Papers Capacity Estimation
“Capacity Estimation” 태그가 달린 논문 33편 · 필터 해제
Code Rate Optimization via Neural Polar Decoders
This paper proposes a method to optimize communication code rates via the application of neural polar decoders (NPDs). Employing this approach enables simultaneous optimization of code rates over input distributions whil…
Capacity EstimationMeet Me at the Arm: The Cooperative Multi-Armed Bandits Problem with Shareable Arms
We study the decentralized multi-player multi-armed bandits (MMAB) problem under a no-sensing setting, where each player receives only their own reward and obtains no information about collisions. Each arm has an unknown…
Capacity EstimationMulti-Armed BanditsSEAL: Searching Expandable Architectures for Incremental Learning
Incremental learning is a machine learning paradigm where a model learns from a sequential stream of tasks. This setting poses a key challenge: balancing plasticity (learning new tasks) and stability (preserving past kno…
AutoMLCapacity EstimationIncremental LearningNeural Architecture SearchA Practitioner's Guide to Automatic Kernel Search for Gaussian Processes in Battery Applications
Gaussian process (GP) models have been used in a wide range of battery applications, in which different kernels were manually selected with considerable expertise. However, to capture complex relationships in the ever-gr…
Capacity EstimationGaussian ProcessesModel SelectionEnhanced Battery Capacity Estimation in Data-Limited Scenarios through Swarm Learning
Data-driven methods have shown potential in electric-vehicle battery management tasks such as capacity estimation, but their deployment is bottlenecked by poor performance in data-limited scenarios. Sharing battery data …
Capacity EstimationManagementDomain knowledge-guided machine learning framework for state of health estimation in Lithium-ion batteries
Accurate estimation of battery state of health is crucial for effective electric vehicle battery management. Here, we propose five health indicators that can be extracted online from real-world electric vehicle operation…
Capacity EstimationManagementFast Capacity Estimation in Ultra-dense Wireless Networks with Random Interference
In wireless communication systems, the accurate and reliable evaluation of channel capacity is believed to be a fundamental and critical issue for terminals. However, with the rapid development of wireless technology, la…
Capacity EstimationAn Unsupervised Machine Learning to Optimize Hybrid Quantum Noise Clusters for Gaussian Quantum Channel
This work focuses on optimizing the hybrid quantum noise model to improve the capacity of Gaussian quantum channels using Machine Learning (ML) generated clusters. The work specifically leverages Gaussian Mixture Model (…
Capacity EstimationBridge the Modality and Capability Gaps in Vision-Language Model Selection
Vision Language Models (VLMs) excel in zero-shot image classification by pairing images with textual category names. The expanding variety of Pre-Trained VLMs enhances the likelihood of identifying a suitable VLM for spe…
Capacity Estimationimage-classificationImage ClassificationLanguage Modeling+3Enhancing Continuous Domain Adaptation with Multi-Path Transfer Curriculum
Addressing the large distribution gap between training and testing data has long been a challenge in machine learning, giving rise to fields such as transfer learning and domain adaptation. Recently, Continuous Domain Ad…
Capacity EstimationDomain Adaptationimage-classificationImage Classification+2Implementing hosting capacity analysis in distribution networks: Practical considerations, advancements and future directions
Hosting capacity analysis is essential for effective integration of distributed energy resources into distribution systems. This paper discusses hosting capacity analysis with emphasis on various aspects affecting the pr…
BenchmarkingCapacity EstimationUncertainty QuantificationPerformance Analysis of Empirical Open-Circuit Voltage Modeling in Lithium Ion Batteries, Part-1: Performance Measures
The open circuit voltage to the state of charge (OCVSOC) characteristic is crucial for battery management systems. Using the OCV-SOC curve, the SOC and the battery capacity can be estimated in real-time. Accurate SOC and…
Capacity EstimationManagementEmpirical Assessment of End-to-End Iris Recognition System Capacity
Iris is an established modality in biometric recognition applications including consumer electronics, e-commerce, border security, forensics, and de-duplication of identity at a national scale. In light of the expanding …
Capacity EstimationIris RecognitionTOSE: A Fast Capacity Estimation Algorithm Based on Spike Approximations
Capacity is one of the most important performance metrics for wireless communication networks. It describes the maximum rate at which the information can be transmitted of a wireless communication system. To support the …
Capacity EstimationA Perspective on Neural Capacity Estimation: Viability and Reliability
Recently, several methods have been proposed for estimating the mutual information from sample data using deep neural networks. These estimators ar referred to as neural mutual information estimation (NMIE)s. NMIEs diffe…
BenchmarkingCapacity EstimationMutual Information EstimationFalse Data Injection Attack on Electric Vehicle-Assisted Voltage Regulation
With the large scale penetration of electric vehicles (EVs) and the advent of bidirectional chargers, EV aggregators will become a major player in the voltage regulation market. This paper proposes a novel false data inj…
Capacity EstimationStochastic OptimizationAttention-based Deep Neural Networks for Battery Discharge Capacity Forecasting
Battery discharge capacity forecasting is critically essential for the applications of lithium-ion batteries. The capacity degeneration can be treated as the memory of the initial battery state of charge from the data po…
Capacity EstimationManagementEVBattery: A Large-Scale Electric Vehicle Dataset for Battery Health and Capacity Estimation
Electric vehicles (EVs) play an important role in reducing carbon emissions. As EV adoption accelerates, safety issues caused by EV batteries have become an important research topic. In order to benchmark and develop dat…
Anomaly DetectionCapacity EstimationOutlier DetectionNeural Capacity Estimators: How Reliable Are They?
Recently, several methods have been proposed for estimating the mutual information from sample data using deep neural networks and without the knowing closed form distribution of the data. This class of estimators is ref…
Capacity EstimationEstimating Total Lung Volume from Pixel-level Thickness Maps of Chest Radiographs Using Deep Learning
Purpose: To estimate the total lung volume (TLV) from real and synthetic frontal chest radiographs (CXR) on a pixel level using lung thickness maps generated by a U-Net deep learning model. Methods: This retrospective st…
Capacity EstimationPulmonary Embolism Detection