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Tight Capacity Bounds for Indoor Visible Light Communications With Signal-Dependent Noise
Channel capacity bounds are derived for a point-to-point indoor visible ...
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Continual Learning from the Perspective of Compression
Connectionist models such as neural networks suffer from catastrophic fo...
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Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning
Learning from non-stationary data remains a great challenge for machine ...
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On the Secrecy Performance of Random VLC Networks with Imperfect CSI and Protected Zone
This paper investigates the physical-layer security for a random indoor ...
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On the Secrecy Rate of Spatial Modulation Based Indoor Visible Light Communications
In this paper, we investigate the physical-layer security for a spatial ...
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Conditional Computation for Continual Learning
Catastrophic forgetting of connectionist neural networks is caused by th...
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Online continual learning with no task boundaries
Continual learning is the ability of an agent to learn online with a non...
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Bandit Inspired Beam Searching Scheme for mmWave High-Speed Train Communications
High-speed trains (HSTs) are being widely deployed around the world. To ...
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Joint Doppler and Channel Estimation with Nested Arrays for Millimeter Wave Communications
Channel estimation is essential for precoding/combining in millimeter wa...
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Adaptive Spatial Modulation for Visible Light Communications with an Arbitrary Number of Transmitters
As a power and bandwidth efficient modulation scheme, the optical spatia...
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Physical-layer Security for Indoor Visible Light Communications: Secrecy Capacity Analysis
This paper investigates the physical-layer security for an indoor visibl...
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On the Spectral Bias of Deep Neural Networks
It is well known that over-parametrized deep neural networks (DNNs) are ...
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A Machine Learning Framework for Resource Allocation Assisted by Cloud Computing
Conventionally, the resource allocation is formulated as an optimization...
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Softmax GAN
Softmax GAN is a novel variant of Generative Adversarial Network (GAN). ...
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MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
MXNet is a multi-language machine learning (ML) library to ease the deve...
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Correntropy Induced L2 Graph for Robust Subspace Clustering
In this paper, we study the robust subspace clustering problem, which ai...
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Purine: A bi-graph based deep learning framework
In this paper, we introduce a novel deep learning framework, termed Puri...
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Network In Network
We propose a novel deep network structure called "Network In Network" (N...
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