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06/30/2023
Impact of Noise on Calibration and Generalisation of Neural Networks
Noise injection and data augmentation strategies have been effective for...
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06/11/2023
An information-Theoretic Approach to Semi-supervised Transfer Learning
Transfer learning is a valuable tool in deep learning as it allows propa...
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04/27/2023
On the Generalization Error of Meta Learning for the Gibbs Algorithm
We analyze the generalization ability of joint-training meta learning al...
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10/15/2022
How Does Pseudo-Labeling Affect the Generalization Error of the Semi-Supervised Gibbs Algorithm?
This paper provides an exact characterization of the expected generaliza...
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09/15/2022
Semi-Counterfactual Risk Minimization Via Neural Networks
Counterfactual risk minimization is a framework for offline policy optim...
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05/19/2022
Simple Regularisation for Uncertainty-Aware Knowledge Distillation
Considering uncertainty estimation of modern neural networks (NNs) is on...
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02/24/2022
Tighter Expected Generalization Error Bounds via Convexity of Information Measures
Generalization error bounds are essential to understanding machine learn...
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01/20/2022
Minimax Demographic Group Fairness in Federated Learning
Federated learning is an increasingly popular paradigm that enables a la...
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11/05/2021
Deep Joint Encryption and Source-Channel Coding: An Image Privacy Protection Approach
Joint source and channel coding (JSCC) has achieved great success due to...
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11/02/2021
Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm
We provide an information-theoretic analysis of the generalization abili...
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10/05/2021
Federating for Learning Group Fair Models
Federated learning is an increasingly popular paradigm that enables a la...
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05/12/2021
High-Performance FPGA-based Accelerator for Bayesian Neural Networks
Neural networks (NNs) have demonstrated their potential in a wide range ...
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04/14/2021
ComBiNet: Compact Convolutional Bayesian Neural Network for Image Segmentation
Fully convolutional U-shaped neural networks have largely been the domin...
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02/22/2021
On the Effects of Quantisation on Model Uncertainty in Bayesian Neural Networks
Bayesian neural networks (BNNs) are making significant progress in many ...
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07/12/2020
VINNAS: Variational Inference-based Neural Network Architecture Search
In recent years, neural architecture search (NAS) has received intensive...
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05/18/2018
Learning to Collaborate for User-Controlled Privacy
It is becoming increasingly clear that users should own and control thei...
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01/28/2013
Generalized Bregman Divergence and Gradient of Mutual Information for Vector Poisson Channels
We investigate connections between information-theoretic and estimation-...
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06/27/2012