20 citations · 39 across the 8 of their papers we have counts for
8 papers
Fast Object Detection with Latticed Multi-Scale Feature Fusion
Yue Shi, Bo Jiang, Zhengping Che +1
Scale variance is one of the crucial challenges in multi-scale object detection. Early approaches address this problem by exploiting the image and feature pyramid, which raises sub…
On Sampling Strategies for Neural Network-based Collaborative Filtering
Ting Chen, Yizhou Sun, Yue Shi +1
Recent advances in neural networks have inspired people to design hybrid recommendation algorithms that can incorporate both (1) user-item interaction information and (2) content i…
Joint Text Embedding for Personalized Content-based Recommendation
Ting Chen, Liangjie Hong, Yue Shi +1
Learning a good representation of text is key to many recommendation applications. Examples include news recommendation where texts to be recommended are constantly published every…
The Apps You Use Bring The Blogs to Follow
Yue Shi, Erheng Zhong, Suju Rajan +3
We tackle the blog recommendation problem in Tumblr for mobile users in this paper. Blog recommendation is challenging since most mobile users would suffer from the cold start when…
Learning Optimal Card Ranking from Query Reformulation
Liangjie Hong, Yue Shi, Suju Rajan
Mobile search has recently been shown to be the major contributor to the growing search market. The key difference between mobile search and desktop search is that information pres…
Learning Subclass Representations for Visually-varied Image Classification
Xinchao Li, Peng Xu, Yue Shi +2
In this paper, we present a subclass-representation approach that predicts the probability of a social image belonging to one particular class. We explore the co-occurrence of user…
GAPfm: Optimal Top-N Recommendations for Graded Relevance Domains
Yue Shi, Alexandros Karatzoglou, Linas Baltrunas +2
Recommender systems are frequently used in domains in which users express their preferences in the form of graded judgments, such as ratings. If accurate top-N recommendation lists…
Exploiting Social Tags for Cross-Domain Collaborative Filtering
Yue Shi, Martha Larson, Alan Hanjalic
One of the most challenging problems in recommender systems based on the collaborative filtering (CF) concept is data sparseness, i.e., limited user preference data is available fo…