48 citations · 84 across the 6 of their papers we have counts for
6 papers
Differentiable Neural Input Search for Recommender Systems
Weiyu Cheng, Yanyan Shen, Linpeng Huang
Latent factor models are the driving forces of the state-of-the-art recommender systems, with an important insight of vectorizing raw input features into dense embeddings. The dime…
Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions
Weiyu Cheng, Yanyan Shen, Linpeng Huang
Various factorization-based methods have been proposed to leverage second-order, or higher-order cross features for boosting the performance of predictive models. They generally en…
Revisiting Flow Information for Traffic Prediction
Xian Zhou, Yanyan Shen, Linpeng Huang
Traffic prediction is a fundamental task in many real applications, which aims to predict the future traffic volume in any region of a city. In essence, traffic volume in a region…
STEP : A Distributed Multi-threading Framework Towards Efficient Data Analytics
Yijie Mei, Yanyan Shen, Yanmin Zhu +1
Various general-purpose distributed systems have been proposed to cope with high-diversity applications in the pipeline of Big Data analytics. Most of them provide simple yet effec…
Explaining Latent Factor Models for Recommendation with Influence Functions
Weiyu Cheng, Yanyan Shen, Yanmin Zhu +1
Latent factor models (LFMs) such as matrix factorization achieve the state-of-the-art performance among various Collaborative Filtering (CF) approaches for recommendation. Despite…
A Calculus of Consistent Component-based Software Updates
Xiaohui Xu, Linpeng Huang, Dejun Wang +1
It is important to enable reasoning about the meaning and possible effects of updates to ensure that the updated system operates correctly. A formal, mathematical model of dynamic…