Lenka Zdeborová

Rigorous Asymptotics for First-Order Algorithms Through the Dynamical Cavity Method COLT 2026 Building Conformal Prediction Intervals with Approximate Message Passing UAI 2025 Counting in Small Transformers: The Delicate Interplay between Attention and Feed-Forward Layers ICML 2025 Fundamental computational limits of weak learnability in high-dimensional multi-index models AISTATS 2025 Fundamental limits of learning in sequence multi-index models and deep attention networks: high-dimensional asymptotics and sharp thresholds ICML 2025 Fundamental Limits of Matrix Sensing: Exact Asymptotics, Universality, and Applications COLT 2025 Analysis of Bootstrap and Subsampling in High-dimensional Regularized Regression UAI 2024 Analysis of Learning a Flow-based Generative Model from Limited Sample Complexity ICLR 2024 A Phase Transition between Positional and Semantic Learning in a Solvable Model of Dot-Product Attention NeurIPS 2024 Asymptotics of feature learning in two-layer networks after one gradient-step ICML 2024 Bayes-optimal learning of an extensive-width neural network from quadratically many samples NeurIPS 2024 Fundamental Limits of Non-Linear Low-Rank Matrix Estimation COLT 2024 The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents ICML 2024 Bayes-optimal Learning of Deep Random Networks of Extensive-width ICML 2023 Expectation consistency for calibration of neural networks UAI 2023 High-dimensional Asymptotics of Denoising Autoencoders NeurIPS 2023 On double-descent in uncertainty quantification in overparametrized models AISTATS 2023 Tree-AMP: Compositional Inference with Tree Approximate Message Passing JMLR 2023 Universality laws for Gaussian mixtures in generalized linear models NeurIPS 2023 Multi-layer State Evolution Under Random Convolutional Design NeurIPS 2022 Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks NeurIPS 2022 Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap NeurIPS 2022 Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed ICML 2021 Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime NeurIPS 2021 Learning curves of generic features maps for realistic datasets with a teacher-student model NeurIPS 2021 Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions NeurIPS 2021 Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval NeurIPS 2020 Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification NeurIPS 2020 Generalisation error in learning with random features and the hidden manifold model ICML 2020 Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization NeurIPS 2020 Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions NeurIPS 2020 Phase retrieval in high dimensions: Statistical and computational phase transitions NeurIPS 2020 The Role of Regularization in Classification of High-dimensional Noisy Gaussian Mixture ICML 2020 Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup NeurIPS 2019 Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models ICML 2019 The spiked matrix model with generative priors NeurIPS 2019 Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models NeurIPS 2019 Entropy and mutual information in models of deep neural networks NeurIPS 2018 Optimal Errors and Phase Transitions in High-Dimensional Generalized Linear Models COLT 2018 The committee machine: Computational to statistical gaps in learning a two-layers neural network NeurIPS 2018 Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula NeurIPS 2016 Matrix Completion from Fewer Entries: Spectral Detectability and Rank Estimation NeurIPS 2015 Swept Approximate Message Passing for Sparse Estimation ICML 2015 Spectral Clustering of graphs with the Bethe Hessian NeurIPS 2014 Blind Calibration in Compressed Sensing using Message Passing Algorithms NeurIPS 2013