In this paper, we investigate tradeoffs among differential privacy (DP) ...
End-to-end training with global optimization have popularized graph neur...
Containers are used by an increasing number of Internet service provider...
The prevalent communication efficient federated learning (FL) frameworks...
Studying the computational complexity of determining winners under votin...
Nowadays, autonomous vehicle technology is becoming more and more mature...
Target-oriented Opinion Words Extraction (TOWE) is a fine-grained sentim...
Designing private voting rules is an important and pressing problem for
...
Logical table-to-text generation is a task that involves generating logi...
Formality style transfer (FST) is a task that involves paraphrasing an
i...
Entity-relation extraction aims to jointly solve named entity recognitio...
To develop driving automation technologies for human, a human-centered
m...
Logical Natural Language Generation, i.e., generating textual descriptio...
Highway pilot assist has become the front line of competition in advance...
Suppose a decision maker wants to predict weather tomorrow by eliciting ...
Motivated by the recent discovery that the interpretation maps of CNNs c...
Differential privacy (DP) is a widely-accepted and widely-applied notion...
When aggregating logically interconnected judgments from n agents, the
r...
A success factor for modern companies in the age of Digital Marketing is...
Graph convolution network (GCN) have achieved state-of-the-art performan...
In the encrypted network traffic intrusion detection, deep learning base...
As large eye-tracking datasets are created, data privacy is a pressing
c...
This paper studies a stylized, yet natural, learning-to-rank problem and...
Voting privacy has received a lot of attention across several research
c...
Computational synthesis planning approaches have achieved recent success...