Optimality and NP-Hardness of Transformers in Learning Markovian Dynamical Functions
- Yanna Ding
- Songtao Lu
- et al.
- 2025
- NeurIPS 2025
Yingdong Lu
Title
Research Staff Member
Bio
I am a researcher in Mathematical Sciences. My reseach interests are in the areas of analysis and probability.
I studied mathmatics and operations research at Peking University in Beijing and Columbia University in the city of New York.
Publications
Fast Linear Solvers via AI-Tuned Markov Chain Monte Carlo-based Matrix Inversion
- Anton Lebedev
- Winkyung Lee
- et al.
- 2025
- SC 2025
Hamiltonian Monte Carlo with Asymmetrical Momentum Distributions
- Soumyadip Ghosh
- Yingdong Lu
- et al.
- 2025
- Physica D: Nonlinear Phenomena
Power iteration with probabilistic updates for systems with heterogeneous performance
- Soumyadip Ghosh
- Lior Horesh
- et al.
- 2025
- HPEC 2025
On Representations of Mean-Field Variational Inference
- Soumyadip Ghosh
- Yingdong Lu
- et al.
- 2025
- Journal of Applied Analysis
On The Variance of Schatten 𝑝-Norm Estimation with Gaussian Sketching Matrices
- Lior Horesh
- Vasileios Kalantzis
- et al.
- 2025
- Monte Carlo Methods Appl.
SPRIG: Stackelberg Perception-Reinforcement Learning with Internal Game Dynamics
- Fernando Martinez
- Juntao Chen
- et al.
- 2025
- AAAI 2025
Federated Learning for Discrete Optimal Transport with Large Population under Incomplete Information
- Juntao Chen
- Yingdong Lu
- 2024
- ISMP 2024
On Representations of Mean-Field Variational Inference
- Soumyadip Ghosh
- Yingdong Lu
- et al.
- 2023
- NeurIPS 2023
General Markov Decision Process Framework for Directly Learning Optimal Control Policies
- 2023
- SIAM CT 2023
Top collaborators
LH
Lior Horesh
Senior Manager, Mathematics & Theoretical Computer Science
MS
Mark S. Squillante
Distinguished Research Staff Member and Manager, Foundations of Probability and Dynamics, Math Sciences
CW
Chai Wah Wu
Principal Research Staff Member