4.8k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Peking UniversityCN85 papers
- Microsoft (United States)US82 papers
- Tsinghua UniversityCN81 papers
- University of Science and Technology of ChinaCN81 papers
- Hong Kong University of Science and TechnologyHK40 papers
- Beihang UniversityCN36 papers
- Chinese Academy of SciencesCN36 papers
- Shanghai Jiao Tong UniversityCN33 papers
- Microsoft Research (United Kingdom)GB28 papers
- Zhejiang UniversityCN28 papers
- Fudan UniversityCN24 papers
- Carnegie Mellon UniversityUS19 papers
6 papers · 2 filters
Skeptical Deep Learning with Distribution Correction
Mingxiao An, Yongzhou Chen, Qi Liu +4
Recently deep neural networks have been successfully used for various classification tasks, especially for problems with massive perfectly labeled training data. However, it is oft…
Target Transfer Q-Learning and Its Convergence Analysis
Yue Wang, Qi Meng, Wei Cheng +3
Q-learning is one of the most popular methods in Reinforcement Learning (RL). Transfer Learning aims to utilize the learned knowledge from source tasks to help new tasks to improve…
Capacity Control of ReLU Neural Networks by Basis-path Norm
Shuxin Zheng, Qi Meng, Huishuai Zhang +3
Recently, path norm was proposed as a new capacity measure for neural networks with Rectified Linear Unit (ReLU) activation function, which takes the rescaling-invariant property o…
MOBA-Slice: A Time Slice Based Evaluation Framework of Relative Advantage between Teams in MOBA Games
Lijun Yu, Dawei Zhang, Xiangqun Chen +1
Multiplayer Online Battle Arena (MOBA) is currently one of the most popular genres of digital games around the world. The domain of knowledge contained in these complicated games i…
xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems
Jianxun Lian, Xiaohuan Zhou, Fuzheng Zhang +3
Combinatorial features are essential for the success of many commercial models. Manually crafting these features usually comes with high cost due to the variety, volume and velocit…
Thompson Sampling for Combinatorial Semi-Bandits
Siwei Wang, Wei Chen
In this paper, we study the application of the Thompson sampling (TS) methodology to the stochastic combinatorial multi-armed bandit (CMAB) framework. We first analyze the standard…