Lenka Zdeborová
Orcid: 0000-0002-8377-3978
According to our database1,
Lenka Zdeborová
authored at least 177 papers
between 2006 and 2024.
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Bibliography
2024
Trans. Mach. Learn. Res., 2024
SIAM J. Math. Data Sci., 2024
Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-dimensional Tokens.
CoRR, 2024
Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants.
CoRR, 2024
CoRR, 2024
Bayes-optimal learning of an extensive-width neural network from quadratically many samples.
CoRR, 2024
Understanding Counting in Small Transformers: The Interplay between Attention and Feed-Forward Layers.
CoRR, 2024
Optimal thresholds and algorithms for a model of multi-modal learning in high dimensions.
CoRR, 2024
CoRR, 2024
CoRR, 2024
CoRR, 2024
A phase transition between positional and semantic learning in a solvable model of dot-product attention.
CoRR, 2024
CoRR, 2024
The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024
2023
Mach. Learn. Sci. Technol., September, 2023
Mach. Learn. Sci. Technol., March, 2023
Bayesian reconstruction of memories stored in neural networks from their connectivity.
PLoS Comput. Biol., January, 2023
J. Mach. Learn. Res., 2023
Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective.
CoRR, 2023
Compressed sensing with l0-norm: statistical physics analysis and algorithms for signal recovery.
CoRR, 2023
Proceedings of the Uncertainty in Artificial Intelligence, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Compressed sensing with ℓ0-norm: statistical physics analysis & algorithms for signal recovery.
Proceedings of the IEEE Information Theory Workshop, 2023
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
Mach. Learn. Sci. Technol., 2022
CoRR, 2022
CoRR, 2022
Theoretical characterization of uncertainty in high-dimensional linear classification.
CoRR, 2022
CoRR, 2022
Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Mathematical and Scientific Machine Learning, 2022
2021
Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem.
Mach. Learn. Sci. Technol., September, 2021
Mach. Learn. Sci. Technol., 2021
CoRR, 2021
Perturbative construction of mean-field equations in extensive-rank matrix factorization and denoising.
CoRR, 2021
Learning Gaussian Mixtures with Generalised Linear Models: Precise Asymptotics in High-dimensions.
CoRR, 2021
Capturing the learning curves of generic features maps for realistic data sets with a teacher-student model.
CoRR, 2021
Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Learning curves of generic features maps for realistic datasets with a teacher-student model.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Mathematical and Scientific Machine Learning, 2021
Proceedings of the Mathematical and Scientific Machine Learning, 2021
The Gaussian equivalence of generative models for learning with shallow neural networks.
Proceedings of the Mathematical and Scientific Machine Learning, 2021
Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed.
Proceedings of the 38th International Conference on Machine Learning, 2021
2020
Multilayer Modularity Belief Propagation to Assess Detectability of Community Structure.
SIAM J. Math. Data Sci., 2020
The Gaussian equivalence of generative models for learning with two-layer neural networks.
CoRR, 2020
The role of regularization in classification of high-dimensional noisy Gaussian mixture.
CoRR, 2020
Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Exact asymptotics for phase retrieval and compressed sensing with random generative priors.
Proceedings of Mathematical and Scientific Machine Learning, 2020
Rademacher complexity and spin glasses: A link between the replica and statistical theories of learning.
Proceedings of Mathematical and Scientific Machine Learning, 2020
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020
The Role of Regularization in Classification of High-dimensional Noisy Gaussian Mixture.
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
2019
IEEE Trans. Inf. Theory, 2019
SIAM J. Math. Data Sci., 2019
CoRR, 2019
Modularity belief propagation on multilayer networks to detect significant community structure.
CoRR, 2019
Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model.
CoRR, 2019
On the Universality of Noiseless Linear Estimation with Respect to the Measurement Matrix.
CoRR, 2019
Passed & Spurious: analysing descent algorithms and local minima in spiked matrix-tensor model.
CoRR, 2019
CoRR, 2019
Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models.
Proceedings of the 36th International Conference on Machine Learning, 2019
Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019
2018
CoRR, 2018
Rank-one matrix estimation: analysis of algorithmic and information theoretic limits by the spatial coupling method.
CoRR, 2018
CoRR, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
The committee machine: Computational to statistical gaps in learning a two-layers neural network.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Conference On Learning Theory, 2018
2017
Phase Transitions, Optimal Errors and Optimality of Message-Passing in Generalized Linear Models.
CoRR, 2017
Constrained Low-rank Matrix Estimation: Phase Transitions, Approximate Message Passing and Applications.
CoRR, 2017
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, 2017
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017
Streaming Bayesian inference: Theoretical limits and mini-batch approximate message-passing.
Proceedings of the 55th Annual Allerton Conference on Communication, 2017
2016
IEEE Trans. Inf. Theory, 2016
The large deviations of the whitening process in random constraint satisfaction problems.
CoRR, 2016
Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Proceedings of the 2016 IEEE Information Theory Workshop, 2016
Proceedings of the IEEE International Symposium on Information Theory, 2016
Phase transitions and optimal algorithms in high-dimensional Gaussian mixture clustering.
Proceedings of the 54th Annual Allerton Conference on Communication, 2016
2015
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Proceedings of the IEEE International Symposium on Information Theory, 2015
Proceedings of the IEEE International Symposium on Information Theory, 2015
Proceedings of the 32nd International Conference on Machine Learning, 2015
Adaptive damping and mean removal for the generalized approximate message passing algorithm.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015
MMSE of probabilistic low-rank matrix estimation: Universality with respect to the output channel.
Proceedings of the 53rd Annual Allerton Conference on Communication, 2015
Proceedings of the 53rd Annual Allerton Conference on Communication, 2015
2014
J. Satisf. Boolean Model. Comput., 2014
CoRR, 2014
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014
2013
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013
Robust error correction for real-valued signals via message-passing decoding and spatial coupling.
Proceedings of the 2013 IEEE Information Theory Workshop, 2013
Phase diagram and approximate message passing for blind calibration and dictionary learning.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013
Proceedings of the IEEE International Conference on Communications, 2013
Compressed sensing under matrix uncertainty: Optimum thresholds and robust approximate message passing.
Proceedings of the IEEE International Conference on Acoustics, 2013
2012
CoRR, 2012
Probabilistic Reconstruction in Compressed Sensing: Algorithms, Phase Diagrams, and Threshold Achieving Matrices
CoRR, 2012
Proceedings of the Twenty-Third Annual ACM-SIAM Symposium on Discrete Algorithms, 2012
Compressed sensing of approximately-sparse signals: Phase transitions and optimal reconstruction.
Proceedings of the 50th Annual Allerton Conference on Communication, 2012
2011
SIAM J. Discret. Math., 2011
Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications
CoRR, 2011
2010
Message Passing for Integrating and Assessing Renewable Generation in a Redundant Power Grid.
Proceedings of the 43rd Hawaii International International Conference on Systems Science (HICSS-43 2010), 2010
2009
CoRR, 2009
Message Passing for Optimization and Control of Power Grid: Toy Model of Distribution with Ancillary Lines
CoRR, 2009
2008
2007
Proc. Natl. Acad. Sci. USA, 2007
Phase Transitions and Computational Difficulty in Random Constraint Satisfaction Problems
CoRR, 2007
2006