Cover Image

On Rank Graduation Metrics for High Dimensional Ordinal Data

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Auricchio, Gennaro, Bernardelli, Adelaide Emma, Giudici, Paolo, Toscani, Giuseppe
Format:	Preprint
Published:	2025
Subjects:	Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

From Kinetic Theory to AI: a Rediscovery of High-Dimensional Divergences and Their Properties
by: Auricchio, Gennaro, et al.
Published: (2025)

Extending the Gini Index to Higher Dimensions via Whitening Processes
by: Auricchio, Gennaro, et al.
Published: (2024)

How to measure multidimensional variation?
by: Auricchio, Gennaro, et al.
Published: (2024)

On the computation of the infinity Wasserstein distance and the Wasserstein Projection Problem
by: Auricchio, Gennaro, et al.
Published: (2025)

Multivariate Gini-type discrepancies
by: Auricchio, Gennaro, et al.
Published: (2024)

The Cloven Traveling Salesman: Cycle Covers and the Integrality Gap of Small ATSP Instances
by: Sosso, Alessandro, et al.
Published: (2025)

Theoretical Perspectives on Jabr-Type Convex Relaxations for AC Optimal Power Flow
by: Riccardi, Gabor, et al.
Published: (2026)

Preference Robust Ordinal Priority Approach with Preference Elicitation under Incomplete Information for Multi-Attribute Robust Ranking and Selection
by: Wang, Renlong
Published: (2024)

Energy distance and evolution problems: a promising tool for kinetic equations
by: Auricchio, Gennaro, et al.
Published: (2025)

Deck of Cards method for Hierarchical, Robust and Stochastic Ordinal Regression
by: Corrente, Salvatore, et al.
Published: (2024)

No-Rank Tensor Decomposition Using Metric Learning
by: Bagherian, Maryam
Published: (2025)

Adapting Polyhedral Dominance Cones to Ordinal Preference Structures
by: Klamroth, Kathrin, et al.
Published: (2026)

Convex Data-Driven Contraction With Riemannian Metrics
by: Oliveira, Andreas, et al.
Published: (2024)

Analysis of a combined Filtered/phase-field approach to topology optimization in elasticit
by: Auricchio, Ferdinando, et al.
Published: (2024)

Generalized Ordinal Priority Approach for Multi-Attribute Decision-Making under Incomplete Preference Information
by: Wang, Renlong
Published: (2024)

Optimal Computing Budget Allocation for Data-driven Ranking and Selection
by: Wang, Yuhao, et al.
Published: (2022)

Lower bounds for the integrality gap of the bi-directed cut formulation of the Steiner Tree Problem
by: Bernardelli, Ambrogio Maria, et al.
Published: (2024)

Geometric Data-Driven Dimensionality Reduction in MPC with Guarantees
by: Schurig, Roland, et al.
Published: (2023)

Multi-Objective Linear Ensembles for Robust and Sparse Training of Few-Bit Neural Networks
by: Bernardelli, Ambrogio Maria, et al.
Published: (2022)

Data-Driven Distributed Optimization via Aggregative Tracking and Deep-Learning
by: Brumali, Riccardo, et al.
Published: (2025)

An Efficient High-Dimensional Gradient Estimator for Stochastic Differential Equations
by: Wang, Shengbo, et al.
Published: (2024)

Identification of High-Dimensional ARMA Models with Binary-Valued Observations
by: Li, Xin, et al.
Published: (2024)

Deep Policy Iteration for High-Dimensional Mean Field Games
by: Assouli, Mouhcine, et al.
Published: (2023)

Conservative Linear Envelopes for Nonlinear, High-Dimensional, Hamilton-Jacobi Reachability
by: Sharpless, Will, et al.
Published: (2024)

Linear Supervision for Nonlinear, High-Dimensional Neural Control and Differential Games
by: Sharpless, William, et al.
Published: (2024)

On Characterizations of Potential and Ordinal Potential Games
by: Arefizadeh, Sina, et al.
Published: (2024)

Data-Driven LQR with Finite-Time Experiments via Extremum-Seeking Policy Iteration
by: Carnevale, Guido, et al.
Published: (2024)

Delegated portfolio management with random default
by: Gennaro, Alberto, et al.
Published: (2024)

Probabilistic Robustness in the Gap Metric
by: Renganathan, Venkatraman
Published: (2025)

Cosine-Similarity Methods for Efficient Training and Sampling in High-Dimensional Latent Spaces
by: Duan, Xu, et al.
Published: (2025)

A Neural Network Framework for High-Dimensional Dynamic Unbalanced Optimal Transport
by: Wan, Wei, et al.
Published: (2024)

Kernel Expansions for High-Dimensional Mean-Field Control with Non-local Interactions
by: Vidal, Alexander, et al.
Published: (2024)

Metric extrapolation in the Wasserstein space
by: Gallouët, Thomas O., et al.
Published: (2024)

Ranking and Selection with Simultaneous Input Data Collection
by: Wang, Yuhao, et al.
Published: (2025)

State-Augmented Linear Games with Antagonistic Error for High-Dimensional, Nonlinear Hamilton-Jacobi Reachability
by: Sharpless, Will, et al.
Published: (2024)

Symmetric Rank-$k$ Methods
by: Liu, Chengchang, et al.
Published: (2023)

Multi-Tubal Rank of Third Order Tensor and Related Low Rank Tensor Completion Problem
by: Yu, Quan, et al.
Published: (2020)

Curvature-Adaptive Perturbation and Subspace Descent for Robust Saddle Point Escape in High-Dimensional Optimization
by: Katende, Ronald, et al.
Published: (2024)

Efficient Online Prediction for High-Dimensional Time Series via Joint Tensor Tucker Decomposition
by: Luan, Zhenting, et al.
Published: (2024)

On Intensity of Preference Rank Reversal in the AHP
by: Mazurek, Jiri, et al.
Published: (2025)