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07/21/2023
Improving Transferability of Adversarial Examples via Bayesian Attacks
This paper presents a substantial extension of our work published at ICL...
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03/23/2022
Estimating trans-ancestry genetic correlation with unbalanced data resources
The aim of this paper is to propose a novel estimation method of using g...
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09/27/2021
HAGEN: Homophily-Aware Graph Convolutional Recurrent Network for Crime Forecasting
The crime forecasting is an important problem as it greatly contributes ...
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05/17/2021
Deep Metric Learning for Few-Shot Image Classification: A Selective Review
Few-shot image classification is a challenging problem which aims to ach...
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07/01/2020
Information Theoretic Sample Complexity Lower Bound for Feed-Forward Fully-Connected Deep Networks
In this paper, we study the sample complexity lower bound of a d-layer f...
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06/27/2020
ReMarNet: Conjoint Relation and Margin Learning for Small-Sample Image Classification
Despite achieving state-of-the-art performance, deep learning methods ge...
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06/10/2020
Towards Certified Robustness of Metric Learning
Metric learning aims to learn a distance metric such that semantically s...
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02/09/2018
Metric Learning via Maximizing the Lipschitz Margin Ratio
In this paper, we propose the Lipschitz margin ratio and a new metric le...
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02/09/2018