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11/03/2022
Fair and Efficient Distributed Edge Learning with Hybrid Multipath TCP
The bottleneck of distributed edge learning (DEL) over wireless has shif...
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03/15/2022
Regenerative Particle Thompson Sampling
This paper proposes regenerative particle Thompson sampling (RPTS), a fl...
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05/29/2021
Learning to Harness Bandwidth with Multipath Congestion Control and Scheduling
Multipath TCP (MPTCP) has emerged as a facilitator for harnessing and po...
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02/25/2021
Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning
Federated learning is a new learning paradigm that decouples data collec...
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12/13/2020
Privacy-preserving Decentralized Aggregation for Federated Learning
Federated learning is a promising framework for learning over decentrali...
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03/21/2020
Dynamic Sampling and Selective Masking for Communication-Efficient Federated Learning
Federated learning (FL) is a novel machine learning setting which enable...
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02/07/2020
Stability and Scalability of Blockchain Systems
The blockchain paradigm provides a mechanism for content dissemination a...
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08/08/2019
Deep Reinforcement Learning for Network Slicing with Heterogeneous Resource Requirements and Time Varying Traffic Dynamics
Efficient network slicing is vital to deal with the highly variable and ...
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12/03/2018
Deep Reinforcement Learning for Intelligent Transportation Systems
Intelligent Transportation Systems (ITSs) are envisioned to play a criti...
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11/19/2018
Practical Deep Reinforcement Learning Approach for Stock Trading
Stock trading strategy plays a crucial role in investment companies. How...
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11/18/2018
Transform-Based Multilinear Dynamical System for Tensor Time Series Analysis
We propose a novel multilinear dynamical system (MLDS) in a transform do...
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12/13/2017
Multidimensional Data Tensor Sensing for RF Tomographic Imaging
Radio-frequency (RF) tomographic imaging is a promising technique for in...
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12/13/2017