Search Results for author: JC Mao

Found 3 papers, 1 papers with code

Recurrent Binary Embedding for GPU-Enabled Exhaustive Retrieval from Billion-Scale Semantic Vectors

no code implementations18 Feb 2018 Ying Shan, Jian Jiao, Jie Zhu, JC Mao

Building on top of the powerful concept of semantic learning, this paper proposes a Recurrent Binary Embedding (RBE) model that learns compact representations for real-time retrieval.

Information Retrieval Retrieval

Deep Embedding Forest: Forest-based Serving with Deep Embedding Features

no code implementations15 Mar 2017 Jie Zhu, Ying Shan, JC Mao, Dong Yu, Holakou Rahmanian, Yi Zhang

Built on top of a representative DNN model called Deep Crossing, and two forest/tree-based models including XGBoost and LightGBM, a two-step Deep Embedding Forest algorithm is demonstrated to achieve on-par or slightly better performance as compared with the DNN counterpart, with only a fraction of serving time on conventional hardware.

Cannot find the paper you are looking for? You can Submit a new open access paper.