Marc Mézard - researchr alias

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Viewing Publication 1 - 19 from 19

2021

The Gaussian equivalence of generative models for learning with shallow neural networksSebastian Goldt, Bruno Loureiro, Galen Reeves, Florent Krzakala, Marc Mézard, Lenka Zdeborová. msml 2021: 426-471 [doi]

Learning curves of generic features maps for realistic datasets with a teacher-student modelBruno Loureiro, Cédric Gerbelot, Hugo Cui, Sebastian Goldt, Florent Krzakala, Marc Mézard, Lenka Zdeborová. nips 2021: 18137-18151 [doi]

2020

Generalisation error in learning with random features and the hidden manifold modelFederica Gerace, Bruno Loureiro, Florent Krzakala, Marc Mézard, Lenka Zdeborová. icml 2020: 3452-3462 [doi]

2017

Multi-layer generalized linear estimationAndre Manoel, Florent Krzakala, Marc Mézard, Lenka Zdeborová. isit 2017: 2098-2102 [doi]

2016

Phase Transitions and Sample Complexity in Bayes-Optimal Matrix FactorizationYoshiyuki Kabashima, Florent Krzakala, Marc Mézard, Ayaka Sakata, Lenka Zdeborová. TIT, 62(7):4228-4265, 2016. [doi]

2014

Reweighted Belief Propagation and Quiet Planting for Random K-SATFlorent Krzakala, Marc Mézard, Lenka Zdeborová. jsat, 8(3/4):149-171, 2014. [doi]

2013

Phase diagram and approximate message passing for blind calibration and dictionary learningFlorent Krzakala, Marc Mézard, Lenka Zdeborová. isit 2013: 659-663 [doi]

Compressed sensing under matrix uncertainty: Optimum thresholds and robust approximate message passingFlorent Krzakala, Marc Mézard, Lenka Zdeborová. icassp 2013: 5519-5523 [doi]

Non-adaptive pooling strategies for detection of rare faulty itemsPan Zhang, Florent Krzakala, Marc Mézard, Lenka Zdeborová. icc 2013: 1409-1414 [doi]

2012

Compressed sensing of approximately-sparse signals: Phase transitions and optimal reconstructionJean Barbier, Florent Krzakala, Marc Mézard, Lenka Zdeborová. allerton 2012: 800-807 [doi]

2011

Group Testing With Random Pools: Optimal Two-Stage AlgorithmsMarc Mézard, Cristina Toninelli. TIT, 57(3):1736-1745, 2011. [doi]

Special Section on Constraint Satisfaction Problems and Message Passing AlgorithmsMarc Mézard, Prasad Tetali. siamdm, 25(2):733-735, 2011. [doi]

2008

Pairs of SAT-assignments in random Boolean formulæHervé Daudé, Marc Mézard, Thierry Mora, Riccardo Zecchina. TCS, 393(1-3):260-279, 2008. [doi]

2006

Constraint Satisfaction by Survey PropagationAlfredo Braunstein, Marc Mézard, Martin Weigt, Riccardo Zecchina. In Allon G. Percus, Gabriel Istrate, Cristopher Moore, editors, Computational Complexity and Statistical Physics. Studies in the sciences of complexity, pages 107-124, Oxford University Press, 2006.

Threshold values of random ::::K::::-SAT from the cavity methodStephan Mertens, Marc Mézard, Riccardo Zecchina. rsa, 28(3):340-373, 2006. [doi]

2005

Survey propagation: An algorithm for satisfiabilityAlfredo Braunstein, Marc Mézard, Riccardo Zecchina. rsa, 27(2):201-226, 2005. [doi]

1992

On The Mean Field Theory of Random HeteropolymersSilvio Franz, Marc Mézard, Giorgio Parisi. IJNS, 3(Supplement):195-200, 1992. [doi]

1989

Learning algorithms in neural networks: recent resultsMarc Mézard. nato 1990: 75-79 [doi]

1988

Basins of Attraction in a Perception-like Neural NetworkWerner Krauth, Marc Mézard, Jean-Pierre Nadal. compsys, 2(4), 1988. [doi]

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