While collaborative filtering is the dominant technique in personalized recommendation, it
models user-item interactions only and cannot provide concrete reasons for a …

In this paper we introduce SVDFeature, a machine learning toolkit for feature-based
collaborative filtering. SVDFeature is designed to efficiently solve the feature-based matrix …

Recommendation techniques have been well developed in the past decades. Most of them
build models only based on user item rating matrix. However, in real world, there is plenty of …

With the development of social networking applications, microblog has turned to be an
indispensable online communication network in our daily life. For microblog users …

In the real-time bidding (RTB) display advertising ecosystem, when receiving a bid request,
the demand-side platform (DSP) needs to predict the click-through rate (CTR) for ads and …

Gradient Boosted Decision Trees (GBDT) is a very successful ensemble learning algorithm
widely used across a variety of applications. Recently, several variants of GBDT training …

With the popularization of social networks, increasing numbers of users choose to use
Weibo to get information. However, as the number of users grows, the information on Weibo …

Relevance ranking models based on additive ensembles of regression trees have shown
quite good effectiveness in web search engines. In the era of big data, tree ensemble …