Joseph Salmon
27 papers · 2011–2025 · 7 venues · across top CS/AI venues
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Achievements
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(14)
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Keyword Champion
(4)
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Renaissance Researcher
(5)
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Conference Pioneer
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Trend Setter
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Research topics
Machine Learning
(27)
Optimization & Theory
(23)
Core Methods
(20)
Mathematics & Optimization
(10)
Optimization
(8)
Learning Types
(4)
Deep Learning
(3)
Mathematics
(3)
Security & Privacy
(2)
Application Areas
(2)
Bayesian & Probabilistic
(2)
Differential Privacy
(2)
Techniques
(2)
Computer Science
(1)
Data Science & Analytics
(1)
Keywords
coordinate descent
(8)
screening rule
(7)
sparse regression
(4)
proximal gradient descent
(3)
hyperparameter optimization
(3)
multi-task learning
(3)
convex optimization
(3)
lasso regression
(3)
generalized linear model
(3)
sparse optimization
(3)
sparse regularization
(3)
duality gap
(3)
high-dimensional optimization
(2)
proximal gradient
(2)
feature selection
(2)
nuclear norm regularization
(2)
logistic regression
(2)
differential privacy
(2)
group sparsity
(2)
non-convex optimization
(2)
Papers
A Two-Head Loss Function for Deep Average-K Classification
WACV 2025
High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent
AISTATS 2023
Benchopt: Reproducible, efficient and collaborative optimization benchmarks
NeurIPS 2022
Convergent Working Set Algorithm for Lasso with Non-Convex Sparse Regularizers
AISTATS 2022
Differentially Private Coordinate Descent for Composite Empirical Risk Minimization
ICML 2022
Implicit Differentiation for Fast Hyperparameter Selection in Non-Smooth Convex Learning
JMLR 2022
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso
AutoML 2022
Stochastic smoothing of the top-K calibrated hinge loss for deep imbalanced classification
ICML 2022
Dual Extrapolation for Sparse GLMs
JMLR 2020
Implicit differentiation of Lasso-type models for hyperparameter optimization
ICML 2020
Statistical control for spatio-temporal MEG/EEG source imaging with desparsified mutli-task Lasso
NeurIPS 2020
Support recovery and sup-norm convergence rates for sparse pivotal estimation
AISTATS 2020
Handling correlated and repeated measurements with the smoothed multivariate square-root Lasso
NeurIPS 2019
Optimal Mini-Batch and Step Sizes for SAGA
ICML 2019
Safe Grid Search with Optimal Complexity
ICML 2019
Screening rules for Lasso with non-convex Sparse Regularizers
ICML 2019
Celer: a Fast Solver for the Lasso with Dual Extrapolation
ICML 2018
Generalized Concomitant Multi-Task Lasso for Sparse Multimodal Regression
AISTATS 2018
Gap Safe Screening Rules for Sparsity Enforcing Penalties
JMLR 2017
GAP Safe Screening Rules for Sparse-Group Lasso
NeurIPS 2016
Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions
ICML 2016
Extending Gossip Algorithms to Distributed Estimation of U-statistics
NeurIPS 2015
GAP Safe screening rules for sparse multi-task and multi-class models
NeurIPS 2015
Mind the duality gap: safer rules for the Lasso
ICML 2015
Probabilistic low-rank matrix completion on finite alphabets
NeurIPS 2014
Learning Heteroscedastic Models by Convex Programming under Group Sparsity
ICML 2013
Optimal aggregation of affine estimators
COLT 2011