Science and Computational Optics. Phase transition in the detection of modules in sparse networks. Send me a mail! Semantic Scholar profile for undefined, with 3 scientific research papers. An instance of a random constraint satisfaction problem defines a random subset (the set of solutions) of a large product space XN. E, Statistical, nonlinear, and…. Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula. Physics, Machine Learning, Statistics, Signal Processing, Computer Semantic Scholar profile for undefined, with 3 scientific research papers. By clicking accept or continuing to use the site, you agree to the terms outlined in our. Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications, Physical review. valuation dun dossier Smur informatis laide dun stylo numrique, 高次元Gauss混合クラスタリングにおける相転移と最適アルゴリズム【Powered by NICT】, By clicking accept or continuing to use the site, you agree to the terms outlined in our. ... Google Scholar ID. Learning and Physics” laboratory, ML & AI pour la physique et les physiciens, Statistical Physics For Optimization and Learning, Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation, Kernel Computations from Large-Scale Random Features Obtained by Optical Processing Units, Marvels and Pitfalls of the Langevin Algorithm in Noisy High-Dimensional Inference, On the universality of noiseless linear estimation with respect to the measurement matrix, Detection limits in the spiked Wigner model, Full Professor, Physics and EE, EPFL, Switzerland, Since 2020, Professor UPMC and Researcher at Ecole Normale Superieure, Paris, 2013-2020, Member of the Institut Universitaire de France, 2015-2020, Holder of a Prairie Institute AI Chair, 2019-2020, Member and Fellow of the ELLIS society, Since 2019, Holder of the chair CFM-ENS on datascience, 2016-2020, Visiting Professor @ Duke University, Maths Dept., 2018, Visiting Scientist @ Simons Institute in Berkeley, 2016, Visiting Scientist @ Los Alamos National Labs, 2008, Maitre de Conference (Associate Professor) in ESPCI Paristech, 2004 - 2013. Florent Krzakala is a full professor at École polytechnique fédérale departments in EPFL. ... Florent Krzakala. Semantic Scholar is a free, AI-powered research tool for scientific literature, based at the Allen Institute for AI. We consider tensor factorizations using a generative model and a Bayesian approach. Author pages are created from data sourced from our academic publisher partnerships and public sources. You are currently offline. Full Professor, Information, Learning & Physics Laboratory (SB/STI) EPFL SB IPHYS IDEPHICS2 Author pages are created from data sourced from our academic publisher partnerships and public sources. We present an asymptotically exact analysis of the problem of detecting communities in sparse random networks generated by stochastic block models, including both assortative and disassortative functional modules. Semantic Scholar profile for Florent Krzakala, with 339 highly influential citations and 195 scientific research papers. He leads the IdePHIcs “Information, I am curently looking for Ph.D students and postdocs. In Proceedings of the 31st Conference on Learning Theory (COLT) 75 410–438. École polytechnique fédérale de Lausanne. Spectral Clustering of graphs with the Bethe Hessian. We show how to rigorously prove the conjectured formula for the symmetric rank-one case. Their combined citations are counted only for the first article. Click here for the youtube channel, or browse with the arrows, KITP Conference: At the Crossroad of Physics and Machine Learning, NeurIPS2019 workshop: Science meets Engineering of Deep Learning, KITP Conference: The Rough High-Dimensional Landscape Problem, A lecture at the 2018 Beg Rohu school on Deep Learning, Disordered serendipity: a glassy path to discovery; A workshop in honour of Giorgio Parisi’s 70th birthday, Talk given at the Flatiron institute in Newyork, April 30, 2019, Lecture given in the international master Physics of Complex Systems on computational science, An introductory pratical course by Florent Krzakala and Antoine Baker, Ecole Doctorale EDPIF 2019, Cours Master 1, Université Paris Sorbonne 2019-2010, Lecture Master 2, Ecole Normale Superieure 2020-2021, ICFP, A set of Lectures given at Duke in 2018 by Lenka Zdeborova and Florent Krzakala. Our interdisplinary research group embodies physicists, mathematicians, and computer scientists working together to solve problems ranging from statistics to signal processing and machine learning. Spectral clustering is a standard approach to label nodes on a graph by studying the (largest or lowest) eigenvalues of a symmetric real matrix such as e.g. You are currently offline. Krzakala Florent Researcher unique identifiers: Arxiv ,Google scholar, ORCID Date of birth: 22/03/1976 Nationality: French Web site: krzakala.org •EDUCATION 2011 Habilitation, Université Paris 6 UPMC 2002 PhD thesis in theoretic physics, Université Paris 11 … Some features of the site may not work correctly. Semantic Scholar is a free, AI-powered research tool for scientific literature, based at the Allen Institute for AI. The following articles are merged in Scholar. Detection limits in the high-dimensional spiked rectangular model. Stefano Sarao Mannelli, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová: Passed & Spurious: analysing descent algorithms and local minima in spiked … Full Professor, Information, Learning & Physics Laboratory (STI/SB) +41 21 693 31 87 Office: ELD 239 EPFL > STI > IEL > IDEPHICS1. High-dimensional generalized linear models are basic building blocks of current data analysis tools including multilayers neural networks. Florent Krzakala is a full professor at École polytechnique fédérale de Lausanne in Switzerland. the startup Lighton. We extend our previous work on the stochastic block model, a commonly used generative model for social and biological networks, and the problem of inferring functional groups or communities from the topology of the network. Statistical and computational phase transitions in spiked tensor estimation, IEEE International Symposium on Information…. He is also the founder and scientific advisor of Feel free to check the group github repo. the adjacency or the Laplacian. We propose a way of encoding sparse data using a “nonbacktracking” matrix and show that the corresponding spectral algorithm performs optimally for some popular generative models, including the stochastic block model. Some features of the site may not work correctly. His research interests include Statistical The SPHINX team acknowledge funding from: EPFL, IdePHICS lab, ELD 239, Station 11 CH-1015 Lausanne, IdePHIcs “Information, Approximate Message-Passing Decoder and Capacity Achieving Sparse Superposition Codes. Gibbs states and the set of solutions of random constraint satisfaction problems. We design a new procedure which is able to reconstruct exactly the signal with a number of measurements that approaches the theoretical limit in the limit of large systems. Krzakala Florent Researcher unique identifiers: Arxiv, Google scholar, ORCID Date of birth: 22/03/1976 Nationality: French Web site: krzakala.org • EDUCATION 2011 Habilitation, Université Paris 6 UPMC 2002 PhD thesis in theoretic physics, Université Paris 11 … Meet the team working in the Sphinx Group. ... Krzakala Florent, Moore Cris, Zdeborova Lenka; 2016; Cite Save Feed. We study the approximate message-passing decoder for sparse superposition coding on the additive white Gaussian noise channel and extend our preliminary work. They arise in signal processing, statistical inference, machine learning, communication theory, and other fields. Compressed sensing is a signal processing method that acquires data directly in a compressed form. ; El Alaoui, A. and Krzakala, F. (2018). Probabilistic Reconstruction in Compressed Sensing: Algorithms, Phase Diagrams, and Threshold Achieving Matrices. Spectral redemption in clustering sparse networks, Proceedings of the National Academy of Sciences. (2018). Learning and Physics” laboratory in the Physics and Engineering Statistical physics-based reconstruction in compressed sensing. Edit profile. His research interests include Statistical Physics, Machine Learning, Statistics, Signal Processing, Computer Science and Computational Optics. de Lausanne in Switzerland. El Alaoui, A. and Jordan, M. I. Florent Krzakala.
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