惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

T
Tailwind CSS Blog
人人都是产品经理
人人都是产品经理
博客园 - 叶小钗
大猫的无限游戏
大猫的无限游戏
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
博客园 - 【当耐特】
The Cloudflare Blog
博客园 - 聂微东
博客园 - 司徒正美
量子位
博客园 - 三生石上(FineUI控件)
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
G
Google Developers Blog
Apple Machine Learning Research
Apple Machine Learning Research
罗磊的独立博客
酷 壳 – CoolShell
酷 壳 – CoolShell
Y
Y Combinator Blog
S
SegmentFault 最新的问题
T
The Blog of Author Tim Ferriss
P
Proofpoint News Feed
Google DeepMind News
Google DeepMind News
Blog — PlanetScale
Blog — PlanetScale
有赞技术团队
有赞技术团队
A
About on SuperTechFans

cs.DC updates on arXiv.org

DUAL-BLADE: Dual-Path NVMe-Direct KV-Cache Offloading for Edge LLM Inference Progressive Semantic Communication for Efficient Edge-Cloud Vision-Language Models Efficient, VRAM-Constrained xLM Inference on Clients Folding Tensor and Sequence Parallelism for Memory-Efficient Transformer Training & Inference DORA: A Scalable Asynchronous Reinforcement Learning System for Language Model Training AMMA: A Multi-Chiplet Memory-Centric Architecture for Low-Latency 1M Context Attention Serving RaMP: Runtime-Aware Megakernel Polymorphism for Mixture-of-Experts Spark Policy Toolkit: Semantic Contracts and Scalable Execution for Policy Learning in Spark Internet of Everything in the 6G Era: Paradigms, Enablers, Potentials and Future Directions PolyKV: A Shared Asymmetrically-Compressed KV Cache Pool for Multi-Agent LLM Inference A Survey on Split Learning for LLM Fine-Tuning: Models, Systems, and Privacy Optimizations ITAS: A Multi-Agent Architecture for LLM-Based Intelligent Tutoring Latency and Cost of Multi-Agent Intelligent Tutoring at Scale TACO: Efficient Communication Compression of Intermediate Tensors for Scalable Tensor-Parallel LLM Training FreeScale: Distributed Training for Sequence Recommendation Models with Minimal Scaling Cost CommFuse: Hiding Tail Latency via Communication Decomposition and Fusion for Distributed LLM Training A Taxonomy and Resolution Strategy for Client-Level Disagreements in Federated Learning Usable Agent Discovery for Decentralized AI Systems Cloud to Edge: Benchmarking LLM Inference On Hardware-Accelerated Single-Board Computers Data-Free Contribution Estimation in Federated Learning using Gradient von Neumann Entropy Shard the Gradient, Scale the Model: Serverless Federated Aggregation via Gradient Partitioning Promoting Simple Agents: Ensemble Methods for Event-Log Prediction GraphLeap: Decoupling Graph Construction and Convolution for Vision GNN Acceleration on FPGA AGNT2: Autonomous Agent Economies on Interaction-Optimized Layer 2 Infrastructure FedSIR: Spectral Client Identification and Relabeling for Federated Learning with Noisy Labels Stream-CQSA: Avoiding Out-of-Memory in Attention Computation via Flexible Workload Scheduling A Delta-Aware Orchestration Framework for Scalable Multi-Agent Edge Computing Federated Learning over Blockchain-Enabled Cloud Infrastructure Optimal Routing for Federated Learning over Dynamic Satellite Networks: Tractable or Not? Sherpa.ai Privacy-Preserving Multi-Party Entity Alignment without Intersection Disclosure for Noisy Identifiers
Wearable Internet of Things for Personalized Healthcare S...
Samiya Khan, Mansaf Alam · 2020-04-20 · via cs.DC updates on arXiv.org

In this age of heterogeneous systems, diverse technologies are integrated to create application-specific solutions. The recent upsurge in acceptance of technologies such as cloud computing and ubiquitous Internet has cleared the path for Internet of Things (IoT). Moreover, the increasing Internet penetration with the rising use of mobile devices has inspired an era of technology that allows interfacing of physical objects and connecting them to Internet for developing applications serving a wide range of purposes. Recent developments in the area of wearable devices has led to the creation of another segment in IoT, which can be conveniently referred to as Wearable Internet of Things (WIoT). Research in this area promises to personalize healthcare in previously unimaginable ways by allowing individual tracking of wellness and health information. This chapter shall cover the different facets of Wearable Internet of Things (WIoT) and ways in which it is a key driving technology behind the concept of personalized healthcare. It shall discuss the theoretical aspects of WIoT, focusing on functionality, design and applicability. Moreover, it shall also elaborate on the role of wearable sensors, big data and cloud computing as enabling technologies for WIoT.