Distribution-Free Distribution Regression

1 February 2013

Aarti Singh

Papers citing "Distribution-Free Distribution Regression"

47 / 47 papers shown

Title
Bayesian Density-Density Regression with Application to Cell-Cell Communications Khai Nguyen Yang Ni Peter Mueller 89 0 0 17 Apr 2025
Improved learning theory for kernel distribution regression with two-stage sampling François Bachoc Louis Bethune Alberto González Sanz Jean-Michel Loubes 145 2 0 28 Jan 2025
Scalable Signature-Based Distribution Regression via Reference Sets Andrew Alden Carmine Ventre Blanka Horvath 142 0 0 11 Oct 2024
Learning to Embed Distributions via Maximum Kernel Entropy Oleksii Kachaiev Stefano Recanatesi OOD 120 0 0 01 Aug 2024
Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels Raphael Carpintero Perez Sébastien da Veiga Josselin Garnier B. Staber 107 6 0 06 Feb 2024
LearnedWMP: Workload Memory Prediction Using Distribution of Query Templates Shaikh Quader Andres Jaramillo Sumona Mukhopadhyay Ghadeer Abuoda Calisto Zuzarte David Kalmuk Marin Litoiu Manos Papagelis 33 1 0 22 Jan 2024
Learning Theory of Distribution Regression with Neural Networks Zhongjie Shi Zhan Yu Ding-Xuan Zhou 32 2 0 07 Jul 2023
Statistical learning on measures: an application to persistence diagrams Olympio Hacquard Gilles Blanchard Clément Levrard 134 3 0 15 Mar 2023
Direct Bayesian Regression for Distribution-valued Covariates Bohao Tang Sandipan Pramanik Yi Zhao B. Caffo A. Datta 39 0 0 11 Mar 2023
Gaussian Processes on Distributions based on Regularized Optimal Transport François Bachoc Louis Bethune Alberto González Sanz Jean-Michel Loubes GP OT 66 8 0 12 Oct 2022
Coefficient-based Regularized Distribution Regression Yuan Mao Lei Shi Zheng-Chu Guo 118 4 0 26 Aug 2022
Generalized Identifiability Bounds for Mixture Models with Grouped Samples Robert A. Vandermeulen René Saitenmacher 72 3 0 22 Jul 2022
Performance of Distribution Regression with Doubling Measure under the seek of Closest Point Ilqar Ramazanli 52 3 0 01 Mar 2022
Distribution Regression with Sliced Wasserstein Kernels Dimitri Meunier Massimiliano Pontil C. Ciliberto OOD 72 17 0 08 Feb 2022
Label-Free Model Evaluation with Semi-Structured Dataset Representations Xiaoxiao Sun Yunzhong Hou Hongdong Li Liang Zheng 66 12 0 01 Dec 2021
A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification Anastasios Nikolas Angelopoulos Stephen Bates OOD 271 625 0 15 Jul 2021
Robust Kernel-based Distribution Regression Zhan Yu D. Ho Ding-Xuan Zhou OOD 68 11 0 21 Apr 2021
Nonlinear Distribution Regression for Remote Sensing Applications J. Adsuara Adrián Pérez-Suay Jordi Munoz-Marí Anna Mateo-Sanchis M. Piles Gustau Camps-Valls 102 17 0 07 Dec 2020
Causal inference using deep neural networks Ye Yuan Xueying Ding Z. Bar-Joseph BDL CML 50 2 0 25 Nov 2020
Stochastic Gradient Descent Meets Distribution Regression Nicole Mücke 62 5 0 24 Oct 2020
Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models Fadhel Ayed Lorenzo Stella Tim Januschowski Jan Gasthaus AI4TS 103 10 0 30 Jul 2020
Estimates on Learning Rates for Multi-Penalty Distribution Regression Zhan Yu D. Ho 23 0 0 16 Jun 2020
Deep Kernels with Probabilistic Embeddings for Small-Data Learning Ankur Mallick Chaitanya Dwivedi B. Kailkhura Gauri Joshi T. Y. Han BDL UQCV 44 8 0 13 Oct 2019
Dataset2Vec: Learning Dataset Meta-Features H. Jomaa Lars Schmidt-Thieme Josif Grabocka SSL 86 64 0 27 May 2019
3D Object Recognition with Ensemble Learning --- A Study of Point Cloud-Based Deep Learning Models Daniel Koguciuk L. Chechlinski Tarek El-Gaaly 3DPC 48 11 0 17 Apr 2019
On Deep Set Learning and the Choice of Aggregations Maximilian Sölch A. Akhundov Patrick van der Smagt Justin Bayer TDI 72 20 0 18 Mar 2019
Theoretical and Experimental Analysis on the Generalizability of Distribution Regression Network C. Kou H. Lee Jorge Sanz Teck Khim Ng 27 0 0 05 Nov 2018
Distribution regression model with a Reproducing Kernel Hilbert Space approach T. T. T. Bui Jean-Michel Loubes Risser Balaresque 58 11 0 27 Jun 2018
Causal effects based on distributional distances Kwangho Kim Jisu Kim Edward H. Kennedy CML 56 19 0 08 Jun 2018
A Compact Network Learning Model for Distribution Regression C. Kou H. Lee Teck Khim Ng 64 10 0 13 Apr 2018
Kernel Embedding Approaches to Orbit Determination of Spacecraft Clusters Srinagesh Sharma J. Cutler 15 3 0 01 Mar 2018
Distance Measure Machines A. Rakotomamonjy Abraham Traoré Maxime Bérar Rémi Flamary Nicolas Courty 64 12 0 01 Mar 2018
Estimating Cosmological Parameters from the Dark Matter Distribution Siamak Ravanbakhsh Junier Oliva S. Fromenteau Layne Price S. Ho J. Schneider Barnabás Póczós 78 76 0 06 Nov 2017
Bayesian Approaches to Distribution Regression H. Law Danica J. Sutherland Dino Sejdinovic Seth Flaxman OOD UQCV BDL 91 37 0 11 May 2017
Deep Sets Manzil Zaheer Satwik Kottur Siamak Ravanbakhsh Barnabás Póczós Ruslan Salakhutdinov Alex Smola 481 2,485 0 10 Mar 2017
A Gaussian Process Regression Model for Distribution Inputs François Bachoc Fabrice Gamboa Jean-Michel Loubes N. Venet 106 53 0 31 Jan 2017
Prototypal Analysis and Prototypal Regression Chenyue Wu E. Tabak 63 13 0 31 Jan 2017
From Dependence to Causation David Lopez-Paz OOD CML 179 26 0 12 Jul 2016
Uncertain programming model for multi-item solid transportation problem Hasan Dalman 155 64 0 31 May 2016
Operator-valued Kernels for Learning from Functional Response Data Hachem Kadri E. Duflos Philippe Preux S. Canu A. Rakotomamonjy Julien Audiffren 93 131 0 28 Oct 2015
Linear-time Learning on Distributions with Approximate Kernel Embeddings Danica J. Sutherland Junier B. Oliva Barnabás Póczós J. Schneider 61 18 0 24 Sep 2015
On The Identifiability of Mixture Models from Grouped Samples Robert A. Vandermeulen Clayton D. Scott 45 9 0 23 Feb 2015
Passing Expectation Propagation Messages with Kernel Methods Wittawat Jitkrittum Arthur Gretton N. Heess 27 0 0 02 Jan 2015
Learning Theory for Distribution Regression Z. Szabó Bharath K. Sriperumbudur Barnabás Póczós Arthur Gretton OOD 116 140 0 08 Nov 2014
Two-stage Sampled Learning Theory on Distributions Z. Szabó Arthur Gretton Barnabás Póczós Bharath K. Sriperumbudur OOD 61 3 0 07 Feb 2014
Fast Distribution To Real Regression Junier B. Oliva Willie Neiswanger Barnabás Póczós J. Schneider Eric Xing 91 45 0 10 Nov 2013
FuSSO: Functional Shrinkage and Selection Operator Junier B. Oliva Barnabás Póczós Timothy D. Verstynen Aarti Singh J. Schneider F. Yeh W. Tseng 42 10 0 10 Nov 2013