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162
kategorie
2 032
podkategorie
23 060
pojęcia
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Split Learning

Collaborative learning approach where the neural network model is split between client and server, enabling learning without sharing raw data.

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SplitNN

Split neural network architecture where initial layers run on the client and deeper layers on the server.

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Cut Layer

Division point of the neural network model between client and server, determining which part of the computation is performed locally.

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Client-side Model

Portion of the neural network model executed on the client device, processing data without transmitting it.

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Server-side Model

Part of the neural network model hosted on the server, completing inference from received partial activations.

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Vertical Split Learning

Variant where the model is split vertically between different layers, distributing computation between client and server.

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Horizontal Split Learning

Approach where features are partitioned horizontally between different entities collaborating on the same model.

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Model Partitioning

Process of strategically dividing an AI model into segments distributed across different infrastructures.

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Privacy-Preserving ML

Set of techniques enabling machine learning without exposing users' sensitive data.

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Communication Overhead

Cost in bandwidth and latency induced by exchanges between client and server in the distributed architecture.

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Latency Optimization

Critical challenge in split learning aiming to minimize response delays in distributed systems.

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Activation Smashing

Potential attack where intermediate activations are analyzed to reconstruct input data.

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Collaborative Intelligence

Concept where multiple entities combine their computational resources for mutually beneficial learning.

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Model Inference

Phase of using the trained model to make predictions, distributed in the context of split learning.

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