| Time&Date |
Monday (August 24) |
Tuesday (August 25) |
Wednesday (August 26) |
Thursday (August 27) |
Friday (August 28) |
| 7:30-8:30 |
Breakfast (60 minutes) |
| Chair |
Alexey Naumov |
Alexey Naumov |
|
Nikita Puchkin |
Nikita Puchkin |
| 9:00-10:00 |
Michal Valko: The genesis of predictive architectures |
Michal Valko: The genesis of predictive architectures |
2 talks by PhD students:
9:00-9:25 - Jiaxin Shi
9:30-10:00 - Wei Yao |
Gen Li: Foundations of Diffusion Generative Models |
Gen Li: Foundations of Diffusion Generative Models
|
| 10:00-10:30 |
Coffee Break (within 30 minutes) |
| Chair |
Yuhao Wang |
Gen Li |
|
Sergey Samsonov |
Sergey Samsonov |
| 10:30-11:10 |
Vladimir Spokoiny: Manifold Gaussian Mixture Models |
Kenji Fukumizu: Flow Matching from Viewpoint of Proximal Operator |
3 talks by PhD students: 10:30-10:55 - Yuzhe Yuan 11:00-11:25 - Nikita Morozov 11:30-11:55 - Ilya Levin |
Miha Bresar: Diffeomorphic Markov Chain Monte Carlo: fast mixing for heavy-tailed distributions |
Maxim Rakhuba: Linear Algebra Problems and Algorithms in Muon-based Optimization Methods |
| 11:15-11:55 |
Bingyi Jing: Balancing Intelligence and Efficiency in Large Language Models |
Nikita Puchkin: Stochastic optimal control approach to generative modelling and Schrödinger potential estimation |
Hoi-To Wai: Stochastic Approximation Schemes with Decision-Dependent Samples: The Case of Performative Prediction |
Praneeth Vepakomma: Modulated learning for private and distributed regression with just a single sample perclient device |
| 12:00-13:30 |
Lunch (90 minutes) |
| Chair |
Free Discussion |
Gen Li |
Free Discussion |
Jing Binyi |
Free Discussion |
| 13:30-14:10 |
Aibek Alanov: Accelerated Inference for Diffusion Models |
Denis Belomestny: Statistical analysis of Inverse Entropy-regularized Reinforcement Learning |
| 14:15-14:55 |
Alex Lamb: Next-Latent Prediction Transformers Learn Compact World Models |
Zhiheng Zhang: Wasserstein Policy Learning for Distributional Outcomes |
| 15:00-15:30 |
Coffee Break (within 30 minutes) |
Coffee Break (within 30 minutes) |
| Chair |
Alexey Naumov |
Jing Binyi |
| 15:30-16:10 |
Tengyao Wang: Optimal in-context adaptivity and distributional robustness of transformers |
Junpei Komiyama: Statistical Certification for Majority Voting |
| 16:15-16:55 |
Yunbei Xu: Pointwise Generalization in Deep Neural Networks |
Lei Wu: Functional Scaling Laws for LLM Pretraining |
| 17:00-17:40 |
Konstantin Yakovlev: Generalization bounds for Diffusion Models and Beyond
|
Marina Sheshukova: Gaussian Approximation and Bootstrap Inference for Stochastic Gradient Methods and Reinforcement Learning |
|
|
Group photo (17:40-18:00) |
|
|
|
| 18:00 |
Dinner |
Banquet (18:00-20:00) |
Dinner |
