Ordinal optimization
View article: Dynamic task scheduling in wireless edge computing using deep reinforcement learning with ordinal optimization
Dynamic task scheduling in wireless edge computing using deep reinforcement learning with ordinal optimization Open
In latency-critical Internet of Things (IoT) applications, multi-access edge computing (MEC) in wireless networks reduces core network strain by pushing computation and data resources to the edge. However, the limited computing power of ed…
View article: Provably Minimum-Length Conformal Prediction Sets for Ordinal Classification
Provably Minimum-Length Conformal Prediction Sets for Ordinal Classification Open
Ordinal classification has been widely applied in many high-stakes applications, e.g., medical imaging and diagnosis, where reliable uncertainty quantification (UQ) is essential for decision making. Conformal prediction (CP) is a general U…
View article: Provably Minimum-Length Conformal Prediction Sets for Ordinal Classification
Provably Minimum-Length Conformal Prediction Sets for Ordinal Classification Open
Ordinal classification has been widely applied in many high-stakes applications, e.g., medical imaging and diagnosis, where reliable uncertainty quantification (UQ) is essential for decision making. Conformal prediction (CP) is a general U…
View article: Robust Modelling of Ordinal Survey Data Using Probabilistic Programming
Robust Modelling of Ordinal Survey Data Using Probabilistic Programming Open
View article: Ordinal Analysis of Well-Ordering Principles, Well Quasi-Orders Closure Properties, and $Σ_n$-Collection Schema
Ordinal Analysis of Well-Ordering Principles, Well Quasi-Orders Closure Properties, and $Σ_n$-Collection Schema Open
The study of well quasi-orders, wqo, is a cornerstone of combinatorics and within wqo theory Kruskal's theorem plays a crucial role. Extending previous proof-theoretic results, we calculate the $Π^1_1$ ordinals of two different versions of…
View article: Ordinal Analysis of Well-Ordering Principles, Well Quasi-Orders Closure Properties, and $Σ_n$-Collection Schema
Ordinal Analysis of Well-Ordering Principles, Well Quasi-Orders Closure Properties, and $Σ_n$-Collection Schema Open
The study of well quasi-orders, wqo, is a cornerstone of combinatorics and within wqo theory Kruskal's theorem plays a crucial role. Extending previous proof-theoretic results, we calculate the $Π^1_1$ ordinals of two different versions of…
View article: Classifying Phonotrauma Severity from Vocal Fold Images with Soft Ordinal Regression
Classifying Phonotrauma Severity from Vocal Fold Images with Soft Ordinal Regression Open
Phonotrauma refers to vocal fold tissue damage resulting from exposure to forces during voicing. It occurs on a continuum from mild to severe, and treatment options can vary based on severity. Assessment of severity involves a clinician's …
View article: Classifying Phonotrauma Severity from Vocal Fold Images with Soft Ordinal Regression
Classifying Phonotrauma Severity from Vocal Fold Images with Soft Ordinal Regression Open
Phonotrauma refers to vocal fold tissue damage resulting from exposure to forces during voicing. It occurs on a continuum from mild to severe, and treatment options can vary based on severity. Assessment of severity involves a clinician's …
View article: An Optimized Deep Learning-Based Smart Parking Mechanism for Smart City Environment
An Optimized Deep Learning-Based Smart Parking Mechanism for Smart City Environment Open
In the recent past, identifying a parking spot at the appropriate time and place has become increasingly crucial around the globe due to the ever-increasing parking demands introduced by vehicles. At this juncture, the process involved in …
View article: Selecting a Good Stochastic Inventory Policy for the Huge Number of Alternative Policies
Selecting a Good Stochastic Inventory Policy for the Huge Number of Alternative Policies Open
In this paper, we present the problem of selecting a good stochastic inventory policy with high probability and minimum total simulation cost when the number of alterna- tive policies is huge. We start with the Ordinal Optimization (OO) pr…
View article: Inference for the proportional odds cumulative logit model with monotonicity constraints for ordinal predictors and ordinal response
Inference for the proportional odds cumulative logit model with monotonicity constraints for ordinal predictors and ordinal response Open
View article: Ordinal Simplicity in Discrete Mechanism Design
Ordinal Simplicity in Discrete Mechanism Design Open
In environments without transfers, market designers usually restrict attention to ordinal mechanisms. Ordinal mechanisms are simpler but miss potentially welfare‐relevant information. Under what conditions is it without loss to focus on or…
View article: Exact likelihood-based evidential prediction of an ordinal variable
Exact likelihood-based evidential prediction of an ordinal variable Open
View article: From ordinal ordering to a prior probability
From ordinal ordering to a prior probability Open
Billot et al. (Econometrica 73:1125–1136, 2005) (BGSS) propose a model for constructing a prior probability over states of nature based on past data. According to their model, the evaluator possesses a similarity function over observations…
View article: Fuzzy Ordinal Decision‐Making Method: A New Multi‐Criteria Decision‐Making With Application to Circular Evaluation of Construction Projects
Fuzzy Ordinal Decision‐Making Method: A New Multi‐Criteria Decision‐Making With Application to Circular Evaluation of Construction Projects Open
Approaches that rely on pairwise comparisons frequently encounter challenges related to inconsistency and uncertainty in the complex realm of multi‐criteria decision‐making (MCDM), resulting in potential decision‐making errors. This articl…
View article: Exploiting Structured Global and Neighbor Orders for Enhanced Ordinal Regression
Exploiting Structured Global and Neighbor Orders for Enhanced Ordinal Regression Open
Ordinal regression combines classification and regression techniques, constrained by the intrinsic order among categories. It has wide-ranging applications in real-world scenarios, such as product quality grading, medical diagnoses, and fa…
View article: XL-DURel: Finetuning Sentence Transformers for Ordinal Word-in-Context Classification
XL-DURel: Finetuning Sentence Transformers for Ordinal Word-in-Context Classification Open
We propose XL-DURel, a finetuned, multilingual Sentence Transformer model optimized for ordinal Word-in-Context classification. We test several loss functions for regression and ranking tasks managing to outperform previous models on ordin…
View article: Analytical Ordinal Priority Approach
Analytical Ordinal Priority Approach Open
The study proposes an analytical (closed-form) solution to the Ordinal Priority Approach (OPA) in multiple attribute decision-making. The proposed Analytical Ordinal Priority Approach (AOPA) can calculate the weights of alternatives, crite…
View article: A Comprehensive Overview of Ordinal Regression in Statistical Modeling
A Comprehensive Overview of Ordinal Regression in Statistical Modeling Open
Ordinal regression or ordinal logistic regression is a statistical technique that makes predictions about an ordinal dependent variable with one or more independent variables. This technique is an extension of both multiple linear and bina…
View article: Risk factors associated with health literacy among community residents in China based on multiple correspondence analysis and ordinal logistic regression
Risk factors associated with health literacy among community residents in China based on multiple correspondence analysis and ordinal logistic regression Open
View article: ORNet: No-reference Point Cloud Quality Assessment in an Ordinal Regression Way
ORNet: No-reference Point Cloud Quality Assessment in an Ordinal Regression Way Open
No-reference Point Cloud Quality Assessment (NR-PCQA) is pivotal for automatically evaluating the perceptual visual quality of point clouds, with the goal of accurately aligning model predictions with ground-truth human subjective ratings.…
View article: Signposts on the Path from Nominal to Ordinal Scales
Signposts on the Path from Nominal to Ordinal Scales Open
Polytomous item response data are typically classified as either nominal or ordinal, but this binary distinction may oversimplify their true structure. In this paper, we reframe the nominal–ordinal distinction as a continuum and introduce …
View article: Ordinal regression meets online learning: Interactive preference learning for multiple criteria choice and ranking with provable guarantees
Ordinal regression meets online learning: Interactive preference learning for multiple criteria choice and ranking with provable guarantees Open
View article: Ordinal Random Processes
Ordinal Random Processes Open
Ordinal patterns have proven to be a valuable tool in many fields. Here, we address the need for theoretical models. A paradigmatic example shows that a model for frequencies of ordinal patterns can be determined without any numerical valu…
View article: Comparative Evaluation of Statistical Methods for Detecting Rater Bias in Ordinal Categorical Data
Comparative Evaluation of Statistical Methods for Detecting Rater Bias in Ordinal Categorical Data Open
Aims: This study seeks to examine four statistical methods Modified McNemar Test, Single Binomial Test, Marginal Homogeneity Test, and Bias Index for identifying bias between two raters utilizing ordinal categorical data. Study Design: Thi…
View article: Uncertainty quantification in ordinal classification: A comparison of measures
Uncertainty quantification in ordinal classification: A comparison of measures Open
Uncertainty quantification has received increasing attention in machine learning in the recent past, but the focus has mostly been on standard (nominal) classification and regression so far. In this paper, we address the question of how to…
View article: Supervised Contrastive Learning for Ordinal Engagement Measurement
Supervised Contrastive Learning for Ordinal Engagement Measurement Open
View article: When the Mean is Misleading: A Guide to Ordered Regression for Meaningfully Modeling Ordinal Outcomes
When the Mean is Misleading: A Guide to Ordered Regression for Meaningfully Modeling Ordinal Outcomes Open
Objectives: To demonstrate the utility of ordered regression models for analyzing ordinal outcomes frequently encountered in criminology, comparing their performance in representing data patterns and estimating effect magnitudes against co…
View article: Modeling Uncertainty in Ordinal Regression: The Uncertainty Rating Scale Model
Modeling Uncertainty in Ordinal Regression: The Uncertainty Rating Scale Model Open
In questionnaires, respondents sometimes feel uncertain about which category to choose and may respond randomly. Including uncertainty in the modeling of response behavior aims to obtain more accurate estimates of the impact of explanatory…
View article: Should we estimate plant cover in percent or on ordinal scales? II – Diversity indices
Should we estimate plant cover in percent or on ordinal scales? II – Diversity indices Open
Question : We asked whether ordinal cover scales cause biases in biodiversity indices derived from vegetation plots and, if so, whether a different back-translation of ordinal categories could improve the situation. Methods : We took three…