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Collaborative Inference

In collaborative inference, a single inference task is performed by multiple models distributed on two or more (typically resource-constrained IoT) devices

Papers

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Showing 51–68 of 68 papers

TitleStatusHype
Fault-Tolerant Collaborative Inference through the Edge-PRUNE Framework—0
Decentralized Low-Latency Collaborative Inference via Ensembles on the EdgeCode0
Multi-Agent Collaborative Inference via DNN Decoupling: Intermediate Feature Compression and Edge LearningCode1
C-NMT: A Collaborative Inference Framework for Neural Machine Translation—0
An Approach to Inference-Driven Dialogue Management within a Social Chatbot—0
SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation LearningCode1
Security Analysis of Capsule Network Inference using Horizontal Collaboration—0
EARLIN: Early Out-of-Distribution Detection for Resource-efficient Collaborative Inference—0
Energy-Efficient Model Compression and Splitting for Collaborative Inference Over Time-Varying Channels—0
Communication-Efficient Split Learning Based on Analog Communication and Over the Air Aggregation—0
PRICURE: Privacy-Preserving Collaborative Inference in a Multi-Party SettingCode0
SPINN: Synergistic Progressive Inference of Neural Networks over Device and Cloud—0
Collaborative Inference for Efficient Remote Monitoring—0
Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing—0
Auto-tuning Neural Network Quantization Framework for Collaborative Inference Between the Cloud and Edge—0
Dual Attention Networks for Multimodal Reasoning and MatchingCode0
Dictionary Learning over Distributed Models—0
Robust Multimodal Graph Matching: Sparse Coding Meets Graph Matching—0
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