no code implementations • 10 Apr 2023 • Wenyun Li, Guo Zhong, Xingyu Lu, Chi-Man Pun
This article proposes a multiview hashing with learnable parameters to retrieve the queried images for a large-scale remote sensing dataset.
1 code implementation • 21 Oct 2022 • Bowen Zhao, Jiuding Sun, Bin Xu, Xingyu Lu, Yuchen Li, Jifan Yu, Minghui Liu, Tingjian Zhang, Qiuyang Chen, Hanming Li, Lei Hou, Juanzi Li
To tackle these issues, we propose EDUKG, a heterogeneous sustainable K-12 Educational Knowledge Graph.
no code implementations • 27 Aug 2021 • Yitao Shen, Yue Wang, Xingyu Lu, Feng Qi, Jia Yan, Yixiang Mu, Yao Yang, Yifan Peng, Jinjie Gu
In order to do effective optimization in the second stage, counterfactual prediction and noise-reduction are essential for the first stage.
1 code implementation • 26 Feb 2021 • Jing Zhu, Xingyu Lu, Mark Heimann, Danai Koutra
While most network embedding techniques model the relative positions of nodes in a network, recently there has been significant interest in structural embeddings that model node role equivalences, irrespective of their distances to any specific nodes.
no code implementations • 23 Dec 2020 • Youcef Nafa, Qun Chen, Zhaoqiang Chen, Xingyu Lu, Haiyang He, Tianyi Duan, Zhanhuai Li
Building upon the recent advances in risk analysis for ER, which can provide a more refined estimate on label misprediction risk than the simpler classifier outputs, we propose a novel AL approach of risk sampling for ER.
no code implementations • 3 Aug 2020 • Xingyu Lu, Kimin Lee, Pieter Abbeel, Stas Tiomkin
Despite the significant progress of deep reinforcement learning (RL) in solving sequential decision making problems, RL agents often overfit to training environments and struggle to adapt to new, unseen environments.
no code implementations • 21 Dec 2019 • Xingyu Lu, Stas Tiomkin, Pieter Abbeel
While recent progress in deep reinforcement learning has enabled robots to learn complex behaviors, tasks with long horizons and sparse rewards remain an ongoing challenge.
no code implementations • 23 Sep 2019 • Ofir Nachum, Haoran Tang, Xingyu Lu, Shixiang Gu, Honglak Lee, Sergey Levine
Hierarchical reinforcement learning has demonstrated significant success at solving difficult reinforcement learning (RL) tasks.
Hierarchical Reinforcement Learning reinforcement-learning +1