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09/09/2023
Symplectic Structure-Aware Hamiltonian (Graph) Embeddings
In traditional Graph Neural Networks (GNNs), the assumption of a fixed e...
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03/19/2023
Randomized Adversarial Training via Taylor Expansion
In recent years, there has been an explosion of research into developing...
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01/23/2023
Optimising Event-Driven Spiking Neural Network with Regularisation and Cutoff
Spiking neural networks (SNNs), a variant of artificial neural networks ...
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05/05/2022
Near-Field Wideband Extremely Large-scale MIMO Transmission with Holographic Metasurface Antennas
Extremely large-scale multiple-input multiple-output (XL-MIMO) is the de...
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03/11/2022
Enhancing Adversarial Training with Second-Order Statistics of Weights
Adversarial training has been shown to be one of the most effective appr...
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01/23/2022
Weight Expansion: A New Perspective on Dropout and Generalization
While dropout is known to be a successful regularization technique, insi...
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01/22/2022
Neuronal Correlation: a Central Concept in Neural Network
This paper proposes to study neural networks through neuronal correlatio...
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08/24/2021
Adversarial Robustness of Deep Learning: Theory, Algorithms, and Applications
This tutorial aims to introduce the fundamentals of adversarial robustne...
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05/26/2021
Topological Pilot Assignment in Large-Scale Distributed MIMO Networks
We consider the pilot assignment problem in large-scale distributed mult...
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04/27/2021
Downlink Precoding for DP-UPA FDD Massive MIMO via Multi-Dimensional Active Channel Sparsification
In this paper, we consider user selection and downlink precoding for an ...
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03/01/2021
A Little Energy Goes a Long Way: Energy-Efficient, Accurate Conversion from Convolutional Neural Networks to Spiking Neural Networks
Spiking neural networks (SNNs) offer an inherent ability to process spat...
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01/29/2021
Topological Interference Management with Adversarial Perturbation
In this paper, we consider the topological interference management (TIM)...
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10/12/2020
How does Weight Correlation Affect the Generalisation Ability of Deep Neural Networks
This paper studies the novel concept of weight correlation in deep neura...
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08/25/2020
Dual-Polarized FDD Massive MIMO: A Comprehensive Framework
We propose a comprehensive scheme for realizing a massive multiple-input...
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06/12/2020
Asymptotic Singular Value Distribution of Linear Convolutional Layers
In convolutional neural networks, the linear transformation of multi-cha...
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05/27/2020
Robust Precoding in Massive MIMO: A Deep Learning Approach
In this paper, we consider massive multiple-input-multiple-output (MIMO)...
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02/12/2020
Energy Efficiency Optimization for Downlink Massive MIMO With Statistical CSIT
We investigate energy efficiency (EE) optimization for single-cell massi...
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10/27/2019
Learning to Localize: A 3D CNN Approach to User Positioning in Massive MIMO-OFDM Systems
In this paper, we consider the user positioning problem in the massive m...
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09/26/2019
On the Optimality of Treating Inter-Cell Interference as Noise: Downlink Cellular Networks and Uplink-Downlink Duality
We consider the information-theoretic optimality of treating inter-cell ...
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01/17/2019
On Multi-Cell Uplink-Downlink Duality with Treating Inter-Cell Interference as Noise
We consider the information-theoretic optimality of treating inter-cell ...
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12/18/2018
Safety and Trustworthiness of Deep Neural Networks: A Survey
In the past few years, significant progress has been made on deep neural...
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08/27/2018
Opportunistic Treating Interference as Noise
We consider a K-user interference network with M states, where each tran...
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03/15/2018
