no code implementations • 18 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.
no code implementations • 15 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.
2 code implementations • KDD 2016 • Ying Shan, T. Ryan Hoens, Jian Jiao, Haijing Wang, Dong Yu, JC Mao
Manually crafted combinatorial features have been the “secret sauce” behind many successful models.