Though successful, federated learning (FL) presents new challenges for machine learning, especially when the issue of data heterogeneity, also known as Non-IID data, arises. To cope with the statistical heterogeneity,...
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Though successful, federated learning (FL) presents new challenges for machine learning, especially when the issue of data heterogeneity, also known as Non-IID data, arises. To cope with the statistical heterogeneity, previous works incorporated a proximal term in local optimization or modified the model aggregation scheme at the server side or advocated clustered federated learning approaches, where the central server groups agent population into clusters with jointly trainable data distributions to take the advantage of a certain level of personalization. While effective, they lack a deep elaboration on what kind of data heterogeneity and how the data heterogeneity impacts the accuracy performance of the participating clients. In contrast to many of the prior FL approaches,wedemonstrate not only the issue of data heterogeneity in current setups is not necessarily a problem but also in fact it can be beneficial for *** are intuitive: 1) Dissimilar labels of clients (label skew) are not necessarily considered data heterogeneity, and 2) the principal angle between the clients' data subspaces spanned by their corresponding principal vectors of data is a better estimate of the data heterogeneity. Impact Statement-FL is becoming a compelling learning paradigm in the artificial intelligence (AI) area. However, FL suffers from a notorious issue which is the existence of statistical Non-IID data across different distributed clients. Due to diverse participants, severe data heterogeneity can be present in different clients data, which has been demonstrated to result in unstable and slow convergence. For instance, training a global model across hospitals to identify brain/cancer tumors where every hospitals? images come froma different domain/distribution. To simulate this statistical data heterogeneity, data heterogeneity has been simply modeled as Non-IID label skewwhich tends to be a rigid data partitioning and is hardly representative and th
The Interior permanent-magnet synchronous motor (IPMSM) is widely used in servo motors due to its high-power density and excellent dynamic performance. However, the high cogging torque and torque ripple reduce the con...
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Complex physical and chemical reactions during CO2sequestration alter the microscopic pore structure of geological formations,impacting sequestration *** investigate CO2sequestration dynamics,comprehensive physical si...
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Complex physical and chemical reactions during CO2sequestration alter the microscopic pore structure of geological formations,impacting sequestration *** investigate CO2sequestration dynamics,comprehensive physical simulation experiments were conducted under varied pressures,coupled with assessments of changes in mineral composition,ion concentrations,pore morphology,permeability,and sequestration capacity before and after ***,a method using NMR T2spectra changes to measure pore volume shift and estimate CO2sequestration is *** quantifies CO2needed for mineralization of soluble ***,when CO2dissolves in crude oil,the precipitation of asphaltene compounds impairs both seepage and storage ***,the impact of dissolution and precipitation is closely associated with storage pressure,with a particularly pronounced influence on smaller *** pressure levels rise,the magnitude of pore alterations progressively *** a pressure threshold of 25 MPa,the rate of change in small pores due to dissolution reaches a maximum of 39.14%,while precipitation results in a change rate of-58.05% for small *** observed formation of dissolution pores and micro-cracks during dissolution,coupled with asphaltene precipitation,provides crucial insights for establishing CO2sequestration parameters and optimizing strategies in low permeability reservoirs.
The high power DC-DC converters are widely used in industrial and renewable application due to variable dc source. For this purpose, the interleaved dual cascade DCDC converter (IDCC) is the most advantageous due to i...
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The "pre-training then fine-tuning (FT)" paradigm is widely adopted to boost the model performance of deep learning-based methods for medical volumetric segmentation. However, conventional full FT incurs hig...
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One of the biggest hurdles in microLED-technology is the efficiency degradation with shrinking pixel-size, due to etching damage. We present the scaling of µLED from 45 to 5 µm by MacEtch, with near size-ind...
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One of the biggest hurdles in microLED-technology is the efficiency degradation with shrinking pixel-size, due to etching damage. We present the scaling of µLED from 45 to 5 µm by MacEtch, with near size-ind...
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Quantum dot light-emitting diodes (QLEDs) have garnered significant attention due to their outstanding optical and electrical properties. Furthermore, there have been many attempts to fabricate QLEDs on the flexible s...
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We prepared oxide semiconductor-based ferroelectric thin-film transistors (FeTFTs) with a floating gate for memory application. Depositing oxide semiconductor on HfZrOx (HZO) as a floating gate successfully induced a ...
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Urban traffic congestion during morning rush hour is a source of severe discomfort for commuters. Some commuters must make an intermediate stop at a school to drop off their children before heading to their destinatio...
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