Accurately classifying heart sound signals is crucial for the detection and diagnosis of cardiovascular diseases. Due to the inherent complexity of heart sounds and variations among subjects, capturing the latent high...
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Dataset Distillation (DD) is a technique for synthesizing smaller, compressed datasets from large original datasets while retaining essential information to maintain efficacy. Efficient DD is a current research focus ...
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ISBN:
(纸本)9798400704369
Dataset Distillation (DD) is a technique for synthesizing smaller, compressed datasets from large original datasets while retaining essential information to maintain efficacy. Efficient DD is a current research focus among scholars. Squeeze, Recover and Relabel ((SReL)-L-2) and Adversarial Prediction Matching (APM) are two advanced and efficient DD methods, yet their performance is moderate with lower volumes of distilled data. This paper proposes an ingenious improvement method, distributed Boosting (DB), capable of significantly enhancing the performance of these two algorithms at low distillation volumes, leading to DB-(SReL)-L-2 and DB-APM. Specifically, DB is divided into three stages: Distribute&Encapsulate, Distill, and Integrate&Mix-relabel. DB-(SReL)-L-2, compared to (SReL)-L-2, demonstrates performance improvements of 25.2%, 26.9%, and 26.2% on full 224x224 ImageNet-1k at Images Per Class (IPC) 10, CIFAR-10 at IPC 10, and CIFAR-10 at IPC 50, respectively. Meanwhile, DB-APM, in comparison to APM, exhibits performance enhancements of 21.2% and 20.9% on CIFAR-10 at IPC 10, CIFAR-100 at IPC 1, respectively. Additionally, we provide a theoretical proof of convergence for DB. To the best of our knowledge, DB is the first method suitable for distributedparallel computing scenarios.
This article examines directions and mechanisms for increasing data reliability in computer networks. Currently, the rapid development of information technologies, the rapid growth of data flow, high-quality data proc...
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With the increasing need for safeguarding confidential and secure healthcare information, Blockchain has become a pioneering approach to managing medical data due to its decentralized structure, resistance to tamperin...
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Infants communicate their emotional needs through speech, which contains rich emotional information. In view of the fact that there is no publicly available infant speech emotion data set and the accuracy of existing ...
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The proceedings contain 17 papers. The topics discussed include: portable implementations of work stealing;sKokkos: enabling Kokkos with transparent device selection on heterogeneous systems using OpenACC;parallelized...
ISBN:
(纸本)9798400708893
The proceedings contain 17 papers. The topics discussed include: portable implementations of work stealing;sKokkos: enabling Kokkos with transparent device selection on heterogeneous systems using OpenACC;parallelized remapping algorithms for km-scale global weather and climate simulations with icosahedral grid system;approximate block diagonalization of symmetric matrices using quantum annealing;QUBO formulation using inequalities for problems with complex constraints;low-latency communication in RISC-V clusters;flexible systolic array platform on virtual 2-D multi-FPGA plane;an efficient task-parallel pipeline programming framework;and task-based low-rank hybrid parallel Cholesky factorization for distributed memory environment.
With the rapid development of information technology, distributed database systems play an important role in large-scale data processing and storage. However, along with it, there is an increasing concern about data s...
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The proceedings contain 28 papers. The topics discussed include: performance and usability implications of multiplatform and WebAssembly containers;operations patterns for hybrid quantum applications;optimization of c...
ISBN:
(纸本)9789897587474
The proceedings contain 28 papers. The topics discussed include: performance and usability implications of multiplatform and WebAssembly containers;operations patterns for hybrid quantum applications;optimization of cloud-native application execution over the edge cloud continuum enabled by DVFS;energy-aware node selection for cloud-based parallel workloads with machine learning and infrastructure as code;security-aware allocation of replicated data in distributed storage systems;performance analysis of mdx ii: a next-generation cloud platform for cross-disciplinary data science research;data orchestration platform for AI workflows execution across computing continuum;framework for decentralized data strategies in virtual banking: navigating scalability, innovation, and regulatory challenges in Thailand;and anomaly detection for partially observable container systems based on architecture profiling.
This paper proposes a new method for the efficiency optimization control of the distributed interleaved parallel power supply systems (DIPPS). The proposed method uses a fuzzy logic controller (FLC) to dynamically adj...
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Container technology has become a cornerstone of cloud computing, offering notable benefits such as enhanced resource utilization and streamlined deployment processes. The adoption of container technology by leading c...
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