Older Updates
- May 2024: Paper "Improved Convergence of Score-Based Diffusion Models via Prediction-Correction" (joint with Francesco and Jan) accepted to Transactions on Machine Learning Research (TMLR). This was also presented at the NeurIPS 2023 Workshop on Diffusion Models. Congratulations Francesco!
- May 2024: Two papers accepted at the 2024 Conference on Learning Theory (COLT'24): "Contraction of Markovian Operators in Orlicz Spaces and Error Bounds for Markov Chain Monte Carlo" (joint with Amedeo), "Spectral Estimators for Structured Generalized Linear Models via Approximate Message Passing" (joint with Yihan, Hong Chang and Ramji). Congratulations Amedeo and Yihan!
- May 2024: Three papers accepted at the 2024 International Conference on Machine Learning (ICML'24): "Compression of Structured Data with Autoencoders: Provable Benefit of Nonlinearities and Depth" (joint with Kevin, Alex and Hamed), "Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features" (joint with Simone), and "How Spurious Features are Memorized: Precise Analysis for Random and NTK Features" (joint with Simone). The last paper was also presented at the NeurIPS 2023 Workshop on Mathematics of Modern Machine Learning. Congratulations Kevin, Alex and Simone!
- February 2024: Paper "Concentration without Independence via Information Measures" (joint with Amedeo) accepted in IEEE Transactions on Information Theory. Congratulations Amedeo!
- September 2023: Paper accepted as a spotlight at the 2023 Conference on Neural Information Processing Systems (NeurIPS'23): "Deep Neural Collapse Is Provably Optimal for the Deep Unconstrained Features Model" (joint with Peter and Christoph). Congratulations Peter!
- July 2023: Paper "Fundamental limits in structured principal component analysis and how to reach them" (joint with Jean, Francesco and Manuel) accepted in the Proceedings of the National Academy of Sciences (PNAS).
- April 2023: Two papers accepted as oral presentations at the 2023 International Conference on Machine Learning (ICML'23): "Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels" (joint with Simone and Shayan), and "Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods" (joint with Alex, Kevin and Hamed). Congratulations Simone, Alex and Kevin!
- April 2023: Two papers accepted at the 2023 IEEE International Symposium on Information Theory (ISIT'23): "Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise" (joint with Teng, YuHao, Jean, ShanSuo and TianQi), and "Concentration without Independence via Information Measures" (joint with Amedeo). Congratulations Amedeo!
- March 2023: Tutorial on "Approximate Message Passing for High-Dimensional Inference" (with Cynthia Rush and Ramji Venkataramanan) accepted at the 2023 IEEE International Symposium on Information Theory (ISIT'23).
- February 2023: Paper "Approximate Message Passing for Multi-Layer Estimation in Rotationally Invariant Models" (joint with Yizhou, TianQi and ShanSuo) accepted at the IEEE Information Theory Workshop 2023 (ITW'23).
- February 2023: Paper "Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence" (joint with Diyuan and Vyacheslav) accepted to Transactions on Machine Learning Research (TMLR). This was also presented at the OPT 2022 NeurIPS workshop. Congratulations Diyuan!
- November 2022: New paper on arXiv: "Precise Asymptotics for Spectral Methods in Mixed Generalized Linear Models" (joint with Yihan and Ramji).
- September 2022: Two papers accepted at the 2022 Conference on Neural Information Processing Systems (NeurIPS'22): "The price of ignorance: how much does it cost to forget noise structure in low-rank matrix estimation?" (joint with Jean, TianQi and Manuel), and "Memorization and Optimization in Deep Neural Networks with Minimum Over-parameterization" (joint with Simone and Mohammad). Congratulations Simone and Mohammad! Simone will also present this work as a talk at the 2022 Conference on the Mathematical Theory of Deep Neural Networks.
- September 2022: Paper "Decoding Reed-Muller Codes with Successive Codeword Permutations" (joint with Nghia, Ali and Warren) accepted in IEEE Transactions on Wireless Communications.
- August 2022: Paper "Sharp asymptotics on the compression of two-layer neural networks" (joint with Mohammad, Simone, Rattana and Stefano) accepted at the IEEE Information Theory Workshop 2022 (ITW'22). Congratulations Mohammad, Simone and Rattana!
- June 2022: Paper "Approximate Message Passing with Spectral Initialization for Generalized Linear Models" (joint with Ramji) invited to the 2022 Machine Learning Special Issue of the Journal of Statistical Mechanics, Theory and Experiment (JSTAT). This paper was previously accepted at the 2021 International Conference on Artificial Intelligence and Statistics (AISTATS'21).
- May 2022: Paper "Estimation in Rotationally Invariant Generalized Linear Models via Approximate Message Passing" (joint with Ramji and Kevin) accepted at the 2022 International Conference on Machine Learning (ICML'22). Congratulations Kevin!
- April 2022: Paper "Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks" (joint with Alex and Vyacheslav) accepted to the Journal of Machine Learning Research (JMLR). Congratulations Alex! A poster about this work was presented at the 2021 Conference on the Mathematical Theory of Deep Neural Networks.
- April 2022: Paper "Polar Coded Computing: The Role of the Scaling Exponent" accepted at the 2022 IEEE International Symposium on Information Theory (ISIT'22). Congratulations Dorsa!
- December 2021: Two papers presented at the 2021 Conference on Neural Information Processing Systems (NeurIPS'21): "PCA Initialization for Approximate Message Passing in Rotationally Invariant Models" (joint with Ramji), and "When Are Solutions Connected in Deep Networks?" (joint with Quynh and Pierre).
- November 2021: Paper "Parallelism versus Latency in Simplified Successive-Cancellation Decoding of Polar Codes" (joint with Ali, Arman, Alexander, John and Andrea) accepted in IEEE Transactions on Wireless Communications. This work was presented at the 2021 IEEE International Symposium on Information Theory (ISIT'21).
- November 2021: Paper "Successive Syndrome-Check Decoding of Polar Codes" (joint with Ali, John and Andrea) accepted at the 2021 Asilomar Conference on Signals, Systems, and Computers.
- July 2021: Honored to have received the 2021 Information Theory Society Paper Award jointly with Shrinivas Kudekar, Santhosh Kumar, Henry Pfister, Eren Şaşoǧlu and Rüdiger Urbanke for the paper "Reed–Muller Codes Achieve Capacity on Erasure Channels".
- July 2021: Paper "Optimal Combination of Linear and Spectral Estimators for Generalized Linear Models" (joint with Christos and Ramji) accepted in Foundations of Computational Mathematics (FoCM).
- May 2021: Paper "Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks" (joint with Quynh and Guido) accepted at the 2021 International Conference on Machine Learning (ICML'21).
- April 2021: Paper "Sparse Multi-Decoder Recursive Projection Aggregation for Reed-Muller Codes" (joint with Dorsa, Nariman and Ali) accepted at the 2021 IEEE International Symposium on Information Theory (ISIT'21). Congratulations Dorsa!
- December 2020: Paper "Global Convergence of Deep Networks with One Wide Layer Followed by Pyramidal Topology" (joint with Quynh) presented at the 2020 Conference on Neural Information Processing Systems (NeurIPS'20).
- June 2020: Paper "Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks" accepted at the 2020 International Conference on Machine Learning (ICML'20). Congratulations Alex!
- January 2020: Paper "Analysis of a Two-Layer Neural Network via Displacement Convexity" (joint with Adel and Andrea) accepted in Annals of Statistics.
- June 2019: Awarded the 2019 Lopez-Loreta Prize: 1M EUR for the 5-year research project "Foundations of Deep Learning".
- July 2018: Awarded the 2018 EPFL Doctorate Award.