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Workshop Sat, Dec 6, 2025 • 8:00 AM – 5:00 PM PST

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
4:20 PM
Panel "Dynamical Systems at the Frontier of Optimization, Sampling, and Games: Insights, Tools, and Future Directions"
Jacob Abernethy ⋅ Yi-An Ma ⋅ Krishnakumar Balasubramanian ⋅ Tatjana Chavdarova
4:55 PM
Closing Remarks