submitted
• Complexity and algorithms for sequential decision-making problems
  • Linear Equations with Min and Max Operators: Computational Complexity. AAAI'25 (Oral)
  • Algorithms for Linear Equations with Min and Max Operators under (Absolutely) Halting Condition. Submitted
  • Improved Algorithmic Analysis for Stochastic Games. Submitted
  • Algorithms with Smoothed Polynomial-Time Complexity for Deterministic Discounted-sum and Mean-payoff Games. In preparation

News

In the summer of 2026, I will be working at Microsoft Research Cambridge as a Research Intern in Machine Learning.