Results 11 to 20 of about 55,996 (318)
Dynamic task scheduling in wireless edge computing using deep reinforcement learning with ordinal optimization [PDF]
EURASIP Journal on Wireless Communications and NetworkingIn 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.
Yongyu Wang, Siqi Sun
doaj +2 more sources
Constraint ordinal optimization
Information Sciences, 2002 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Li, D., Lee, L.H., Ho, Y.C.
openaire +3 more sources
Prediction of sentiment polarity in restaurant reviews using an ordinal regression approach based on evolutionary XGBoost [PDF]
PeerJ Computer ScienceAs the business world shifts to the web and tremendous amounts of data become available on multilingual mobile applications, new business and research challenges and opportunities have been explored.
Dana A. Al-Qudah +5 more
doaj +3 more sources
Correction to “Immunogenic Nanovesicle‐Tandem‐Augmented Chemoimmunotherapy via Efficient Cancer‐Homing Delivery and Optimized Ordinal‐Interval Regime” [PDF]
Advanced Science, EarlyView.
openalex +2 more sources
Online Ordinal Optimization under Model Misspecification
SSRN Electronic Journal, 2021 We consider an ordinal optimization problem, where a decision maker learns the statistical characteristics of a number of systems using sequential sampling in order to ultimately determine the "best" one (with high probability). In so doing, the decision maker postulates a parametric model which may not precisely represent the true underlying system ...
Dohyun Ahn, Dongwook Shin, Assaf Zeevi
openaire +2 more sources
Mean-Variance Portfolio Optimization Based on Ordinal Information
SSRN Electronic Journal, 2019 We propose a new approach that allows for incorporating qualitative views, such as ordering information, into estimates of future asset returns within the Black-Litterman model. We develop a mathematical framework and numerical computation methods for this setting.
Eranda Çela +3 more
openaire +2 more sources
Mathematics, 2023 Simulation optimization problems with stochastic constraints are optimization problems with deterministic cost functions subject to stochastic constraints.
Shih-Cheng Horng, Shieh-Shing Lin
doaj +1 more source
Quasi-Unimodal Distributions for Ordinal Classification
Mathematics, 2022 Ordinal classification tasks are present in a large number of different domains. However, common losses for deep neural networks, such as cross-entropy, do not properly weight the relative ordering between classes.
Tomé Albuquerque +2 more
doaj +1 more source
Distributed Ordinal Regression Over Networks
IEEE Access, 2021 Many real-world data are labeled with natural orders, i.e., ordinal labels. Examples can be found in a wide variety of fields. Ordinal regression is a problem to predict ordinal labels for given patterns.
Huan Liu, Jiankai Tu, Chunguang Li
doaj +1 more source
Ordinal optimization through multi-objective reformulation
European Journal of Operational Research, 2023 We analyze combinatorial optimization problems with ordinal, i.e., non-additive, objective functions that assign categories (like good, medium and bad) rather than cost coefficients to the elements of feasible solutions. We review different optimality concepts for ordinal optimization problems and discuss their similarities and differences.
Kathrin Klamroth +2 more
openaire +2 more sources