:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Mourão-Miranda, Janaina, Hussain, Zakria, Tsirlis, Konstantinos, Phillips, Christophe, Shawe-Taylor, John
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2512.11547
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Controlling Multiple Errors Simultaneously with a PAC-Bayes Bound
by: Adams, Reuben, et al.
Published: (2022)

Interpretable Generative and Discriminative Learning for Multimodal and Incomplete Clinical Data
by: Belenguer-Llorens, Albert, et al.
Published: (2025)

General Uncertainty Estimation with Delta Variances
by: Schmitt, Simon, et al.
Published: (2025)

Some theoretical improvements on the tightness of PAC-Bayes risk certificates for neural networks
by: García-Pérez, Diego, et al.
Published: (2025)

Robust Offline Policy Learning with Observational Data from Multiple Sources
by: Carranza, Aldo Gael, et al.
Published: (2024)

Multiple Locally Linear Kernel Machines
by: Picard, David
Published: (2024)

Leveraging Real-Time Data Analysis and Multiple Kernel Learning for Manufacturing of Innovative Steels
by: Rannetbauer, Wolfgang, et al.
Published: (2025)

Sparse Multiple Kernel Learning: Alternating Best Response and Semidefinite Relaxations
by: Bertsimas, Dimitris, et al.
Published: (2025)

Supervised Multiple Kernel Learning approaches for multi-omics data integration
by: Briscik, Mitja, et al.
Published: (2024)

Uncertainty Quantification With Multiple Sources
by: Ying, Mufang, et al.
Published: (2024)

Multiple Kernel Clustering via Local Regression Integration
by: Du, Liang, et al.
Published: (2024)

Kernel Correlation-Dissimilarity for Multiple Kernel k-Means Clustering
by: Su, Rina, et al.
Published: (2024)

Temporal Taskification in Streaming Continual Learning: A Source of Evaluation Instability
by: Filat, Nicolae, et al.
Published: (2026)

A Theory for Conditional Generative Modeling on Multiple Data Sources
by: Wang, Rongzhen, et al.
Published: (2025)

Kernel-Elastic Autoencoder for Molecular Design
by: Li, Haote, et al.
Published: (2023)

Fast Asymmetric Factorization for Large Scale Multiple Kernel Clustering
by: Chen, Yan, et al.
Published: (2024)

Bayesian Surrogate Training on Multiple Data Sources: A Hybrid Modeling Strategy
by: Reiser, Philipp, et al.
Published: (2024)

Granular-Ball-Induced Multiple Kernel K-Means
by: Xia, Shuyin, et al.
Published: (2025)

MEP: Multiple Kernel Learning Enhancing Relative Positional Encoding Length Extrapolation
by: Gao, Weiguo
Published: (2024)

Sparsity-Aware Distributed Learning for Gaussian Processes with Linear Multiple Kernel
by: Suwandi, Richard Cornelius, et al.
Published: (2023)

Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model
by: Wu, Runqing, et al.
Published: (2025)

Mitigating the Multiplicity Burden: The Role of Calibration in Reducing Predictive Multiplicity of Classifiers
by: Cavus, Mustafa
Published: (2026)

The Role of Hyperparameters in Predictive Multiplicity
by: Cavus, Mustafa, et al.
Published: (2025)

Hierarchical Multiple Kernel K-Means Algorithm Based on Sparse Connectivity
by: Wang, Lei, et al.
Published: (2024)

Q2SAR: A Quantum Multiple Kernel Learning Approach for Drug Discovery
by: Giraldo, Alejandro, et al.
Published: (2025)

Multilinear Kernel Regression and Imputation via Manifold Learning
by: Nguyen, Duc Thien, et al.
Published: (2024)

Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data Sources
by: Xu, Renzhe, et al.
Published: (2025)

Data as a Lever: A Neighbouring Datasets Perspective on Predictive Multiplicity
by: Ganesh, Prakhar, et al.
Published: (2025)

Relative Error Embeddings for the Gaussian Kernel Distance
by: Chen, Di, et al.
Published: (2016)

Generalized Stock Price Prediction for Multiple Stocks Combined with News Fusion
by: Liao, Pei-Jun, et al.
Published: (2026)

Automation of Smart Homes with Multiple Rule Sources
by: Eran, Kaufman, et al.
Published: (2024)

A Family of Kernelized Matrix Costs for Multiple-Output Mixture Neural Networks
by: Hu, Bo, et al.
Published: (2025)

Efficient Joint Prediction of Multiple Future Tokens
by: Ahn, Kwangjun, et al.
Published: (2025)

An Analytical Multiple Criteria Framework for Temporal and Dynamic Business-to-Business Customer Segmentation in Manufacturing
by: Raees, Muhammad, et al.
Published: (2026)

Resolving Predictive Multiplicity for the Rashomon Set
by: Haghighat, Parian, et al.
Published: (2026)

Giga-scale Kernel Matrix Vector Multiplication on GPU
by: Hu, Robert, et al.
Published: (2022)

Data-Adaptive Tradeoffs among Multiple Risks in Distribution-Free Prediction
by: Nguyen, Drew T., et al.
Published: (2024)

Reconciling Predictive Multiplicity in Practice
by: Behzad, Tina, et al.
Published: (2025)

Scaling Law Phenomena Across Regression Paradigms: Multiple and Kernel Approaches
by: Chen, Yifang, et al.
Published: (2025)

Longitudinal Missing Data Imputation for Predicting Disability Stage of Patients with Multiple Sclerosis
by: Vazifehdan, Mahin, et al.
Published: (2025)