Fine-tuning can be vulnerable to adversarial attacks. Existing works abo...
Learning against label noise is a vital topic to guarantee a reliable
pe...
Hierarchical clustering recursively partitions data at an increasingly f...
Convolutional Neural Networks (CNNs) have achieved tremendous success in...
Deep Convolutional Neural Networks (DCNNs) and their variants have been
...
Recent studies show that crowd-sourced Natural Language Inference (NLI)
...
Authentication is the task of confirming the matching relationship betwe...
We present HDP-VFL, the first hybrid differentially private (DP) framewo...
Transfer learning has become a common practice for training deep learnin...
Privacy-preserving recommendations are recently gaining momentum, since ...
Deep auto-encoders (DAEs) have achieved great success in learning data
r...
Attention-based methods have played an important role in model
interpret...
Model interpretation is essential in data mining and knowledge discovery...
In this paper, we report our recent practice at Tencent for user modelin...
With the recent proliferation of the use of text classifications, resear...
Nowadays, news apps have taken over the popularity of paper-based media,...
Deep domain adaptation models learn a neural network in an unlabeled tar...
Natural language inference (NLI) aims at predicting the relationship bet...
Temporal action localization is a recently-emerging task, aiming to loca...
Authentication is a task aiming to confirm the truth between data instan...
Natural Language Sentence Matching (NLSM) has gained substantial attenti...
Recurrent Neural Networks (RNNs) and their variants, such as Long-Short ...
Recently, Reinforcement Learning (RL) approaches have demonstrated advan...