Florent Krzakala
Orcid: 0000-0003-2313-2578
According to our database1,
Florent Krzakala
authored at least 170 papers
between 2004 and 2024.
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Bibliography
2024
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
The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents.
CoRR, 2024
2023
IEEE Trans. Inf. Theory, December, 2023
Mach. Learn. Sci. Technol., September, 2023
Asymptotic Errors for Teacher-Student Convex Generalized Linear Models (Or: How to Prove Kabashima's Replica Formula).
IEEE Trans. Inf. Theory, March, 2023
Bayesian reconstruction of memories stored in neural networks from their connectivity.
PLoS Comput. Biol., January, 2023
J. Mach. Learn. Res., 2023
CoRR, 2023
Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective.
CoRR, 2023
Asymptotic Characterisation of Robust Empirical Risk Minimisation Performance in the Presence of Outliers.
CoRR, 2023
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
Are Gaussian Data All You Need? The Extents and Limits of Universality in High-Dimensional Generalized Linear Estimation.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
CoRR, 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
Proceedings of the IEEE International Symposium on Information Theory, 2022
Fluctuations, Bias, Variance & Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the IEEE International Conference on Acoustics, 2022
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
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
LightOn Optical Processing Unit : Scaling-up AI and HPC with a Non von Neumann co-processor.
Proceedings of the IEEE Hot Chips 33 Symposium, 2021
2020
Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation.
IEEE Trans. Inf. Theory, 2020
Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignment.
CoRR, 2020
The Gaussian equivalence of generative models for learning with two-layer neural networks.
CoRR, 2020
Light-in-the-loop: using a photonics co-processor for scalable training of neural networks.
CoRR, 2020
The role of regularization in classification of high-dimensional noisy Gaussian mixture.
CoRR, 2020
Large-Scale Optical Reservoir Computing for Spatiotemporal Chaotic Systems Prediction.
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
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
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 37th International Conference on Machine Learning, 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
Kernel Computations from Large-Scale Random Features Obtained by Optical Processing Units.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
Asymptotic Errors for High-Dimensional Convex Penalized Linear Regression beyond Gaussian Matrices.
Proceedings of the Conference on Learning Theory, 2020
2019
IEEE Trans. Inf. Theory, 2019
SIAM J. Math. Data Sci., 2019
CoRR, 2019
Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model.
CoRR, 2019
Optical Reservoir Computing using multiple light scattering for chaotic systems prediction.
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
Spectral Method for Multiplexed Phase Retrieval and Application in Optical Imaging in Complex Media.
Proceedings of the IEEE International Conference on Acoustics, 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 2018 IEEE Statistical Signal Processing Workshop, 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 2018 IEEE International Symposium on Information Theory, 2018
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018
Proceedings of the Conference On Learning Theory, 2018
2017
IEEE Trans. Signal Process., 2017
Approximate Message-Passing Decoder and Capacity Achieving Sparse Superposition Codes.
IEEE Trans. Inf. Theory, 2017
Robust Phase Retrieval with the Swept Approximate Message Passing (prSAMP) Algorithm.
Image Process. Line, 2017
Finite Size Corrections and Likelihood Ratio Fluctuations in the Spiked Wigner Model.
CoRR, 2017
Phase Transitions, Optimal Errors and Optimality of Message-Passing in Generalized Linear Models.
CoRR, 2017
A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines.
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
IEEE Signal Process. Lett., 2016
Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16).
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
Inferring sparsity: Compressed sensing using generalized restricted Boltzmann machines.
Proceedings of the 2016 IEEE Information Theory Workshop, 2016
Proceedings of the 2016 IEEE Information Theory Workshop, 2016
Proceedings of the IEEE International Symposium on Information Theory, 2016
Random projections through multiple optical scattering: Approximating Kernels at the speed of light.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016
Intensity-only optical compressive imaging using a multiply scattering material and a double phase retrieval approach.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016
Phase transitions and optimal algorithms in high-dimensional Gaussian mixture clustering.
Proceedings of the 54th Annual Allerton Conference on Communication, 2016
Proceedings of the 54th Annual Allerton Conference on Communication, 2016
2015
Intensity-only optical compressive imaging using a multiply scattering material : a double phase retrieval system.
CoRR, 2015
CoRR, 2015
CoRR, 2015
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 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
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
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
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014
2013
Compressed sensing and Approximate Message Passing with spatially-coupled Fourier and Hadamard matrices.
CoRR, 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
The Quantum Adiabatic Algorithm applied to random optimization problems: the quantum spin glass perspective
CoRR, 2012
CoRR, 2012
Probabilistic Reconstruction in Compressed Sensing: Algorithms, Phase Diagrams, and Threshold Achieving Matrices
CoRR, 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
2009
First-order transitions and the performance of quantum algorithms in random optimization problems.
CoRR, 2009
2007
Proc. Natl. Acad. Sci. USA, 2007
Phase Transitions and Computational Difficulty in Random Constraint Satisfaction Problems
CoRR, 2007
2004
Threshold values, stability analysis and high-q asymptotics for the coloring problem on random graphs
CoRR, 2004