FAI-Seminar: Previous Talks
2024 R02
| Time | Speaker | Talk Title | Talk Info | Paper | Video |
| 07/19 | 张博航 (北京大学) |
Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness | Talk Info | [1], [2], [3] |
B站 |
| 08/09 | 黎善达 (CMU) |
Inference Scaling Law of Large Language Models and Second-Prize Winning Solution of AIMO | Talk Info | [1], [2] | B站 |
| 08/16 | 王天浩 (TTIC) |
Tractable training dynamics of transformers for in-context learning | Talk Info | [1], [2] | B站 |
| 08/23 | 吴京风 (Berkeley) |
Reimaging Gradient Descent: Large Stepsize, Oscillation, and Acceleration | Talk Info | [1] | B站 |
| 08/30 | 马梓业 (港城大) |
Navigating the non-convex landscape via amplifying escape directions of saddle points | Talk Info | [1], [2], [3] |
B站 |
| 11/01 | 刘勇 (中国人民大学) |
Can Retrieval Augmented Generation (RAG) Enhance the LLM’s Reasoning Capabilities? | Talk Info | B站 |
2024 R01
| Time | Speaker | Talk Title | Talk Info | Paper | Video |
| Special talk 05/31 | 李建 (清华大学) |
Generalization Error and Implicit Bias of Gradient Methods in Deep Learning | Talk Info | B站 | |
| 03/08 | 翟润天 (CMU) |
On the Generalization of Representation Learning and Big Foundation Models | Talk Info | [1, 2] | B站 |
| 03/15 | 罗胜杰 (北京大学) |
Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products | Talk Info | [1] | B站 |
| 03/22 | 高天宇(Princeton) | Long-Context Language Modeling with Parallel Context Encoding | Talk Info | B站 | |
| 03/29 | 邹荻凡 (香港大学) |
Faster Sampling without Isoperimetry via Diffusion-based Monte Carlo | Talk Info | [1] | B站 |
| 04/05 | 陆一平 (NYU) |
Simulation-Calibrated Scientific Machine Learning | Talk Info | [1] | B站 |
| 04/12 | 俞鼎力(Princeton) | Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks | Talk Info | [1] | B站 |
| 04/19 | 吕凯风(Princeton) | Understanding the Limitations of Neural Networks on Algorithmic Reasoning | Talk Info | [1, 2] | B站 |
| 04/26 | 李禹辰 (CMU) |
Towards Mathematical Understanding of Modern Language Models | Talk Info | [1, 2, 3, 4] |
B站 |
2023 R03
| Time | Speaker | Talk Title | Talk Info | Paper | Video |
| Special Talk 2/16 | 胡威 (UMich) |
Hidden Structures in Neural Network Representations | Talk Info | [1, 2] | B站 |
| 11/10 | 陈乐偲 (清华大学) |
Near-Optimal Nonconvex-Strongly-Convex Bilevel Optimization with Fully First-Order Oracles | Talk Info | [1] | B站 |
| 11/17 | 张博航 (北京大学) |
Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective | Talk Info | [1] | B站 |
| 11/24 | 顾欣然 (清华大学) |
A Quadratic Synchronization Rule for Distributed Deep Learning | Talk Info | [1] | B站 |
| 12/1 | 石佳欣(DeepMind) | MultiresConv: From Wavelet Theory to Long Context Modeling with Neural Networks | Talk Info | [1] | B站 |
| 12/8 | 范凤磊 (香港中文 大学) |
In Pursuit of Deciphering ReLU Networks and Beyond | Talk Info | [1] | B站 |
| 12/15 | NeurIPS break | ||||
| 12/22 | 刘冰彬 (CMU) |
Thinking Fast with Transformers: algorithmic reasoning with shortcuts | Talk Info | [1] (ICLR 23' oral), [2] (NeurIPS 23' spotlight) | B站 |
| 12/29 | 温凯越 (清华大学) |
Transformers are uninterpretable with myopic methods: a case study with bounded Dyck grammars | Talk Info | [1] | B站 |
| 1/12 | 游凯超 (清华大学) |
Understand, Learn, and Adopt the PyTorch compiler (torch.compile) | Talk Info | [1, 2, 3] | B站 |
2023 R02
| Time | Speaker | Talk Title | Paper | Video |
| (Special)09/15 | 李志远 (Stanford) |
The Generalization Benefit of Flatnes Regularization | [1][2] | B站 |
| 06/23 | 张博航 (北京大学) |
Understanding the Expressivity of Subgraph-based GNNs for Graph Learning | [1] | B站 |
| 06/30 | 罗胜杰 (北京大学) |
One Transformer Can Understand Both 2D & 3D Molecular Data | [1] | B站 |
| 07/07 | 刘子鸣 (MIT) |
Intelligence from hunger | [1], [2] | B站 |
| 07/14 | 马鉴昊 (UMich) |
Robust Sparse Mean Estimation | [1] | B站 |
| 07/21 | 金及凯 (北京大学) |
Minimax optimal operator learning | [1] | B站 |
| 07/28 | ICML break | |||
| 08/04 | 王博涵 (中国科学 技术大学) |
When and Why Momentum Accelerates SGD | [1] | B站 |
| 08/11 | 滕佳烨 (清华大学) |
Predictive inference with feature conformal prediction | [1] | B站 |
| 08/18 | 蔡天乐 (Princeton) |
Large Language Models as Tool Makers | [1] | B站 |
2023 R01
| Time | Speaker | Talk Title | Paper | Video |
| (Special) 05/26 | 张景昭 (清华大学) |
Two Phases of Scaling Laws for Nearest Neighbor Classifiers | [1] | B站 |
| 03/03 | 张鼎怀 (Mila) |
GFlowNets: Exploration for Probabilistic Inference | [1],[2],[3],[4] | B站 |
| 03/10 | 顾欣然 (清华大学) |
Why (and When) does Local SGD Generalize Better than SGD | [1] | B站 |
| 03/17 | 王博涵 (中国科学 技术大学) |
Provable Benefit of Adaptivity in ADAM | [1] | B站 |
| 03/24 | 温凯越 (清华大学) |
How Does Sharpness-Aware Minimization Minimize Sharpness? | [1] | B站 |
| 03/31 | 张博航 (北京大学) |
Rethinking the Expressive Power of GNNs via Graph Biconnectivity | [1] (ICLR 2023 Outstanding Paper) | B站 |
| 04/07 | 马鉴昊(UMich) | Escaping Saddle Points Or Not? | [1], [2] | B站 |
| 04/14 | 陈乐偲 (复旦大学) |
On Bilevel Optimization without Lower-level Strong Convexity | [1] | B站 |
| 04/21 | 黄凯旋(Princeton) | Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data | [1] | B站 |
| 04/28 | 戴言 (清华大学) |
Variance-Aware Sparse Linear Bandits | [1] | B站 |