activity
20192022
most citedTowards Playing Full MOBA Games with Deep Reinforcement Learning

42 citations · 46 across the 3 of their papers we have counts for

collaborators

8 papers

cs.CV20224 cited

AlignVE: Visual Entailment Recognition Based on Alignment Relations

Biwei Cao, Jiuxin Cao, Jie Gui +5

Visual entailment (VE) is to recognize whether the semantics of a hypothesis text can be inferred from the given premise image, which is one special task among recent emerged visio…

hep-ex2021

PANDA Phase One

G. Barucca, F. Davì, G. Lancioni +421

The Facility for Antiproton and Ion Research (FAIR) in Darmstadt, Germany, provides unique possibilities for a new generation of hadron-, nuclear- and atomic physics experiments. T…

cs.AI202042 cited

Towards Playing Full MOBA Games with Deep Reinforcement Learning

Deheng Ye, Guibin Chen, Wen Zhang +15

MOBA games, e.g., Honor of Kings, League of Legends, and Dota 2, pose grand challenges to AI systems such as multi-agent, enormous state-action space, complex action control, etc.…

cs.LG2019

Optimal Function Approximation with Relu Neural Networks

Bo Liu, Yi Liang

We consider in this paper the optimal approximations of convex univariate functions with feed-forward Relu neural networks. We are interested in the following question: what is the…

cs.LG2019

Transfer Learning-Based Label Proportions Method with Data of Uncertainty

Yanshan Xiao, HuaiPei Wang, Bo Liu

Learning with label proportions (LLP), which is a learning task that only provides unlabeled data in bags and each bag's label proportion, has widespread successful applications in…

cs.CV2019

Multi-scale Cell Instance Segmentation with Keypoint Graph based Bounding Boxes

Jingru Yi, Pengxiang Wu, Qiaoying Huang +4

Most existing methods handle cell instance segmentation problems directly without relying on additional detection boxes. These methods generally fails to separate touching cells du…