Rémi Bardenet

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 32

Top Topics

Point Processes

Top Venues

J. Mach. Learn. Res.

Publications

Martin Rouault, Rémi Bardenet, Mylène Maïda
Monte Carlo with kernel-based Gibbs measures: Guarantees for probabilistic herding. CoRR (2024)
Michaël Fanuel, Rémi Bardenet
On the Number of Steps of CyclePopping in Weakly Inconsistent U(1)-Connection Graphs. CoRR (2024)
Barbara Pascal, Rémi Bardenet
Point Processes and spatial statistics in time-frequency analysis. CoRR (2024)
Thibaut Lemoine, Rémi Bardenet
Monte Carlo methods on compact complex manifolds using Bergman kernels. CoRR (2024)
Juan Manuel Miramont, Rémi Bardenet, Pierre Chainais, François Auger
Benchmarking multi-component signal processing methods in the time-frequency plane. CoRR (2024)
Hugo Jaquard, Michaël Fanuel, Pierre-Olivier Amblard, Rémi Bardenet, Simon Barthelmé, Nicolas Tremblay
Smoothing Complex-Valued Signals on Graphs with Monte-Carlo. ICASSP (2023)
Diala Hawat, Guillaume Gautier, Rémi Bardenet, Raphaël Lachièze-Rey
On estimating the structure factor of a point process, with applications to hyperuniformity. Stat. Comput. 33 (3) (2023)
Rémi Bardenet, Michaël Fanuel, Alexandre Feller
On sampling determinantal and Pfaffian point processes on a quantum computer. CoRR (2023)
Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
Signal reconstruction using determinantal sampling. CoRR (2023)
Arnaud Poinas, Rémi Bardenet
On proportional volume sampling for experimental design in general spaces. Stat. Comput. 33 (1) (2023)
Barbara Pascal, Rémi Bardenet
A Covariant, Discrete Time-Frequency Representation Tailored for Zero-Based Signal Detection. IEEE Trans. Signal Process. 70 (2022)
Michaël Fanuel, Rémi Bardenet
Sparsification of the regularized magnetic Laplacian with multi-type spanning forests. CoRR (2022)
Michaël Fanuel, Rémi Bardenet
Nonparametric estimation of continuous DPPs with kernel methods. CoRR (2021)
Michaël Fanuel, Rémi Bardenet
Nonparametric estimation of continuous DPPs with kernel methods. NeurIPS (2021)
Guillaume Gautier, Rémi Bardenet, Michal Valko
Fast sampling from β-ensembles. Stat. Comput. 31 (1) (2021)
Rémi Bardenet, Subhro Ghosh, Meixia Lin
Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGD. CoRR (2021)
Rémi Bardenet, Subhroshekhar Ghosh, Meixia Lin
Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGD. NeurIPS (2021)
Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
Kernel interpolation with continuous volume sampling. ICML (2020)
Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
Kernel interpolation with continuous volume sampling. CoRR (2020)
Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
A determinantal point process for column subset selection. J. Mach. Learn. Res. 21 (2020)
Rémi Bardenet, Subhroshekhar Ghosh
Learning from DPPs via Sampling: Beyond HKPV and symmetry. CoRR (2020)
Guillaume Gautier, Guillermo Polito, Rémi Bardenet, Michal Valko
DPPy: DPP Sampling with Python. J. Mach. Learn. Res. 20 (2019)
Guillaume Gautier, Rémi Bardenet, Michal Valko
On two ways to use determinantal point processes for Monte Carlo integration. NeurIPS (2019)
Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
Kernel quadrature with DPPs. NeurIPS (2019)
Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
Kernel quadrature with DPPs. CoRR (2019)
Guillaume Gautier, Rémi Bardenet, Michal Valko
DPPy: Sampling Determinantal Point Processes with Python. CoRR (2018)
Rémi Bardenet, Adrien Hardy
From Random Matrices to Monte Carlo Integration Via Gaussian Quadrature. SSP (2018)
Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
A determinantal point process for column subset selection. CoRR (2018)
Rémi Bardenet, Arnaud Doucet, Christopher C. Holmes
On Markov chain Monte Carlo methods for tall data. J. Mach. Learn. Res. 18 (2017)
Guillaume Gautier, Rémi Bardenet, Michal Valko
Zonotope hit-and-run for efficient sampling from projection DPPs. CoRR (2017)
Guillaume Gautier, Rémi Bardenet, Michal Valko
Zonotope Hit-and-run for Efficient Sampling from Projection DPPs. ICML (2017)
Ross Johnstone, Rémi Bardenet, David Gavaghan, Liudmila Polonchuk, Mark Davies, Gary R. Mirams
Hierarchical Bayesian Modelling of Variability and Uncertainty in Synthetic Action Potential Traces. CinC (2016)
Bernhard Knapp, Rémi Bardenet, Miguel O. Bernabeu, Rafel Bordas, Maria Bruna, Ben Calderhead, Jonathan Cooper, Alexander G. Fletcher, Derek Groen, Bram Kuijper, Joanna Lewis, Greg J. McInerny, Timo Minssen, James M. Osborne, Verena Paulitschke, Joe Pitt-Francis, Jelena Todoric, Christian A. Yates, David Gavaghan, Charlotte M. Deane
Ten Simple Rules for a Successful Cross-Disciplinary Collaboration. PLoS Comput. Biol. 11 (4) (2015)
Rémi Bardenet, Michalis K. Titsias
Inference for determinantal point processes without spectral knowledge. NIPS (2015)
Rémi Bardenet, Arnaud Doucet, Christopher C. Holmes
Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach. ICML (2014)
Rémi Bardenet, Mátyás Brendel, Balázs Kégl, Michèle Sebag
Collaborative hyperparameter tuning. ICML (2) (2013)
Rémi Bardenet, Olivier Cappé, Gersende Fort, Balázs Kégl
Adaptive Metropolis with Online Relabeling. AISTATS (2012)
James Bergstra, Rémi Bardenet, Yoshua Bengio, Balázs Kégl
Algorithms for Hyper-Parameter Optimization. NIPS (2011)
Rémi Bardenet, Balázs Kégl
Surrogating the surrogate: accelerating Gaussian-process-based global optimization with a mixture cross-entropy algorithm. ICML (2010)