Pansharpening Techniques: Optimizing the Loss Function for Convolutional Neural Networks by Rocco Restaino

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Enhancing cross entropy with a linearly adaptive loss function for optimized classification performance by Jae Wan Shim

“…Abstract We propose the linearly adaptive cross entropy loss function. This is a novel measure derived from the information theory. …”
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Integrating Recurrent Neural Networks and Loss Function Optimization for Efficient Indoor Camera Positioning by Shamsul Alam, Farhan Mohamed, Bellal Hossain

“…RNNs enable the system to generate accurate estimations based on previous information by extracting temporal dependencies and patterns from the camera information. We optimized the loss function to enhance the indoor camera position's overall performance and convergence speed. …”
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Reinforcement Learning-Based Formulations With Hamiltonian-Inspired Loss Functions for Combinatorial Optimization Over Graphs by Redwan Ahmed Rizvee, Raheeb Hassan, Md. Mosaddek Khan

“…The transformation of QUBO to an Ising Hamiltonian is recognized as an effective method for solving key optimization problems using quantum algorithms. Recently, PI-GNN, a generic framework, has been proposed to address CO problems over graphs based on QUBO with Hamiltonian loss function to train the underlying GNN architecture. …”
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Residential real estate price prediction based on adaptive loss function and feature embedding optimization by Hongqin Zhang

“…To align with the dynamic nature of the real estate market, we propose a real estate price prediction model that leverages an adaptive loss function and optimizes feature embedding. Initially, we utilize diverse real estate factors to develop a representation method for real estate prices, rooted in feature embedding optimization, to thoroughly examine the interconnections among these factors. …”
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Research on optimization of maintenance strategy for power grid equipment considering the function-economic correlation by QI Weiwen, YE Lin, CHEN Jianguo, ZHOU Zhengyang

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A Surrogate Piecewise Linear Loss Function for Contextual Stochastic Linear Programs in Transport by Qi Hong, Mo Jia, Xuecheng Tian, Zhiyuan Liu, Shuaian Wang

Subjects: “…piecewise linear loss function…”
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Optimal Control Problems for Erlang Loss Systems by Mario Lefebvre

“…The dynamic programming equation satisfied by the value function <i>F</i>, from which the optimal control follows at once, is derived, and <i>F</i> is found explicitly when <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>s</mi><mo>=</mo><mn>2</mn></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>s</mi><mo>=</mo><mn>3</mn></mrow></semantics></math></inline-formula>. …”
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Research on Wood Defects Feature Imbalance Optimization and Recognition by Xiao Wang

“…Besides, generalization ability test indicates that new methods allow the classifier to have comparable accuracies on five additional datasets. The proposed loss functions improve the model performance through optimizing the model training process, providing a new idea for deep learning application in wood defects detection.…”
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Deep Learning Design for Loss Optimization in Metamaterials by Xianfeng Wu, Jing Zhao, Kunlun Xie, Xiaopeng Zhao

“…The paper presents an innovative strategy for loss optimization in metamaterials with disordered structural unit distributions, proving their robustness and ability to perform intended functions within a critical distribution ratio. …”
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Deep Learning Algorithm for Optimized Sensor Data Fusion in Fault Diagnosis and Tolerance by M. Elhoseny, Deepak Dasaratha Rao, Bala Dhandayuthapani Veerasamy, Noha Alduaiji, J. Shreyas, Piyush Kumar Shukla

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Towards solving NLP tasks with optimal transport loss by Rishabh Bhardwaj, Tushar Vaidya, Soujanya Poria

“…Incorporating such information in the computations of the probability divergence can facilitate the model’s learning dynamics.In this work, we study an under-explored loss function in NLP — Wasserstein Optimal Transport (OT) — which takes label coordinates into account and thus allows the learning algorithm to incorporate inter-label relations. …”
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TOPSIS vs Quality Loss Function Multi-Criteria Optimization of   Mechanical Performance in Laser Spot Welding Process by Ruba Khalil, Bassim Bachy

“…An orthogonal L9 array with three levels was used. Multi-objective optimization techniques TOPSIS-Quality Loss Function were used, and the results were compared. …”
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Optimized Allocation of Flood Control Emergency Materials Based on Loss Quantification by Wei Wang, Yunqing Wang, Li Huang, Yue Song

“…ABSTRACT Reserve management of emergency materials for flood control is the basis for the smooth development of flood control emergency work. To optimize the allocation of flood control emergency materials in each emergency node warehouse, a multiobjective optimization model is constructed from the perspective of multiwarehouse collaborative reservation with the shortest transportation time, the lowest storage and transportation costs, and the minimum out‐of‐stock loss. …”
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Pareto Local Search Function for Optimal Placement of DG and Capacitors Banks in Distribution Systems by Abdolreza Sadighmanesh, Mehran Sabahi, Mahdi Zavvari

“…To limit the search space and find Pareto points, a new combination method including Pareto chart and a weight function has been used. The optimal operation of the distribution network is performed by three single objective functions related to the voltage stability index, voltage profile of buses and power loss. …”
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The dual-edged potential of AI autonomously defining loss functions by Abbas Ghori

Subjects: “…AI-defined loss functions…”
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Optimal excess of loss reinsurance-barrier dividend strategies with investment by SUN Zongqi, YANG Peng, WU Jing, YANG Yang

“…The optimal barrier dividend problem under excess of loss reinsurance strategy has rarely been studied so far. …”
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Multiobjective Optimization of SWISS Rectifier by YAN Jingbin, SHEN Yunsen, LIU Si, WEI Jinxin, GAO Chongxi

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Application of Optimal Network Reconfiguration for Loss Minimization and Voltage Profile Enhancement of Distribution System Using Heap-Based Optimizer by Duku Otuo-Acheampong, Ghamgeen Izat Rashed, Amoh Mensah Akwasi, Hussain Haider

“…A distribution system’s network reconfiguration (NR) is the process of changing the status of the switches to change the topology of the feeders. Using optimal NR at various network load levels, this research proposed an economical way for improving the voltage profile and reducing power loss in distribution systems. …”
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Beyond Standard Losses: Redefining Text-to-SQL with Task-Specific Optimization by Iker Azurmendi, Ekaitz Zulueta, Gustavo García, Nekane Uriarte-Arrazola, Jose Manuel Lopez-Guede

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