no code implementations • 24 Feb 2023 • Junhuan Yang, Yi Sheng, Yuzhou Zhang, Weiwen Jiang, Lei Yang
What's more, for a larger size image in the BBBC005 dataset, the existing approach cannot be accommodated to Raspberry PI due to out of memory; on the other hand, SegHDC can obtain segmentation results within 3 minutes while achieving a 0. 9587 IoU score.
1 code implementation • 28 Oct 2022 • Haojie Pan, Zepeng Zhai, Yuzhou Zhang, Ruiji Fu, Ming Liu, Yangqiu Song, Zhongyuan Wang, Bing Qin
In this paper, we propose Kuaipedia, a large-scale multi-modal encyclopedia consisting of items, aspects, and short videos lined to them, which was extracted from billions of videos of Kuaishou (Kwai), a well-known short-video platform in China.
no code implementations • 29 Dec 2019 • Yuzhou Zhang, Yi Mei, Buzhong Zhang, Keqin Jiang
This paper proposes a novel problem decomposition operator, named the route cutting off operator, which considers the interactions between the tasks in a sophisticated way.
6 code implementations • 9 Apr 2019 • Bin Liu, Ruiming Tang, Yingzhi Chen, Jinkai Yu, Huifeng Guo, Yuzhou Zhang
Easy-to-use, Modular and Extendible package of deep-learning based CTR models. DeepFM, DeepInterestNetwork(DIN), DeepInterestEvolutionNetwork(DIEN), DeepCrossNetwork(DCN), AttentionalFactorizationMachine(AFM), Neural Factorization Machine(NFM), AutoInt, Deep Session Interest Network(DSIN)
Ranked #1 on Click-Through Rate Prediction on Huawei App Store
no code implementations • 14 Nov 2018 • Haokun Chen, Xinyi Dai, Han Cai, Wei-Nan Zhang, Xuejian Wang, Ruiming Tang, Yuzhou Zhang, Yong Yu
Reinforcement learning (RL) has recently been introduced to interactive recommender systems (IRS) because of its nature of learning from dynamic interactions and planning for long-run performance.
5 code implementations • 29 Oct 2018 • Feng Liu, Ruiming Tang, Xutao Li, Wei-Nan Zhang, Yunming Ye, Haokun Chen, Huifeng Guo, Yuzhou Zhang
The DRR framework treats recommendation as a sequential decision making procedure and adopts an "Actor-Critic" reinforcement learning scheme to model the interactions between the users and recommender systems, which can consider both the dynamic adaptation and long-term rewards.