Rémi Bardenet

48 papers A* 9A 1Misc 1Journal 30Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Repulsive Monte Carlo on the sphere for the sliced Wasserstein distance. Trans. Mach. Learn. Res. Vladimir Petrovic, Rémi Bardenet, Agnès Desolneux
2025	—	`conf`	Adaptive hyperparameter tuning for time-frequency algorithms based on the zeros of the spectrogram. SSP Juan Manuel Miramont, Rémi Bardenet, Pierre Chainais, François Auger
2025	J	`jnl`	Bypassing orthogonalization in the quantum DPP sampler. CoRR Michaël Fanuel, Rémi Bardenet
2025	J	`jnl`	Negative Dependence as a toolbox for machine learning : review and new developments. CoRR Hoang Son Tran, Vladimir Petrovic, Rémi Bardenet, Subhroshekhar Ghosh
2025	J	`jnl`	Quenched large deviations for Monte Carlo integration with Coulomb gases. CoRR Rémi Bardenet, Mylène Maïda, Martin Rouault
2025	J	`jnl`	Repulsive Monte Carlo on the sphere for the sliced Wasserstein distance. CoRR Vladimir Petrovic, Rémi Bardenet, Agnès Desolneux
2024	J	`jnl`	Benchmarking multi-component signal processing methods in the time-frequency plane. CoRR Juan Manuel Miramont, Rémi Bardenet, Pierre Chainais, François Auger
2024	J	`jnl`	Monte Carlo methods on compact complex manifolds using Bergman kernels. CoRR Thibaut Lemoine, Rémi Bardenet
2024	J	`jnl`	Monte Carlo with kernel-based Gibbs measures: Guarantees for probabilistic herding. CoRR Martin Rouault, Rémi Bardenet, Mylène Maïda
2024	J	`jnl`	On the Number of Steps of CyclePopping in Weakly Inconsistent U(1)-Connection Graphs. CoRR Michaël Fanuel, Rémi Bardenet
2024	J	`jnl`	Point Processes and spatial statistics in time-frequency analysis. CoRR Barbara Pascal, Rémi Bardenet
2024	A*	`conf`	Small coresets via negative dependence: DPPs, linear statistics, and concentration. NeurIPS Rémi Bardenet, Subhroshekhar Ghosh, Hugo Simon-Onfroy, Hoang Son Tran
2024	J	`jnl`	Small coresets via negative dependence: DPPs, linear statistics, and concentration. CoRR Rémi Bardenet, Subhroshekhar Ghosh, Hugo Simon-Onfroy, Hoang Son Tran
2023	J	`jnl`	On estimating the structure factor of a point process, with applications to hyperuniformity. Stat. Comput. Diala Hawat, Guillaume Gautier, Rémi Bardenet, Raphaël Lachièze-Rey
2023	J	`jnl`	On proportional volume sampling for experimental design in general spaces. Stat. Comput. Arnaud Poinas, Rémi Bardenet
2023	J	`jnl`	On sampling determinantal and Pfaffian point processes on a quantum computer. CoRR Rémi Bardenet, Michaël Fanuel, Alexandre Feller
2023	J	`jnl`	Signal reconstruction using determinantal sampling. CoRR Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
2023	Misc	`conf`	Smoothing Complex-Valued Signals on Graphs with Monte-Carlo. ICASSP Hugo Jaquard, Michaël Fanuel, Pierre-Olivier Amblard, Rémi Bardenet, Simon Barthelmé, Nicolas Tremblay
2022	J	`jnl`	A Covariant, Discrete Time-Frequency Representation Tailored for Zero-Based Signal Detection. IEEE Trans. Signal Process. Barbara Pascal, Rémi Bardenet
2022	J	`jnl`	Sparsification of the regularized magnetic Laplacian with multi-type spanning forests. CoRR Michaël Fanuel, Rémi Bardenet
2022	—	`book`	Turning repulsive point processes into subsampling algorithms. Rémi Bardenet
2021	A*	`conf`	Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGD. NeurIPS Rémi Bardenet, Subhroshekhar Ghosh, Meixia Lin
2021	J	`jnl`	Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGD. CoRR Rémi Bardenet, Subhroshekhar Ghosh, Meixia Lin
2021	J	`jnl`	Fast sampling from β-ensembles. Stat. Comput. Guillaume Gautier, Rémi Bardenet, Michal Valko
2021	A*	`conf`	Nonparametric estimation of continuous DPPs with kernel methods. NeurIPS Michaël Fanuel, Rémi Bardenet
2021	J	`jnl`	Nonparametric estimation of continuous DPPs with kernel methods. CoRR Michaël Fanuel, Rémi Bardenet
2020	J	`jnl`	A determinantal point process for column subset selection. J. Mach. Learn. Res. Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
2020	A*	`conf`	Kernel interpolation with continuous volume sampling. ICML Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
2020	J	`jnl`	Kernel interpolation with continuous volume sampling. CoRR Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
2020	J	`jnl`	Learning from DPPs via Sampling: Beyond HKPV and symmetry. CoRR Rémi Bardenet, Subhroshekhar Ghosh
2019	J	`jnl`	DPPy: DPP Sampling with Python. J. Mach. Learn. Res. Guillaume Gautier, Guillermo Polito, Rémi Bardenet, Michal Valko
2019	A*	`conf`	Kernel quadrature with DPPs. NeurIPS Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
2019	J	`jnl`	Kernel quadrature with DPPs. CoRR Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
2019	A*	`conf`	On two ways to use determinantal point processes for Monte Carlo integration. NeurIPS Guillaume Gautier, Rémi Bardenet, Michal Valko
2018	J	`jnl`	A determinantal point process for column subset selection. CoRR Ayoub Belhadji, Rémi Bardenet, Pierre Chainais
2018	J	`jnl`	DPPy: Sampling Determinantal Point Processes with Python. CoRR Guillaume Gautier, Rémi Bardenet, Michal Valko
2018	—	`conf`	From Random Matrices to Monte Carlo Integration Via Gaussian Quadrature. SSP Rémi Bardenet, Adrien Hardy
2017	J	`jnl`	On Markov chain Monte Carlo methods for tall data. J. Mach. Learn. Res. Rémi Bardenet, Arnaud Doucet, Christopher C. Holmes
2017	A*	`conf`	Zonotope Hit-and-run for Efficient Sampling from Projection DPPs. ICML Guillaume Gautier, Rémi Bardenet, Michal Valko
2017	J	`jnl`	Zonotope hit-and-run for efficient sampling from projection DPPs. CoRR Guillaume Gautier, Rémi Bardenet, Michal Valko
2016	—	`conf`	Hierarchical Bayesian Modelling of Variability and Uncertainty in Synthetic Action Potential Traces. CinC Ross H. Johnstone, Rémi Bardenet, David Gavaghan, Liudmila Polonchuk, Mark Davies, Gary R. Mirams
2015	—	`conf`	Inference for determinantal point processes without spectral knowledge. NIPS Rémi Bardenet, Michalis K. Titsias
2015	J	`jnl`	Ten Simple Rules for a Successful Cross-Disciplinary Collaboration. PLoS Comput. Biol. 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
2014	A*	`conf`	Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach. ICML Rémi Bardenet, Arnaud Doucet, Christopher C. Holmes
2013	—	`conf`	Collaborative hyperparameter tuning. ICML (2) Rémi Bardenet, Mátyás Brendel, Balázs Kégl, Michèle Sebag
2012	A	`conf`	Adaptive Metropolis with Online Relabeling. AISTATS Rémi Bardenet, Olivier Cappé, Gersende Fort, Balázs Kégl
2011	—	`conf`	Algorithms for Hyper-Parameter Optimization. NIPS James Bergstra, Rémi Bardenet, Yoshua Bengio, Balázs Kégl
2010	A*	`conf`	Surrogating the surrogate: accelerating Gaussian-process-based global optimization with a mixture cross-entropy algorithm. ICML Rémi Bardenet, Balázs Kégl