On intelligenCE And Networks

Exact Bayesian inference for Markov switching diffusions

Autori: Timothée Stumpf-Fétizon, Krzysztof Łatuszyński, Jan Palczewski, Gareth Roberts
Pubblicato in: 2025
Editore: arxiv

Self-normalized Cramér-type Moderate Deviation of Stochastic Gradient Langevin Dynamics

Autori: Hongsheng Dai, Xiequan Fan, Jianya Lu
Pubblicato in: 2024
Editore: arxiv

Sampling with time-changed Markov processes

Autori: Andrea Bertazzi, Giorgos Vasdekis
Pubblicato in: 2025
Editore: arxiv

Differential privacy guarantees of Markov chain Monte Carlo algorithms

Autori: Andrea Bertazzi, Tim Johnston, Gareth O. Roberts, Alain Durmus
Pubblicato in: arxiv, 2025
Editore: arxiv

Prediction-Aware Learning in Multi-Agent Systems

Autori: Aymeric Capitaine, Etienne Boursier, Eric Moulines, Michael I. Jordan, Alain Durmus
Pubblicato in: 2025
Editore: arxiv

Redesigning the ensemble Kalman filter with a dedicated model of epistemic uncertainty

Autori: Chatchuea Kimchaiwong, Jeremie Houssineau, Adam M. Johansen
Pubblicato in: 2024
Editore: arxiv

On integral priors for multiple comparison in Bayesian model selection

Autori: Diego Salmerón, Juan Antonio Cano, Christian P. Robert
Pubblicato in: arxiv, 2024
Editore: arxiv

Importance sampling-based gradient method for dimension reduction in Poisson log-normal model

Autori: Bastien Batardière, Julien Chiquet, Joon Kwon, Julien Stoehr
Pubblicato in: arxiv, 2024
Editore: arxiv

Career Modeling with Missing Data and Traces

Autori: Théo Voldoire, Robin J. Ryder, Ryan Lahfa
Pubblicato in: arxiv, 2024
Editore: arxiv

Optimal Design for Reward Modeling in RLHF

Autori: Antoine Scheid, Etienne Boursier, Alain Durmus, Michael I. Jordan, Pierre Ménard, Eric Moulines, Michal Valko
Pubblicato in: 2024
Editore: arxiv

Annealed variational mixtures for disease subtyping and biomarker discovery

Autori: Emma Prevot, Rory Toogood, Filippo Pagani, Paul D. W. Kirk
Pubblicato in: 2024
Editore: arxiv

Phylogenetic latent space models for network data

Autori: Federico Pavone, Daniele Durante, Robin J. Ryder
Pubblicato in: arxiv, 2025
Editore: arxiv

Refined Analysis of Federated Averaging's Bias and Federated Richardson-Romberg Extrapolation

Autori: Paul Mangold, Alain Durmus, Aymeric Dieuleveut, Sergey Samsonov, Eric Moulines
Pubblicato in: 2024
Editore: arxiv

A Principled Approach to Bayesian Transfer Learning

Autori: Adam Bretherton, Joshua J. Bon, David J. Warne, Kerrie Mengersen, Christopher Drovandi
Pubblicato in: arxiv, 2025
Editore: arxiv

Beyond Log-Concavity and Score Regularity: Improved Convergence Bounds for Score-Based Generative Models in W2-distance

Autori: Marta Gentiloni-Silveri, Antonio Ocello
Pubblicato in: 2025
Editore: arxiv

Pareto-Optimality, Smoothness, and Stochasticity in Learning-Augmented One-Max-Search

Autori: Ziyad Benomar, Lorenzo Croissant, Vianney Perchet, Spyros Angelopoulos
Pubblicato in: arxiv, 2025
Editore: arxiv

Discrete Markov Probabilistic Models

Autori: Le-Tuyet-Nhi Pham, Dario Shariatian, Antonio Ocello, Giovanni Conforti, Alain Durmus
Pubblicato in: 2025
Editore: arxiv

Conditioning diffusion models by explicit forward-backward bridging

Autori: Adrien Corenflos, Zheng Zhao, Simo Särkkä, Jens Sjölund, Thomas B. Schön
Pubblicato in: 2024
Editore: arxiv

Composite likelihood inference for the Poisson log-normal model

Autori: Julien Stoehr, Stephane Robin
Pubblicato in: arxiv, 2024
Editore: arxiv

Quantifying the Speed-Up from Non-Reversibility in MCMC Tempering Algorithms

Autori: Gareth O. Roberts, Jeffrey S. Rosenthal
Pubblicato in: 2025
Editore: arxiv

Sampling using adaptive regenerative processes

Autori: Hector McKimm, Andi Wang, Murray Pollock, Christian Robert, Gareth Roberts
Pubblicato in: Bernoulli, Numero 31, 2024, ISSN 1350-7265
Editore: Bernoulli Society for Mathematical Statistics and Probability
DOI: 10.3150/24-BEJ1737

Bernoulli factory: The 2-coin problem

Autori: Shenggang Hu, Bo Zhang, Hongsheng Dai, Wei Liang
Pubblicato in: Monte Carlo Methods and Applications, Numero 30, 2024, ISSN 0929-9629
Editore: Walter de Gruyter GmbH
DOI: 10.1515/MCMA-2024-2016

Statistical disaggregation—A Monte Carlo approach for imputation under constraints

Autori: Shenggang Hu, Hongsheng Dai, Fanlin Meng, Louis Aslett, Murray Pollock, Gareth O. Roberts
Pubblicato in: Scandinavian Journal of Statistics, Numero 52, 2025, ISSN 0303-6898
Editore: Wiley
DOI: 10.1111/SJOS.12790

Modelling Pathwise Uncertainty of Stochastic Differential Equations Samplers via Probabilistic Numerics

Autori: Yvann Le Fay, Simo Särkkä, Adrien Corenflos
Pubblicato in: Bayesian Analysis, Numero -1, 2025, ISSN 1936-0975
Editore: Institute of Mathematical Statistics
DOI: 10.1214/25-BA1522

Auxiliary MCMC samplers for parallelisable inference in high-dimensional latent dynamical systems

Autori: Adrien Corenflos, Simo Särkkä
Pubblicato in: Electronic Journal of Statistics, Numero 19, 2025, ISSN 1935-7524
Editore: Institute of Mathematical Statistics
DOI: 10.1214/25-EJS2363

Unbiased and consistent nested sampling via sequential Monte Carlo

Autori: Robert Salomone, Leah F South, Christopher Drovandi, Dirk P Kroese, Adam M Johansen
Pubblicato in: Journal of the Royal Statistical Society Series B: Statistical Methodology, Numero 87, 2025, ISSN 1369-7412
Editore: Oxford University Press (OUP)
DOI: 10.1093/JRSSSB/QKAF015

Parallel Square-Root Statistical Linear Regression for Inference in Nonlinear State Space Models

Autori: Fatemeh Yaghoobi, Adrien Corenflos, Sakira Hassan, Simo Särkkä
Pubblicato in: SIAM Journal on Scientific Computing, Numero 47, 2025, ISSN 1064-8275
Editore: Society for Industrial & Applied Mathematics (SIAM)
DOI: 10.1137/23M156121X

Robust inference for the unification of confidence intervals in meta-analysis

Autori: Wei Liang, Haicheng Huang, Hongsheng Dai, Yinghui Wei
Pubblicato in: Journal of Nonparametric Statistics, 2025, ISSN 1048-5252
Editore: Informa UK Limited
DOI: 10.1080/10485252.2025.2492254

Scaling of piecewise deterministic Monte Carlo for anisotropic targets

Autori: Joris Bierkens, Kengo Kamatani, Gareth O. Roberts
Pubblicato in: Bernoulli, Numero 31, 2025, ISSN 1350-7265
Editore: Bernoulli Society for Mathematical Statistics and Probability
DOI: 10.3150/24-BEJ1807

Particle Semi-Implicit Variational Inference

Autori: Jen Ning Lim, Adam Johansen
Pubblicato in: Neurips 2024, 2024
Editore: Neurips 2024

Enhancing Feature-Specific Data Protection via Bayesian Coordinate Differential Privacy

Autori: Maryam Aliakbarpour, Syomantak Chaudhuri, Thomas A. Courtade, Alireza Fallah, Michael I. Jordan
Pubblicato in: AISTAT 2025, 2024
Editore: AISTAT 2025

Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents

Autori: Safwan Labbi, Daniil Tiapkin, Lorenzo Mancini, Paul Mangold, Eric Moulines
Pubblicato in: AISTAT 2025, 2024
Editore: AISTAT 2025

The Statistical Fairness-Accuracy Frontier

Autori: Alireza Fallah, Michael I. Jordan, Annie Ulichney
Pubblicato in: 2025
Editore: arxiv

Delegating Data Collection in Decentralized Machine Learning

Autori: Nivasini Ananthakrishnan, Stephen Bates, Michael I. Jordan, Nika Haghtalab
Pubblicato in: Proceedings of Machine Learning Research, 2023, ISSN 2640-3498
Editore: Proceedings of Machine Learning Research

Learning Contracts in Hierarchical Multi-Agent Systems

Autori: Antoine Scheid, Etienne Boursier, Alain Durmus, Eric Moulines, Michael Jordan
Pubblicato in: 2025
Editore: arxiv

Improved learning rates in multi-unit uniform price auctions

Autori: Marius Potfer, Dorian Baudry, Hugo Richard, Vianney Perchet, Cheng Wan
Pubblicato in: Neurips proceedings 2024, 2024
Editore: Neurips proceedings 2024

Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up

Autori: Paul Mangold, Alain Durmus, Aymeric Dieuleveut, Eric Moulines
Pubblicato in: 2025
Editore: ICML2025

Empirical Privacy Variance

Autori: Yuzheng Hu, Fan Wu, Ruicheng Xian, Yuhang Liu, Lydia Zakynthinou, Pritish Kamath, Chiyuan Zhang, David Forsyth
Pubblicato in: ICML 2025, 2025
Editore: ICML 2025

Divide-and-Conquer Posterior Sampling for Denoising Diffusion priors

Autori: Yazid Janati, Badr MOUFAD, Alain Durmus, Eric Moulines, Jimmy Olsson
Pubblicato in: Neurips 2024, 2024
Editore: Neurips 2024

DAVED: Data Acquisition via Experimental Design for Data Markets

Autori: Charles Lu, Baihe Huang, Sai Praneeth Karimireddy, Praneeth Vepakomma, Michael Jordan, Ramesh Raskar
Pubblicato in: 2024
Editore: arxiv

Fair Allocation in Dynamic Mechanism Design

Autori: Alireza Fallah, Michael I. Jordan, Annie Ulichney
Pubblicato in: Neurips 2024, 2024, ISSN 2331-8422
Editore: Neurips 2024

Incentivized Learning in Principal-Agent Bandit Games

Autori: Antoine Scheid, Daniil Tiapkin, Etienne Boursier, Aymeric Capitaine, El Mahdi El Mhamdi, Eric Moulines, Michael I. Jordan, Alain Durmus
Pubblicato in: ICML 2024, 2024, ISSN 2640-3498
Editore: The Proceedings of Machine Learning Research

Strategic Multi-Armed Bandit Problems Under Debt-Free Reporting

Autori: Ahmed Ben Yahmed, Clément Calauzènes, Vianney Perchet
Pubblicato in: Neurips 2024, 2024
Editore: Neurips 2024

On integral priors for multiple comparison in Bayesian model selection

Autori: Diego Salmerón, Juan Antonio Cano, Christian P. Robert
Pubblicato in: 2024
Editore: Arxiv

Privacy Guarantees in Posterior Sampling under Contamination

Autori: Shenggang Hu, Louis Aslett, Hongsheng Dai, Murray Pollock, Gareth O Roberts
Pubblicato in: 2024, ISSN 2331-8422
Editore: arxiv

Gaussian Approximation and Multiplier Bootstrap for Polyak-Ruppert Averaged Linear Stochastic Approximation with Applications to TD Learning

Autori: Sergey Samsonov, Eric Moulines, Qi-Man Shao, Zhuo-Song Zhang, Alexey Naumov
Pubblicato in: 2024
Editore: arxiv

Learning Variational Inequalities from Data: Fast Generalization Rates under Strong Monotonicity

Autori: Eric Zhao, Tatjana Chavdarova, Michael Jordan
Pubblicato in: 2024
Editore: arxiv

Improved Algorithms for Contextual Dynamic Pricing

Autori: Matilde Tullii, Solenne Gaucher, Nadav Merlis, Vianney Perchet
Pubblicato in: Neurips 2024, 2024
Editore: Neurips 2024

Privacy Can Arise Endogenously in an Economic System with Learning Agents

Autori: Nivasini Ananthakrishnan, Tiffany Ding, Mariel Werner, Sai Praneeth Karimireddy, Michael I. Jordan
Pubblicato in: FORC 2024, 2024
Editore: FORC 2024
DOI: 10.4230/LIPIcs.FORC.2024.9

Safety vs. Performance: How Multi-Objective Learning Reduces Barriers to Market Entry

Autori: Meena Jagadeesan, Michael I. Jordan, and Jacob Steinhardt
Pubblicato in: 2024
Editore: arxiv

Fairness-Aware Meta-Learning via Nash Bargaining

Autori: Yi Zeng, Xuelin Yang, Li Chen, Cristian Canton Ferrer, Ming Jin, Michael I. Jordan, Ruoxi Jia
Pubblicato in: 2024, ISSN 2331-8422
Editore: arxiv

Solving Fredholm Integral Equations of the Second Kind via Wasserstein Gradient Flows

Autori: Francesca R Crucinio, Adam M Johansen
Pubblicato in: 2024
Editore: arxiv

Learning to Mitigate Externalities: the Coase Theorem with Hindsight Rationality

Autori: Antoine Scheid, Aymeric Capitaine, Etienne Boursier, Eric Moulines, Michael I Jordan, Alain Durmus
Pubblicato in: Neurips proceedings 2024, 2024, ISSN 2331-8422
Editore: Neurips 2024

Unravelling in Collaborative Learning

Autori: Aymeric Capitaine, Etienne Boursier, Antoine Scheid, Eric Moulines, Michael I. Jordan, El-Mahdi El-Mhamdi, Alain Durmus
Pubblicato in: Neurips proceedings 2024, 2024, ISSN 2331-8422
Editore: Neurips proceedings 2024

Optimizing the coalition gain in Online Auctions with Greedy Structured Bandits

Autori: Dorian Baudry, Hugo Richard, Maria Cherifa, Vianney Perchet, Clément Calauzènes
Pubblicato in: Neurips 2024, 2024
Editore: Neurips 2024

Information Elicitation in Agency Games

Autori: Serena Wang, Michael I. Jordan, Katrina Ligett, R. Preston McAfee
Pubblicato in: 2024
Editore: arxiv

Piecewise deterministic generative models

Autori: A. bertazzi, A. Durmus, D. Shariatian, U. Simsekli, E. Moulines
Pubblicato in: Neurips 2024, 2024
Editore: Neurips proceedings 2024

Stereographic Markov Chain Monte Carlo

Autori: Jun Yang, K. Latuszy'nski, G. Roberts
Pubblicato in: 2024, ISSN 2331-8422
Editore: arxiv

Theoretical guarantees in KL for Diffusion Flow Matching

Autori: Marta Gentiloni Silveri, Alain Durmus, Giovanni Conforti
Pubblicato in: Neurips 2024, 2024
Editore: Neurips 2024

Addressing Bias in Online Selection with Limited Budget of Comparisons

Autori: Ziyad Benomar, Evgenii Chzhen, Nicolas Schreuder, Vianney Perchet
Pubblicato in: Neurips 2024, 2024
Editore: Neurips 2024

Class-Conditional Conformal Prediction with Many Classes

Autori: Tiffany Ding, Anastasios N. Angelopoulos, Stephen Bates, Michael I. Jordan, Ryan J. Tibshirani
Pubblicato in: Neurips proceedings 2024, 2024, ISSN 1234-5678
Editore: Neurips 2024

On Counterfactual Metrics for Social Welfare: Incentives, Ranking, and Information Asymmetry

Autori: Serena Wang, Stephen Bates, P Aronow, Michael Jordan
Pubblicato in: Proceedings of Machine Learning Research, 2023, ISSN 2640-3498
Editore: Proceedings of Machine Learning Research

Backward Conformal Prediction

Autori: Etienne Gauthier, Francis Bach, Michael I. Jordan
Pubblicato in: 2025
Editore: Neurips 2025

Dimension-free Private Mean Estimation for Anisotropic Distributions

Autori: Yuval Dagan, Michael Jordan, Xuelin Yang, Lydia Zakynthinou, Nikita Zhivotovskiy
Pubblicato in: Neurips proceedings 2024, 2024
Editore: Neurips proceedings 2024

The Value of Reward Lookahead in Reinforcement Learning

Autori: Nadav Merlis, Dorian Baudry, Vianney Perchet
Pubblicato in: Neurips 2024, 2024
Editore: Neurips 2024

Almost sure convergence rates of adaptive increasingly rare Markov chain Monte Carlo

Autori: Julian Hofstadler, Krzysztof Latuszynski, Gareth O Roberts, Daniel Rudolf
Pubblicato in: 2024, ISSN 2331-8422
Editore: arxiv

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