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Francis Bach - Where is Machine Learning Going?
Francis Bach
Fri Dec 11 06:31 AM -- 07:00 AM (PST) @ None
Author Information
Francis Bach (Inria)
Francis Bach is a researcher at INRIA, leading since 2011 the SIERRA project-team, which is part of the Computer Science Department at Ecole Normale Supérieure in Paris, France. After completing his Ph.D. in Computer Science at U.C. Berkeley, he spent two years at Ecole des Mines, and joined INRIA and Ecole Normale Supérieure in 2007. He is interested in statistical machine learning, and especially in convex optimization, combinatorial optimization, sparse methods, kernel-based learning, vision and signal processing. He gave numerous courses on optimization in the last few years in summer schools. He has been program co-chair for the International Conference on Machine Learning in 2015.
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2017 : Concluding remarks »
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2017 : Neil Lawrence, Francis Bach and François Laviolette »
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2017 : Sharp asymptotic and finite-sample rates of convergence of empirical measures in Wasserstein distance »
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2017 : Overture »
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2017 Workshop: (Almost) 50 shades of Bayesian Learning: PAC-Bayesian trends and insights »
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2017 Poster: On Structured Prediction Theory with Calibrated Convex Surrogate Losses »
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2017 Oral: On Structured Prediction Theory with Calibrated Convex Surrogate Losses »
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2017 Poster: Nonlinear Acceleration of Stochastic Algorithms »
Damien Scieur · Francis Bach · Alexandre d'Aspremont -
2017 Poster: Integration Methods and Optimization Algorithms »
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2016 : Francis Bach. Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression. »
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2016 : Submodular Functions: from Discrete to Continuous Domains »
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2016 Tutorial: Large-Scale Optimization: Beyond Stochastic Gradient Descent and Convexity »
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