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Found 8 papers, 1 papers with code
Intent Assurance using LLMs guided by Intent Drift
Intent-Based Networking (IBN) presents a paradigm shift for network management, by promising to align intents and business objectives with network operations--in an automated manner.
LLM-based policy generation for intent-based management of applications
And the task of identifying and adapting these steps (as conditions change) requires a decomposition approach that cannot be exactly pre-defined beforehand.
Improving Knowledge Distillation with Teacher's Explanation
The teacher in KD is a black-box model, imparting knowledge to the student only through its predictions.
Generative Adversarial Classification Network with Application to Network Traffic Classification
Large datasets in machine learning often contain missing data, which necessitates the imputation of missing data values.
Flow-Packet Hybrid Traffic Classification for Class-Aware Network Routing
At a network router, the packets need to be processed with minimum delay, so the classifier cannot wait until the end of the flow to make a decision.
Queue-Learning: A Reinforcement Learning Approach for Providing Quality of Service
End-to-end delay is a critical attribute of quality of service (QoS) in application domains such as cloud computing and computer networks.
Reinforcement Learning-based Admission Control in Delay-sensitive Service Systems
Our evaluations verify that the proposed RL-based admission controller is capable of providing probabilistic bounds on the end-to-end delay of the network, without using system model information.
Probabilistic Bounds on the End-to-End Delay of Service Function Chains using Deep MDN
Ensuring the conformance of a service system's end-to-end delay to service level agreement (SLA) constraints is a challenging task that requires statistical measures beyond the average delay.
Performance Networking and Internet Architecture
