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.
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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 Nicolas Flammarion, Balamurugan Palaniappan, Michael I. Jordan
7 papers
· 2015–2025
· COLT, JMLR, ICML
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Statistical Collusion by Collectives on Learning Platforms
ICML 2025
Averaging Stochastic Gradient Descent on Riemannian Manifolds
COLT 2018
Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression
JMLR 2017
Robust Discriminative Clustering with Sparse Regularizers
JMLR 2017
Stochastic Composite Least-Squares Regression with Convergence Rate $O(1/n)$
COLT 2017
Stochastic Variance Reduction Methods for Saddle-Point Problems
NeurIPS 2016
From Averaging to Acceleration, There is Only a Step-size
COLT 2015
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