4 citations · 12 across the 5 of their papers we have counts for
6 papers
ProV-Mem: Proactive Memory for Streaming Video Question Answering
Bingbing Wang, Jing Li, Han Gao +3
Proactive streaming video question answering requires a model to continuously monitor an incoming stream and autonomously decide when to speak, what to say, and whether to emit a r…
Stable Adversarial Learning under Distributional Shifts
Jiashuo Liu, Zheyan Shen, Peng Cui +4
Machine learning algorithms with empirical risk minimization are vulnerable under distributional shifts due to the greedy adoption of all the correlations found in training data. R…
SocialTrans: A Deep Sequential Model with Social Information for Web-Scale Recommendation Systems
Qiaoan Chen, Hao Gu, Lingling Yi +4
On social network platforms, a user's behavior is based on his/her personal interests, or influenced by his/her friends. In the literature, it is common to model either users' pers…
Combining Offline Causal Inference and Online Bandit Learning for Data Driven Decision
Li Ye, Yishi Lin, Hong Xie +1
A fundamental question for companies with large amount of logged data is: How to use such logged data together with incoming streaming data to make good decisions? Many companies c…
Boosting Information Spread: An Algorithmic Approach
Yishi Lin, Wei Chen, John C. S. Lui
The majority of influence maximization (IM) studies focus on targeting influential seeders to trigger substantial information spread in social networks. In this paper, we consider…
Algorithmic Design for Competitive Influence Maximization Problems
Yishi Lin, John C. S. Lui
Given the popularity of the viral marketing campaign in online social networks, finding an effective method to identify a set of most influential nodes so to compete well with othe…