Francis Bach

33 catalog papers. Identity-linked publications and additional name matches are distinguished below.

ORCID: 0000-0001-8644-1058

Publications

• On the Effectiveness of the z-Transform Method in Quadratic Optimization — Journal of Machine Learning Research 2026 (name-matched, not ORCID-linked)
• High-Dimensional Analysis of Gradient Flow for Extensive-Width Quadratic Neural Networks — Journal of Machine Learning Research 2026 (name-matched, not ORCID-linked)
• Enhanced Feature Learning via Regularisation: Integrating Neural Networks and Kernel Methods — Journal of Machine Learning Research 2025 (name-matched, not ORCID-linked)
• Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation — Journal of Machine Learning Research 2025 (name-matched, not ORCID-linked)
• Physics-informed Kernel Learning — Journal of Machine Learning Research 2025 (name-matched, not ORCID-linked)
• Bridging the gap between constant step size stochastic gradient descent and Markov chains — The Annals of Statistics 2020
• Optimal Convergence Rates for Convex Distributed Optimization in Networks — Journal of Machine Learning Research 2019 (name-matched, not ORCID-linked)
• Robust Discriminative Clustering with Sparse Regularizers — Journal of Machine Learning Research 2017 (name-matched, not ORCID-linked)
• Breaking the Curse of Dimensionality with Convex Neural Networks — Journal of Machine Learning Research 2017 (name-matched, not ORCID-linked)
• Active-set Methods for Submodular Minimization Problems — Journal of Machine Learning Research 2017 (name-matched, not ORCID-linked)
• On the Equivalence between Kernel Quadrature Rules and Random Feature Expansions — Journal of Machine Learning Research 2017 (name-matched, not ORCID-linked)
• On the Consistency of Ordinal Regression Methods — Journal of Machine Learning Research 2017 (name-matched, not ORCID-linked)
• Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression — Journal of Machine Learning Research 2017 (name-matched, not ORCID-linked)
• Online but Accurate Inference for Latent Variable Models with Local Gibbs Sampling — Journal of Machine Learning Research 2017 (name-matched, not ORCID-linked)
• Nonparametric stochastic approximation with large step-sizes — The Annals of Statistics 2016 (name-matched, not ORCID-linked)
• Adaptivity of Averaged Stochastic Gradient Descent to Local Strong Convexity for Logistic Regression — Journal of Machine Learning Research 2014 (name-matched, not ORCID-linked)
• Multi-task Regression using Minimal Penalties — Journal of Machine Learning Research 2012 (name-matched, not ORCID-linked)
• Proximal Methods for Hierarchical Sparse Coding — Journal of Machine Learning Research 2011 (name-matched, not ORCID-linked)
• Convex and Network Flow Optimization for Structured Sparsity — Journal of Machine Learning Research 2011 (name-matched, not ORCID-linked)
• Structured Variable Selection with Sparsity-Inducing Norms — Journal of Machine Learning Research 2011 (name-matched, not ORCID-linked)
• Online Learning for Matrix Factorization and Sparse Coding — Journal of Machine Learning Research 2010 (name-matched, not ORCID-linked)
• A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization — Journal of Machine Learning Research 2009 (name-matched, not ORCID-linked)
• Kernel dimension reduction in regression — The Annals of Statistics 2009
• Optimal Solutions for Sparse Principal Component Analysis — Journal of Machine Learning Research 2008 (name-matched, not ORCID-linked)
• Consistency of Trace Norm Minimization — Journal of Machine Learning Research 2008 (name-matched, not ORCID-linked)
• Consistency of the Group Lasso and Multiple Kernel Learning — Journal of Machine Learning Research 2008 (name-matched, not ORCID-linked)
• SimpleMKL — Journal of Machine Learning Research 2008 (name-matched, not ORCID-linked)
• Statistical Consistency of Kernel Canonical Correlation Analysis — Journal of Machine Learning Research 2007 (name-matched, not ORCID-linked)
• Considering Cost Asymmetry in Learning Classifiers — Journal of Machine Learning Research 2006 (name-matched, not ORCID-linked)
• Learning Spectral Clustering, With Application To Speech Separation — Journal of Machine Learning Research 2006 (name-matched, not ORCID-linked)
• Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces — Journal of Machine Learning Research 2004 (name-matched, not ORCID-linked)
• Beyond Independent Components: Trees and Clusters — Journal of Machine Learning Research 2003 (name-matched, not ORCID-linked)
• Kernel Independent Component Analysis — Journal of Machine Learning Research 2002 (name-matched, not ORCID-linked)