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Showing 1476–1500 of 2231 papers

TitleStatusHype
A Late Multi-Modal Fusion Model for Detecting Hybrid Spam E-mail—0
A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining—0
ALERT: Accurate Learning for Energy and Timeliness—0
Algorithm to Compilation Co-design: An Integrated View of Neural Network Sparsity—0
A Lightweight Moving Target Defense Framework for Multi-purpose Malware Affecting IoT Devices—0
ALISA: Accelerating Large Language Model Inference via Sparsity-Aware KV Caching—0
ALO-VC: Any-to-any Low-latency One-shot Voice Conversion—0
A Low-Cost, High-Speed, and Robust Bin Picking System for Factory Automation Enabled by a Non-Stop, Multi-View, and Active Vision Scheme—0
A matrix-free approach to parallel and memory-efficient deformable image registration—0
A Microprocessor implemented in 65nm CMOS with Configurable and Bit-scalable Accelerator for Programmable In-memory Computing—0
AMPLE: Event-Driven Accelerator for Mixed-Precision Inference of Graph Neural Networks—0
A Multi-Agent System Approach to Load-Balancing and Resource Allocation for Distributed Computing—0
An Adaptive Device-Edge Co-Inference Framework Based on Soft Actor-Critic—0
Analog CMOS-based Resistive Processing Unit for Deep Neural Network Training—0
Analytically-Driven Resource Management for Cloud-Native Microservices—0
Analyzing and Mitigating Data Stalls in DNN Training—0
Analyzing CNN Based Behavioural Malware Detection Techniques on Cloud IaaS—0
Analyzing In-browser Cryptojacking—0
Analyzing Machine Learning Performance in a Hybrid Quantum Computing and HPC Environment—0
An Automatic and Efficient BERT Pruning for Edge AI Systems—0
An Edge AI System Based on FPGA Platform for Railway Fault Detection—0
An Efficient Active Set Algorithm for Covariance Based Joint Data and Activity Detection for Massive Random Access with Massive MIMO—0
An Efficient and Streaming Audio Visual Active Speaker Detection System—0
An Efficient FPGA-based Accelerator for Deep Forest—0
An Efficient Mixture of Deep and Machine Learning Models for COVID-19 and Tuberculosis Detection Using X-Ray Images in Resource Limited Settings—0
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