5 citations · 15 across the 9 of their papers we have counts for
9 papers
Learning Personalized Page Content Ranking Using Customer Representation
Xin Shen, Yan Zhao, Sujan Perera +3
On E-commerce stores, there are rich recommendation content to help shoppers shopping more efficiently. However given numerous products, it's crucial to select most relevant conten…
Measuring Long-term Impact of Ads on LinkedIn Feed
Jinyun Yan, Birjodh Tiwana, Souvik Ghosh +2
Organic updates (from a member's network) and sponsored updates (or ads, from advertisers) together form the newsfeed on LinkedIn. The newsfeed, the default homepage for members, a…
Personalized Treatment Selection using Causal Heterogeneity
Ye Tu, Kinjal Basu, Cyrus DiCiccio +4
Randomized experimentation (also known as A/B testing or bucket testing) is widely used in the internet industry to measure the metric impact obtained by different treatment varian…
People Like Us: Mining Scholarly Data for Comparable Researchers
Graham Cormode, S. Muthukrishnan, Jinyun Yan
We present the problem of finding comparable researchers for any given researcher. This problem has many motivations. Firstly, know thyself. The answers of where we stand among res…
A Consensus-Focused Group Recommender System
Stratis Ioannidis, S. Muthukrishnan, Jinyun Yan
In many cases, recommendations are consumed by groups of users rather than individuals. In this paper, we present a system which recommends social events to groups. The system help…
First Author Advantage: Citation Labeling in Research
Graham Cormode, S. Muthukrishnan, Jinyun Yan
Citations among research papers, and the networks they form, are the primary object of study in scientometrics. The act of making a citation reflects the citer's knowledge of the r…
Who and Where: People and Location Co-Clustering
Zixuan Wang, Jinyun Yan
In this paper, we consider the clustering problem on images where each image contains patches in people and location domains. We exploit the correlation between people and location…
A Time and Space Efficient Algorithm for Contextual Linear Bandits
José Bento, Stratis Ioannidis, S. Muthukrishnan +1
We consider a multi-armed bandit problem where payoffs are a linear function of an observed stochastic contextual variable. In the scenario where there exists a gap between optimal…
Scienceography: the study of how science is written
Graham Cormode, S. Muthukrishnan, Jinyun Yan
Scientific literature has itself been the subject of much scientific study, for a variety of reasons: understanding how results are communicated, how ideas spread, and assessing th…