:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Cheshire, James, Clémençon, Stephan
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2602.24263
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Beyond Kemeny Medians: Consensus Ranking Distributions Definition, Properties and Statistical Learning
by: Clémençon, Stephan, et al.
Published: (2026)

On Ranking-based Tests of Independence
by: Limnios, Myrto, et al.
Published: (2024)

Robust Distributed Estimation: Extending Gossip Algorithms to Ranking and Trimmed Means
by: Van Elst, Anna, et al.
Published: (2025)

Asynchronous Gossip Algorithms for Rank-Based Statistical Methods
by: Van Elst, Anna, et al.
Published: (2025)

Active Seriation: Efficient Ordering Recovery with Statistical Guarantees
by: Cheshire, James, et al.
Published: (2026)

Decentralized Ranking Aggregation via Gossip: Convergence and Robustness
by: Caillec, Kerrian Le, et al.
Published: (2026)

Doing well with less! On Sampling Techniques for Empirical Pairwise Loss Estimation/Minimization
by: Davy, Louise, et al.
Published: (2026)

A Statistical Learning View of Simple Kriging
by: Siviero, Emilia, et al.
Published: (2022)

Mitigating Bias in Facial Recognition Systems: Centroid Fairness Loss Optimization
by: Conti, Jean-Rémy, et al.
Published: (2025)

Assessing Uncertainty in Similarity Scoring: Performance & Fairness in Face Recognition
by: Conti, Jean-Rémy, et al.
Published: (2022)

Fast and Efficient Gossip Algorithms for Robust and Non-smooth Decentralized Learning
by: van Elst, Anna, et al.
Published: (2026)

On Gossip Algorithms for Machine Learning with Pairwise Objectives
by: Colin, Igor, et al.
Published: (2026)

Flexible Parametric Inference for Space-Time Hawkes Processes
by: Siviero, Emilia, et al.
Published: (2024)

On Regression in Extreme Regions
by: Clémençon, Stephan, et al.
Published: (2023)

TimeSAE: Sparse Decoding for Faithful Explanations of Black-Box Time Series Models
by: Oublal, Khalid, et al.
Published: (2026)

Posterior Label Smoothing for Node Classification
by: Heo, Jaeseung, et al.
Published: (2024)

Polar Depth for Potentially Heavy-Tailed Data
by: Clemençon, Stephan, et al.
Published: (2026)

Feature Impact Analysis on Top Long-Jump Performances with Quantile Random Forest and Explainable AI Techniques
by: Gan, Qi, et al.
Published: (2025)

Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation
by: Lukasik, Michal, et al.
Published: (2025)

Low-Rank Filtering and Smoothing for Sequential Deep Learning
by: Sliwa, Joanna, et al.
Published: (2024)

Smooth Ranking SVM via Cutting-Plane Method
by: Ozcan, Erhan Can, et al.
Published: (2024)

Bernstein Flows for Flexible Posteriors in Variational Bayes
by: Dürr, Oliver, et al.
Published: (2022)

Neural Bipartite Matching
by: Georgiev, Dobrik, et al.
Published: (2020)

Active Sequential Posterior Estimation for Sample-Efficient Simulation-Based Inference
by: Griesemer, Sam, et al.
Published: (2024)

Estimating Total Effects in Bipartite Experiments with Spillovers and Partial Eligibility
by: Tan, Albert, et al.
Published: (2025)

Emergent Low-Rank Training Dynamics in MLPs with Smooth Activations
by: Xu, Alec S., et al.
Published: (2026)

A Smoothing Newton Method for Rank-one Matrix Recovery
by: Maunu, Tyler, et al.
Published: (2025)

Intriguing Properties of Input-dependent Randomized Smoothing
by: Súkeník, Peter, et al.
Published: (2021)

Joint Out-of-Distribution Filtering and Data Discovery Active Learning
by: Schmidt, Sebastian, et al.
Published: (2025)

Oxytrees: Model Trees for Bipartite Learning
by: Ilídio, Pedro, et al.
Published: (2025)

RankOOD -- Class Ranking-based Out-of-Distribution Detection
by: Denipitiyage, Dishanika, et al.
Published: (2025)

Theoretical Analysis of Heteroscedastic Gaussian Processes with Posterior Distributions
by: Ito, Yuji
Published: (2024)

On the Posterior Distribution in Denoising: Application to Uncertainty Quantification
by: Manor, Hila, et al.
Published: (2023)

Distributional Active Inference
by: Akgül, Abdullah, et al.
Published: (2026)

STERLING: Synergistic Representation Learning on Bipartite Graphs
by: Jing, Baoyu, et al.
Published: (2023)

Fair Active Ranking from Pairwise Preferences
by: Gorantla, Sruthi, et al.
Published: (2024)

Hierarchical Randomized Smoothing
by: Scholten, Yan, et al.
Published: (2023)

Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors
by: Choi, Jeongwhan, et al.
Published: (2026)

Disentanglement Analysis in Deep Latent Variable Models Matching Aggregate Posterior Distributions
by: Saha, Surojit, et al.
Published: (2025)

Rank Collapse Causes Over-Smoothing and Over-Correlation in Graph Neural Networks
by: Roth, Andreas, et al.
Published: (2023)