20 citations · 44 across the 3 of their papers we have counts for
3 papers
cs.LG2018★ 19 cited
Ranking Distillation: Learning Compact Ranking Models With High Performance for Recommender System
Jiaxi Tang, Ke Wang
We propose a novel way to train ranking models, such as recommender systems, that are both effective and efficient. Knowledge distillation (KD) was shown to be successful in image…
cs.IR2018★ 5 cited
Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding
Jiaxi Tang, Ke Wang
Top- sequential recommendation models each user as a sequence of items interacted in the past and aims to predict top- ranked items that a user will likely interact in a `nea…
cs.SI2017★ 20 cited
Top-k Route Search through Submodularity Modeling of Recurrent POI Features
Hongwei Liang, Ke Wang
We consider a practical top-k route search problem: given a collection of points of interest (POIs) with rated features and traveling costs between POIs, a user wants to find k rou…