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no code implementations • ICML 2020 • Yufeng Zhang, Qi Cai, Zhuoran Yang, Zhaoran Wang

Generative adversarial imitation learning (GAIL) demonstrates tremendous success in practice, especially when combined with neural networks.

no code implementations • 14 Oct 2021 • Qilong Yan, Yufeng Zhang, Qiang Liu, Shu Wu, Liang Wang

User profiling has long been an important problem that investigates user interests in many real applications.

no code implementations • 19 Aug 2021 • Zhihan Liu, Yufeng Zhang, Zuyue Fu, Zhuoran Yang, Zhaoran Wang

In generative adversarial imitation learning (GAIL), the agent aims to learn a policy from an expert demonstration so that its performance cannot be discriminated from the expert policy on a certain predefined reward set.

no code implementations • 15 Aug 2021 • Qiang Liu, Yanqiao Zhu, Zhaocheng Liu, Yufeng Zhang, Shu Wu

To train high-performing models with the minimal annotation cost, active learning is proposed to select and label the most informative samples, yet it is still challenging to measure informativeness of samples used in DNNs.

no code implementations • 8 Mar 2021 • Yi Wang, Jinxiang Yao, Yufeng Zhang

For C1-smooth strongly monotone discrete-time dynamical systems, it is shown that ``convergence to linearly stable cycles" is a prevalent asymptotic behavior in the measuretheoretic sense.

Dynamical Systems

no code implementations • 10 Feb 2021 • Yufeng Zhang, Wanwei Liu, Zhenbang Chen, Kenli Li, Ji Wang

Secondly, for any three $n$-dimensional Gaussians $\mathcal{N}_1, \mathcal{N}_2$ and $\mathcal{N}_3$, we find a bound of $KL(\mathcal{N}_1||\mathcal{N}_3)$ if $KL(\mathcal{N}_1||\mathcal{N}_2)$ and $KL(\mathcal{N}_2||\mathcal{N}_3)$ are bounded.

1 code implementation • 28 Jan 2021 • Yufeng Zhang, Jinghao Zhang, Zeyu Cui, Shu Wu, Liang Wang

To retrieve more relevant, appropriate and useful documents given a query, finding clues about that query through the text is crucial.

no code implementations • 18 Jan 2021 • Xiangzhuo Xing, Yue Sun, Xiaolei Yi, Meng Li, Jiajia Feng, Yan Meng, Yufeng Zhang, Wenchong Li, Nan Zhou, Xiude He, Jun-Yi Ge, Wei Zhou, Tsuyoshi Tamegai, Zhixiang Shi

FeSe$_{1-x}$Te$_{x}$ superconductors manifest some intriguing electronic properties depending on the value of $x$.

Superconductivity Materials Science

no code implementations • 1 Jan 2021 • Yufeng Zhang, Yunan Zhang, ChengXiang Zhai

To classify images, neural networks extract features from raw inputs and then sum them up with fixed weights via the fully connected layer.

no code implementations • 21 Dec 2020 • Zhuoran Yang, Yufeng Zhang, Yongxin Chen, Zhaoran Wang

Specifically, we prove that moving along the geodesic in the direction of functional gradient with respect to the second-order Wasserstein distance is equivalent to applying a pushforward mapping to a probability distribution, which can be approximated accurately by pushing a set of particles.

no code implementations • NeurIPS 2020 • Yufeng Zhang, Qi Cai, Zhuoran Yang, Yongxin Chen, Zhaoran Wang

Temporal-diﬀerence and Q-learning play a key role in deep reinforcement learning, where they are empowered by expressive nonlinear function approximators such as neural networks.

no code implementations • 8 Jun 2020 • Yufeng Zhang, Qi Cai, Zhuoran Yang, Yongxin Chen, Zhaoran Wang

We aim to answer the following questions: When the function approximator is a neural network, how does the associated feature representation evolve?

2 code implementations • ACL 2020 • Yufeng Zhang, Xueli Yu, Zeyu Cui, Shu Wu, Zhongzhen Wen, Liang Wang

We first build individual graphs for each document and then use GNN to learn the fine-grained word representations based on their local structures, which can also effectively produce embeddings for unseen words in the new document.

no code implementations • 8 Mar 2020 • Yufeng Zhang, Qi Cai, Zhuoran Yang, Zhaoran Wang

Generative adversarial imitation learning (GAIL) demonstrates tremendous success in practice, especially when combined with neural networks.

no code implementations • 9 Feb 2020 • Yufeng Zhang, Wanwei Liu, Zhenbang Chen, Ji Wang, Zhiming Liu, Kenli Li, Hongmei Wei

Based on our analysis, we propose two group anomaly detection methods.

no code implementations • 11 Nov 2019 • Yunan Zhang, Xiang Cheng, Yufeng Zhang, Zihan Wang, Zhengqi Fang, Xiaoyan Wang, Zhenya Huang, ChengXiang Zhai

Answering complex questions involving multiple entities and relations is a challenging task.

1 code implementation • 11 Apr 2019 • Hao Wu, Jiayuan Mao, Yufeng Zhang, Yuning Jiang, Lei LI, Weiwei Sun, Wei-Ying Ma

We propose Unified Visual-Semantic Embeddings (UniVSE) for learning a joint space of visual and textual concepts.

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