Learning Theory for Distribution Regression

Learning Theory for Distribution Regression

8 November 2014

Bharath K. Sriperumbudur

Barnabás Póczós

Papers citing "Learning Theory for Distribution Regression"

19 / 19 papers shown

Title
Improved learning theory for kernel distribution regression with two-stage sampling F. Bachoc Louis Bethune Alberto González Sanz Jean-Michel Loubes 96 1 0 28 Jan 2025
Demystifying amortized causal discovery with transformers Francesco Montagna Max Cairney-Leeming Dhanya Sridhar Francesco Locatello CML 57 1 0 27 May 2024
Asymptotic analysis for covariance parameter estimation of Gaussian processes with functional inputs Lucas Reding A. F. López-Lopera F. Bachoc 44 1 0 26 Apr 2024
Domain Generalization by Functional Regression Markus Holzleitner S. Pereverzyev Werner Zellinger OOD 21 4 0 09 Feb 2023
Statistical Optimality of Divide and Conquer Kernel-based Functional Linear Regression Jiading Liu Lei Shi 30 9 0 20 Nov 2022
Learning linear operators: Infinite-dimensional regression as a well-behaved non-compact inverse problem Mattes Mollenhauer Nicole Mücke T. Sullivan 30 25 0 16 Nov 2022
Gaussian Processes on Distributions based on Regularized Optimal Transport F. Bachoc Louis Bethune Alberto González Sanz Jean-Michel Loubes GP OT 34 7 0 12 Oct 2022
Generalized Identifiability Bounds for Mixture Models with Grouped Samples Robert A. Vandermeulen René Saitenmacher 28 2 0 22 Jul 2022
Nonlinear Distribution Regression for Remote Sensing Applications J. Adsuara Adrián Pérez-Suay Jordi Munoz-Marí Anna Mateo-Sanchis M. Piles Gustau Camps-Valls 21 17 0 07 Dec 2020
Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models Fadhel Ayed Lorenzo Stella Tim Januschowski Jan Gasthaus AI4TS 40 10 0 30 Jul 2020
Amortised Learning by Wake-Sleep W. Li Theodore H. Moskovitz Heishiro Kanagawa M. Sahani OOD 23 7 0 22 Feb 2020
A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings Junhyung Park Krikamol Muandet 35 77 0 10 Feb 2020
Kernel Instrumental Variable Regression Rahul Singh M. Sahani Arthur Gretton 33 168 0 01 Jun 2019
BRUNO: A Deep Recurrent Model for Exchangeable Data I. Korshunova Jonas Degrave Ferenc Huszár Y. Gal Arthur Gretton J. Dambre BDL 24 33 0 21 Feb 2018
MONK -- Outlier-Robust Mean Embedding Estimation by Median-of-Means M. Lerasle Z. Szabó Gaspar Massiot Guillaume Lecué 34 34 0 13 Feb 2018
Kernel method for persistence diagrams via kernel embedding and weight factor G. Kusano Kenji Fukumizu Y. Hiraoka 17 83 0 12 Jun 2017
Deep Sets Manzil Zaheer Satwik Kottur Siamak Ravanbakhsh Barnabás Póczós Ruslan Salakhutdinov Alex Smola 95 2,422 0 10 Mar 2017
Kernel regression, minimax rates and effective dimensionality: beyond the regular case Gilles Blanchard Nicole Mücke 13 9 0 12 Nov 2016
Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages Wittawat Jitkrittum Arthur Gretton N. Heess S. M. Ali Eslami Balaji Lakshminarayanan Dino Sejdinovic Z. Szabó 35 33 0 09 Mar 2015