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Francis Bach

126 papers · 2008–2026 · 14 venues · across top CS/AI venues

This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 45 separate collaboration groups - the largest holds only 15% of them. Pick the group below that matches the researcher you mean. How a shared name is split.

Achievements are not shown for a combined profile - each one describes a single researcher's record, which this is not.

Which Francis Bach?

21 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.

with Alessandro Rudi, Loucas Pillaud-Vivien, Ulysse Marteau-Ferey 18 papers · 2018–2023 · COLT, ICML, AISTATS Hide ▲
Kernelized Diffusion Maps COLT 2023 Two Losses Are Better Than One: Faster Optimization Using a Cheaper Proxy ICML 2023 Non-Convex Optimization with Certificates and Fast Rates Through Kernel Sums of Squares COLT 2022 On the Consistency of Max-Margin Losses AISTATS 2022 Sampling from Arbitrary Functions via PSD Models AISTATS 2022 A Dimension-free Computational Upper-bound for Smooth Optimal Transport Estimation COLT 2021 Disambiguation of Weak Supervision leading to Exponential Convergence rates ICML 2021 Fast Rates for Structured Prediction COLT 2021 Consistent Structured Prediction with Max-Min Margin Markov Networks ICML 2020 Statistical Estimation of the Poincaré constant and Application to Sampling Multimodal Distributions AISTATS 2020 Structured Prediction with Partial Labelling through the Infimum Loss ICML 2020 Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance COLT 2019 Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses NeurIPS 2019 Localized Structured Prediction NeurIPS 2019 Massively scalable Sinkhorn distances via the Nyström method NeurIPS 2019 Sharp Analysis of Learning with Discrete Losses AISTATS 2019 Exponential Convergence of Testing Error for Stochastic Gradient Methods COLT 2018 Statistical Optimality of Stochastic Gradient Descent on Hard Learning Problems through Multiple Passes NeurIPS 2018
24 papers whose co-authors appear nowhere else under this name
Eigenvalue Calibration for Semantic Embeddings of Large Language Models UAI 2026 Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation JMLR 2025 Efficient Optimization Algorithms for Linear Adversarial Training AISTATS 2025 Enhanced Feature Learning via Regularisation: Integrating Neural Networks and Kernel Methods JMLR 2025 Geometry-Dependent Matching Pursuit: a Transition Phase for Convergence on Linear Regression and LASSO JMLR 2025 Classifier Calibration with ROC-Regularized Isotonic Regression AISTATS 2024 Statistical and Geometrical properties of the Kernel Kullback-Leibler divergence NeurIPS 2024 The Galerkin method beats Graph-Based Approaches for Spectral Algorithms AISTATS 2024 On Bridging the Gap between Mean Field and Finite Width Deep Random Multilayer Perceptron with Batch Normalization ICML 2023 Deep Equals Shallow for ReLU Networks in Kernel Regimes ICLR 2021 A Universal Algorithm for Variational Inequalities Adaptive to Smoothness and Noise COLT 2019 Fast Decomposable Submodular Function Minimization using Constrained Total Variation NeurIPS 2019 Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron AISTATS 2019 Partially Encrypted Deep Learning using Functional Encryption NeurIPS 2019 Efficient Algorithms for Non-convex Isotonic Regression through Submodular Optimization NeurIPS 2018 Rest-Katyusha: Exploiting the Solution's Structure via Scheduled Restart Schemes NeurIPS 2018 A Quantitative Measure of the Impact of Coarticulation on Phone Discriminability Interspeech 2017 Breaking the Curse of Dimensionality with Convex Neural Networks JMLR 2017 On the Equivalence between Kernel Quadrature Rules and Random Feature Expansions JMLR 2017 Highly-Smooth Zero-th Order Online Optimization COLT 2016 Parameter Learning for Log-supermodular Distributions NeurIPS 2016 Adaptivity of Averaged Stochastic Gradient Descent to Local Strong Convexity for Logistic Regression JMLR 2014 Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n) NeurIPS 2013 Sharp analysis of low-rank kernel matrix approximations COLT 2013

Venues · all papers under this name

NeurIPS (33) AISTATS (26) JMLR (22) ICML (18) COLT (16) CVPR (2) ICLR (2) COLING (1) CoNLL (1) EMNLP (1) ICCV (1) IJCAI (1) Interspeech (1) UAI (1)