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Workshop Sat, Dec 6, 2025 • 8:00 AM – 5:00 PM PST Upper Level Room 7

Dynamics at the Frontiers of Optimization, Sampling, and Games

Tatjana Chavdarova · Dilsad Er · Niao He · Michael Jordan · Eric Moulines · Michael Muehlebach · Molei Tao · Andre Wibisono
Project Page [ OpenReview] 

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Schedule

Timezone: America/Los_Angeles
8:55 AM
Opening Remarks
9:35 AM
Invited Talk by Philippe Rigollet (MIT)
Philippe Rigollet
10:10 AM
Distribution Dynamics in Stochastic Optimization: A Decision-Dependent Formulation
Zhiyu He · Saverio Bolognani · Florian Dorfler · Michael Muehlebach
10:35 AM
When Scores Learn Geometry: Rate Separations under the Manifold Hypothesis
Xiang Li · Zebang Shen · Ya-Ping Hsieh · Niao He
11:30 AM
Poster Session 1
→ Distribution Dynamics in Stochastic Optimization: A Decision-Dependent Formulation
Zhiyu He · Saverio Bolognani · Florian Dorfler · Michael Muehlebach
→ Game Dynamics in Multi-agent Performative Prediction: A Case Study in Mortgage Competition
Guanghui Wang · Krishna Acharya · Lokranjan Lakshmikanthan · Vidya Muthukumar · Juba Ziani
→ Schrödinger Bridge as Robustified Optimal Transport Flows
Jinxin Wang · Ya-Ping Hsieh · Bahar Taskesen
→ PiKE: Adaptive Data Mixing for Large-Scale Multi-Task Learning Under Low Gradient Conflicts
Zeman Li · Yuan Deng · Peilin Zhong · Meisam Razaviyayn · Vahab Mirrokni
→ From Randomized Hamiltonian Flow to Fast Stochastic Optimization
Austin Feng · Qiang Fu · Xiuyuan Wang · Andre Wibisono
→ Larger Datasets Can Be Repeated More: A Theoretical Analysis of Multi-Epoch Scaling in Linear Regression
Tingkai Yan · Haodong Wen · Binghui Li · Kairong Luo · Wenguang Chen · Kaifeng Lyu
→ On Separation Between Best-Iterate, Random-Iterate, and Last-Iterate Convergence of Learning in Games
Yang Cai · Gabriele Farina · Julien Grand-Clément · Christian Kroer · Chung-Wei Lee · Haipeng Luo · Weiqiang Zheng
→ Global Convergence of Gradient EM for Over-Parameterized Gaussian Mixtures
Mo Zhou · Weihang Xu · Maryam Fazel · Simon Du
→ Data Generation without Function Estimation
Hadi Daneshmand · Ashkan Soleymani
→ High-dimensional Mean-Field Games by Particle-based Flow Matching
Jiajia Yu · Junghwan Lee · Yao Xie · Xiuyuan Cheng
→ Decoding Silence through Neural Estimation in Stochastic Dynamical Systems
Shubham Aggarwal · Dipankar Maity · Tamer Basar
→ Adaptive kernel selection for Stein Variational Gradient Descent
Moritz Melcher · Simon Weissmann · Ashia Wilson · Jakob Zech
→ Task-Level Insights from Eigenvalues across Sequence Models
Jelena Trisovic · Rahel Rickenbach · Alexandre Didier · Melanie Zeilinger · Jerome Sieber
→ Rethinking Langevin Thompson Sampling from A Stochastic Approximation Perspective
Weixin Wang · Haoyang Zheng · Guang Lin · Wei Deng · Pan Xu
12:55 PM
Best Paper Award and Talk: On Separation Between Best-Iterate, Random-Iterate, and Last-Iterate Convergence of Learning in Games
Yang Cai · Weiqiang Zheng · Haipeng Luo · Christian Kroer · Gabriele Farina · Julien Grand-Clément · Chung-Wei Lee
3:00 PM
On the Mixing Time of Unadjusted Hamiltonian Monte Carlo in KL Divergence
Nawaf Bou-Rabee · Siddharth Mitra · Andre Wibisono
→ When Scores Learn Geometry: Rate Separations under the Manifold Hypothesis
Xiang Li · Zebang Shen · Ya-Ping Hsieh · Niao He
→ On the Mixing Time of Unadjusted Hamiltonian Monte Carlo in KL Divergence
Nawaf Bou-Rabee · Siddharth Mitra · Andre Wibisono
→ Preference Graphs and the Attractors of Regularized Learning in Games
Omar Abbadi · Rida Laraki · Panayotis Mertikopoulos
→ Landing with the Score: Riemannian Optimization through Denoising
Andrey Kharitenko · Zebang Shen · Riccardo De Santi · Niao He · Florian Dorfler
→ A New Approach to Controlling Linear Dynamical Systems
Anand Brahmbhatt · Gon Buzaglo · Sofiia Druchyna · Elad Hazan
→ Almost sure convergence analysis of regularized SGD
Sebastian Kassing · Simon Weissmann · Leif Döring
→ Optimal Algorithms for Bandit Learning in Matching Markets
Tejas Pagare · Agniv Bandyopadhyay · Sandeep Juneja
→ Automated algorithm design via Nevanlinna-Pick interpolation
Ibrahim Kurban Ozaslan · Tryphon Georgiou · Mihailo Jovanovic
→ Distributed Low-Communication Training with Decoupled Momentum Optimization
Sasho Nedelkoski · Alexander Acker · Odej Kao · Soeren Becker · Dominik Scheinert
→ ALPs: Adaptive Lookahead Policy Gradients for Multi-Agent Reinforcement Learning
Aniket Sanyal · Baraah Adil Mohammed Sidahmed · Rebekka Burkholz · Tatjana Chavdarova
→ Cautious Optimism: A Meta-Algorithm for Near-Constant Regret in General Games
Ashkan Soleymani · Georgios Piliouras · Gabriele Farina
→ Fictitious Play in Product Markov Games With Kullback-Leibler Control Cost
Khaled Nakhleh · Sarper Aydin · Ceyhun Eksin · Sabit Ekin
4:55 PM
Closing Remarks