Lenka Zdeborová

Some of my past presentations (most of the recent ones are videos):

  • Applied Machine Learning Days, EPFL, AI & Physics track, January 2020 Statistical physics for machine learning.

  • NeurIPS 2019 contributions, December 2019: 2 invited talks as workshop and a pannel I moderated Understanding Machine Learning via Exactly Solvable Statistical Physics Models; The spiked matrix model with generative priors; Theory Panel Discussion.

  • IPAM, UCLA, November 2019 Understanding machine learning via exactly solvable statistical physics models.

  • MIFODS - Stochastics and Statistics Seminar, MIT, November 2019 Understanding ML with statistical physics.

  • MLAI in Telecom Paris October 2019 When statistical physics meets machine learning.

  • Workshop on Science of Data Science, ICTP, Trieste, October 2019 Analysing the gradient descent-based dynamics in complex landscapes.

  • 40 years of Replica Symmetry Breaking, September 2019, Rome Analyzing performance of gradient-based algorithms.

  • CIRM, Marseille, June 2019 Algorithms in high-dimensional non-convex landscapes.

  • ICML 2019 workshop Theoretical Physics for Deep Learning, LA, June 2019 Loss landscape and behaviour of algorithms in the spiked matrix-tensor model.

  • Academie des sciences, Conference : De la physique statistique a l’intelligence artificielle, June 2019 Statistical physics modelling of machine learning (in French).

  • MATH + X Symposium, Rice University, Houston, January 2019 Computational threshold in simple models on neural networks.

  • Institut des Hautes Etudes Scientifiques (IHES) for the Itzykson seminar, 21st November 2018, Phase transitions in regression and simple neural networks.

  • A short talk to large public at the conference France is AI'18 in Paris Statistical Physics Modelling of Machine Learning.

  • Talk I gave in 50emes Journees de la Statistique 2018 in Saclay on Generalized Linear Regression: Optimal Errors and Algorithm for Random Instances..

  • A talk including historial perspective and recent advances in Statistical Mechanics of Learning a rule I gave in IPhT at the Claude Itzykson conference celebrating Cyrano DeDominicis, June 2018, Statistical Mechanics of Learning a rule.

  • Three lectures (3 times 1.5h) on Random Constraint Satisfaction and Inference I gave in ICTS in Bangalore.

  • Seminar I gave in the Simons Institute for Theory of Computing in Berkeley on Solvable Model of Unsupervised Feature Learning.

  • Seminar I gave in Big Data conference in Harvard on Clustering in Networks: Phase Transitions and optimal algorithms.

  • Seminar for rather large public on Statistical Physics of Complexity.

  • Colloquim I gave in the physics department of ENS on Clustering of networks: From phase transitions to optimal algorithms.

  • Statistical Physics of Infence: Thresholds and Algorithms; presentation of my HDR thesis in November 2015.

  • A video of a colloquim I gave in the physics department of ENS on Clustering of networks: From phase transitions to optimal algorithms in March 2015.

  • A video of a talk I gave for a rather large public on Statistical Physics of Complexity. Third Session of the Visionary & Retrospective Talks club, at the Center for Research and Interdisciplinarity, Paris, January 2015

  • Phase transitions and sample complexity in Bayes-optimal matrix factorization; talk at GDR ISIS workshop in Paris, January, 2014.

  • Clustering in networks: Phase transitions and optimal algorithms; talk given at Journee de Physique Statistique in Paris, January, 2014 and several other occasions.

  • From crystal nucleation to fast data acquisition; talk at STATPHYS 2013 in Seoul, July, 2013.

  • Non-adaptive pooling strategies for detection of rare faulty items; talk at a ICC workshop in Budapest, June, 2013.

  • Inferring the origin of epidemic with dynamic message passing; talk given at a workshop in Santa Fe, May, 2013.

  • Where the really hard problems really are?; review talk at a workshop in Tokyo, January, 2013.

  • Compressed Sensing; Seminar in ENS, Paris, November 2012.

  • Phase transitions and algorithmic barriers in inference problems; invited talk given at IPAM, UCLA, in January 2012. Includes examples of community detection and compressed sensing, physics explanation of why the spatial coupling in compressed sensing saturates the threshold.

  • Smart Grid; Introductory lecture about Smart Grid given in ENS, December 2011.

  • Random Adversarial Satisfiability Problem; invited talk in Bardonecchia, Italy, February 2011.

  • Inference of functional modules in networks; invited talk in Tokyo, Japan, November 2010.

  • Inference of parameters in particle tracking by passing messages between images; talk in Hong Kong, China, July 2010.

  • Glassy phases: A possible origin of computational hardness; invited talk on the March Meeting in Portland, March 2010.

  • Integration of renewables in redundant power grid; presented at HICSS-43, Hawaii, January 2010.

  • Random Field Ising Model; no spin glass phase in random field Ising model, RFIM at fixed magnetization, conjecture about graph partitioning. Presented at Banff, Canada, November 2009.

  • Cavity method for slow dynamics; generalization of the cavity method for adiabatic evolution of glassy Gibbs states; presented at LPT University Paris-Sud, October 2009.

  • Learning from and about complex energy landscapes; presented as a Santa Fe Institute Colloquium, September 2009.

  • Physics on random graphs; presented at Physics of Computations seminar, University of Chicago, September 2009.

  • Statistical physics of hard optimization problems; defense of my PhD thesis, June 2008 in University Paris-Sud.

  • Last Modification March, 2020