Search Results for author: Quan Yuan

Found 12 papers, 2 papers with code

SCC: an efficient deep reinforcement learning agent mastering the game of StarCraft II

no code implementations24 Dec 2020 Xiangjun Wang, Junxiao Song, Penghui Qi, Peng Peng, Zhenkun Tang, Wei zhang, Weimin Li, Xiongjun Pi, Jujie He, Chao GAO, Haitao Long, Quan Yuan

In this paper, we will share the key insights and optimizations on efficient imitation learning and reinforcement learning for StarCraft II full game.

Imitation Learning Starcraft +1

Large Scale Product Graph Construction for Recommendation in E-commerce

no code implementations12 Oct 2020 Xiaoyong Yang, Yadong Zhu, Yi Zhang, Xiaobo Wang, Quan Yuan

Building a recommendation system that serves billions of users on daily basis is a challenging problem, as the system needs to make astronomical number of predictions per second based on real-time user behaviors with O(1) time complexity.

graph construction Recommendation Systems

Towards Interpretable Clinical Diagnosis with Bayesian Network Ensembles Stacked on Entity-Aware CNNs

no code implementations ACL 2020 Jun Chen, Xiaoya Dai, Quan Yuan, Chao Lu, Haifeng Huang

The automatic text-based diagnosis remains a challenging task for clinical use because it requires appropriate balance between accuracy and interpretability.

Improving Recommendation Diversity by Highlighting the ExTrA Fabricated Experts

no code implementations24 Apr 2020 Ya-Hui An, Qiang Dong, Quan Yuan, Chao Wang

Nowadays, recommender systems (RSes) are becoming increasingly important to individual users and business marketing, especially in the online e-commerce scenarios.

Recommendation Systems

Alleviating the recommendation bias via rank aggregation

no code implementations22 Apr 2020 Qiang Dong, Quan Yuan, Yang-Bo Shi

The primary goal of a recommender system is often known as "helping users find relevant items", and a lot of recommendation algorithms are proposed accordingly.

Fairness Recommendation Systems

User Validation of Recommendation Serendipity Metrics

no code implementations27 Jun 2019 Li Chen, Ningxia Wang, Yonghua Yang, Keping Yang, Quan Yuan

Though it has been recognized that recommending serendipitous (i. e., surprising and relevant) items can be helpful for increasing users' satisfaction and behavioral intention, how to measure serendipity in the offline environment is still an open issue.

Blind Motion Deblurring with Cycle Generative Adversarial Networks

no code implementations7 Jan 2019 Quan Yuan, Junxia Li, Lingwei Zhang, Zhefu Wu, Guangyu Liu

Blind motion deblurring is one of the most basic and challenging problems in image processing and computer vision.

Deblurring

Bridging Collaborative Filtering and Semi-Supervised Learning: A Neural Approach for POI Recommendation

no code implementations1 Aug 2017 Carl Yang, Lanxiao Bai, Chao Zhang, Quan Yuan, J. Han profile

In this work, we propose to devise a general and principled SSL (semi-supervised learning) framework, to alleviate data scarcity via smoothing among neighboring users and POIs, and treat various context by regularizing user preference based on context graphs.

Collaborative Filtering Recommendation Systems

Graph-based Point-of-interest Recommendation with Geographical and Temporal Influences

no code implementations1 Nov 2014 Quan Yuan, Gao Cong, Aixin Sun

In this paper, we focus on the problem of time-aware POI recommendation, which aims at recommending a list of POIs for a user to visit at a given time.

Recommendation Systems

A Weight-coded Evolutionary Algorithm for the Multidimensional Knapsack Problem

no code implementations21 Feb 2013 Quan Yuan, Zhi-Xin Yang

A revised weight-coded evolutionary algorithm (RWCEA) is proposed for solving multidimensional knapsack problems.

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