226 citations · 420 across the 13 of their papers we have counts for
13 papers
More Like Real World Game Challenge for Partially Observable Multi-Agent Cooperation
Meng Yao, Xueou Feng, Qiyue Yin
Some standardized environments have been designed for partially observable multi-agent cooperation, but we find most current environments are synchronous, whereas real-world agents…
Improved Training of Mixture-of-Experts Language GANs
Yekun Chai, Qiyue Yin, Junge Zhang
Despite the dramatic success in image generation, Generative Adversarial Networks (GANs) still face great challenges in synthesizing sequences of discrete elements, in particular h…
Distributed Deep Reinforcement Learning: A Survey and A Multi-Player Multi-Agent Learning Toolbox
Qiyue Yin, Tongtong Yu, Shengqi Shen +5
With the breakthrough of AlphaGo, deep reinforcement learning becomes a recognized technique for solving sequential decision-making problems. Despite its reputation, data inefficie…
RACA: Relation-Aware Credit Assignment for Ad-Hoc Cooperation in Multi-Agent Deep Reinforcement Learning
Hao Chen, Guangkai Yang, Junge Zhang +2
In recent years, reinforcement learning has faced several challenges in the multi-agent domain, such as the credit assignment issue. Value function factorization emerges as a promi…
The Partially Observable Asynchronous Multi-Agent Cooperation Challenge
Meng Yao, Qiyue Yin, Jun Yang +5
Multi-agent reinforcement learning (MARL) has received increasing attention for its applications in various domains. Researchers have paid much attention on its partially observabl…
AI in Human-computer Gaming: Techniques, Challenges and Opportunities
Qiyue Yin, Jun Yang, Kaiqi Huang +6
With breakthrough of the AlphaGo, human-computer gaming AI has ushered in a big explosion, attracting more and more researchers all around the world. As a recognized standard for t…
Learning to Reweight Imaginary Transitions for Model-Based Reinforcement Learning
Wenzhen Huang, Qiyue Yin, Junge Zhang +1
Model-based reinforcement learning (RL) is more sample efficient than model-free RL by using imaginary trajectories generated by the learned dynamics model. When the model is inacc…
Planning with Exploration: Addressing Dynamics Bottleneck in Model-based Reinforcement Learning
Xiyao Wang, Junge Zhang, Wenzhen Huang +1
Model-based reinforcement learning (MBRL) is believed to have higher sample efficiency compared with model-free reinforcement learning (MFRL). However, MBRL is plagued by dynamics…
Deep Self-Supervised Representation Learning for Free-Hand Sketch
Peng Xu, Zeyu Song, Qiyue Yin +2
In this paper, we tackle for the first time, the problem of self-supervised representation learning for free-hand sketches. This importantly addresses a common problem faced by the…
Deep Learning for Free-Hand Sketch: A Survey
Peng Xu, Timothy M. Hospedales, Qiyue Yin +3
Free-hand sketches are highly illustrative, and have been widely used by humans to depict objects or stories from ancient times to the present. The recent prevalence of touchscreen…
Cross-modal Subspace Learning for Fine-grained Sketch-based Image Retrieval
Peng Xu, Qiyue Yin, Yongye Huang +6
Sketch-based image retrieval (SBIR) is challenging due to the inherent domain-gap between sketch and photo. Compared with pixel-perfect depictions of photos, sketches are iconic re…
A Comprehensive Survey on Cross-modal Retrieval
Kaiye Wang, Qiyue Yin, Wei Wang +2
In recent years, cross-modal retrieval has drawn much attention due to the rapid growth of multimodal data. It takes one type of data as the query to retrieve relevant data of anot…
Cross-Modal Learning via Pairwise Constraints
Ran He, Man Zhang, Liang Wang +2
In multimedia applications, the text and image components in a web document form a pairwise constraint that potentially indicates the same semantic concept. This paper studies cros…