no code implementations • CCL 2021 • Qian Chen, Xiaoying Gao, Suge Wang, Xin Guo
“知识图谱问题生成任务是从给定的知识图谱中生成与其相关的问题。目前, 知识图谱问题生成模型主要使用基于RNN或Transformer对知识图谱子图进行编码, 但这种方式丢失了显式的图结构化信息, 在解码器中忽视了局部信息对节点的重要性。本文提出迭代信息传递图编码器来编码子图, 获取子图显式的图结构化信息, 此外, 我们还使用滑动窗口注意力机制提高RNN解码器, 提升子图局部信息对节点的重要度。从WQ和PQ数据集上的实验结果看, 我们提出的模型比KTG模型在BLEU4指标上分别高出2. 16和15. 44, 证明了该模型的有效性。”
no code implementations • 6 May 2024 • Yingying Zhang, Chuangji Shi, Xin Guo, Jiangwei Lao, Jian Wang, Jiaotuan Wang, Jingdong Chen
The design of the query is crucial for the performance of DETR and its variants.
1 code implementation • 8 Feb 2024 • Zhiheng Xi, Wenxiang Chen, Boyang Hong, Senjie Jin, Rui Zheng, wei he, Yiwen Ding, Shichun Liu, Xin Guo, Junzhe Wang, Honglin Guo, Wei Shen, Xiaoran Fan, Yuhao Zhou, Shihan Dou, Xiao Wang, Xinbo Zhang, Peng Sun, Tao Gui, Qi Zhang, Xuanjing Huang
In this paper, we propose R$^3$: Learning Reasoning through Reverse Curriculum Reinforcement Learning (RL), a novel method that employs only outcome supervision to achieve the benefits of process supervision for large language models.
no code implementations • 12 Jan 2024 • Chuanji Shi, Yingying Zhang, Jiaotuan Wang, Xin Guo, Qiqi Zhu
Unlike conventional AOI generation methods, such as the Road-cut method that segments road networks at various levels, our approach diverges from semantic segmentation algorithms that depend on pixel-level classification.
no code implementations • 10 Jan 2024 • Haotian Gu, Xin Guo, Timothy L. Jacobs, Philip Kaminsky, Xinyu Li
Freight transportation marketplace rates are typically challenging to forecast accurately.
no code implementations • 15 Dec 2023 • Xin Guo, Jiangwei Lao, Bo Dang, Yingying Zhang, Lei Yu, Lixiang Ru, Liheng Zhong, Ziyuan Huang, Kang Wu, Dingxiang Hu, Huimei He, Jian Wang, Jingdong Chen, Ming Yang, Yongjun Zhang, Yansheng Li
Prior studies on Remote Sensing Foundation Model (RSFM) reveal immense potential towards a generic model for Earth Observation.
no code implementations • 23 Nov 2023 • Xin Guo, Xinyu Li, Renyuan Xu
This paper proposes and analyzes two new policy learning methods: regularized policy gradient (RPG) and iterative policy optimization (IPO), for a class of discounted linear-quadratic control (LQC) problems over an infinite time horizon with entropy regularization.
no code implementations • 6 Nov 2023 • Haoyang Cao, Haotian Gu, Xin Guo, Mathieu Rosenbaum
Transfer learning is an emerging and popular paradigm for utilizing existing knowledge from previous learning tasks to improve the performance of new ones.
1 code implementation • 14 Sep 2023 • Zhiheng Xi, Wenxiang Chen, Xin Guo, wei he, Yiwen Ding, Boyang Hong, Ming Zhang, Junzhe Wang, Senjie Jin, Enyu Zhou, Rui Zheng, Xiaoran Fan, Xiao Wang, Limao Xiong, Yuhao Zhou, Weiran Wang, Changhao Jiang, Yicheng Zou, Xiangyang Liu, Zhangyue Yin, Shihan Dou, Rongxiang Weng, Wensen Cheng, Qi Zhang, Wenjuan Qin, Yongyan Zheng, Xipeng Qiu, Xuanjing Huang, Tao Gui
Many efforts have been made to develop intelligent agents, but they mainly focus on advancement in algorithms or training strategies to enhance specific capabilities or performance on particular tasks.
1 code implementation • 19 Aug 2023 • Liwen Zhang, Weige Cai, Zhaowei Liu, Zhi Yang, Wei Dai, Yujie Liao, Qianru Qin, Yifei Li, Xingyu Liu, Zhiqiang Liu, Zhoufan Zhu, Anbo Wu, Xin Guo, Yun Chen
Our work offers a more comprehensive financial knowledge evaluation benchmark, utilizing data of mock exams and covering a wide range of evaluated LLMs.
no code implementations • 25 Jul 2023 • Haoyang Cao, Haotian Gu, Xin Guo, Mathieu Rosenbaum
In particular, 1. a strong correlation between the transfer risk and the overall performance of transfer learning methods is established, underscoring the significance of transfer risk as a viable indicator of "transferability"; 2. transfer risk is shown to provide a computationally efficient way to identify appropriate source tasks in transfer learning, enhancing the efficiency and effectiveness of the transfer learning approach; 3. additionally, the numerical experiments offer valuable new insights for portfolio management across these different settings.
no code implementations • 16 Jul 2023 • Xin Guo, Lihong Li, Sareh Nabi, Rabih Salhab, Junzi Zhang
Motivated by bid recommendation in online ad auctions, this paper considers a general class of multi-level and multi-agent games, with two major characteristics: one is a large number of anonymous agents, and the other is the intricate interplay between competition and cooperation.
no code implementations • 22 May 2023 • Haoyang Cao, Haotian Gu, Xin Guo
Transfer learning is a popular paradigm for utilizing existing knowledge from previous learning tasks to improve the performance of new ones.
no code implementations • 21 May 2023 • Xin Guo, Xinyu Li, Chinmay Maheshwari, Shankar Sastry, Manxi Wu
In this new framework, Markov games are shown to be Markov $\alpha$-potential games, and the existence of an associated $\alpha$-potential function is established.
no code implementations • 17 May 2023 • Xin Guo, Ruixun Zhang, Chaoyi Zhao
Signature transforms are iterated path integrals of continuous and discrete-time time series data, and their universal nonlinearity linearizes the problem of feature selection.
no code implementations • 27 Jan 2023 • Haoyang Cao, Haotian Gu, Xin Guo, Mathieu Rosenbaum
In this paper we build for the first time, to the best of our knowledge, a mathematical framework for the general procedure of transfer learning.
no code implementations • ICCV 2023 • Kaixiang Ji, Feng Chen, Xin Guo, Yadong Xu, Jian Wang, Jingdong Chen
Image manipulation detection (IMD) is of vital importance as faking images and spreading misinformation can be malicious and harm our daily life.
no code implementations • CVPR 2023 • Yurui Zhu, Tianyu Wang, Xueyang Fu, Xuanyu Yang, Xin Guo, Jifeng Dai, Yu Qiao, Xiaowei Hu
Inspired by this observation, we design an efficient unified framework with a two-stage training strategy to explore the weather-general and weather-specific features.
no code implementations • CVPR 2023 • Jiangwei Lao, Weixiang Hong, Xin Guo, Yingying Zhang, Jian Wang, Jingdong Chen, Wei Chu
In this work, we propose a novel feature enhancement network to simultaneously model short- and long-term temporal correlation.
no code implementations • 25 Sep 2022 • Xin Guo, Zheng-Chu Guo, Lei Shi
This article provides convergence analysis of online stochastic gradient descent algorithms for functional linear models.
no code implementations • 11 Feb 2022 • Haoyang Cao, Xin Guo, Guan Wang
Anomaly detection has been an active research area with a wide range of potential applications.
no code implementations • 4 Jan 2022 • Guan Wang, Yusuke Kikuchi, Jinglin Yi, Qiong Zou, Rui Zhou, Xin Guo
Recently, deep learning techniques have been successfully applied for detection of diabetic retinopathy (DR).
no code implementations • 17 Dec 2021 • Lin Liu, Shanxin Yuan, Jianzhuang Liu, Xin Guo, Youliang Yan, Qi Tian
For zero-shot image restoration, we design a novel model, termed SiamTrans, which is constructed by Siamese transformers, encoders, and decoders.
no code implementations • 5 Dec 2021 • Xin Guo, Yuming Chen, Jian Du, Erdan Dong
Design/methodology/approach: Taking cardiovascular research publications in China as a sample, we extracted the SPO triples as knowledge unit and the hedging/conflicting uncertainties as the knowledge context.
no code implementations • 1 Dec 2021 • Othmane Mounjid, Xin Guo
Training generative adversarial networks (GANs) is known to be difficult, especially for financial time series.
no code implementations • 13 Sep 2021 • Xin Guo, Anran Hu, Junzi Zhang
To our best knowledge, this is the first theoretical guarantee on fictitious discount algorithms for the episodic reinforcement learning of finite-time-horizon MDPs, which also leads to the (first) global convergence of policy gradient methods for finite-time-horizon episodic reinforcement learning.
1 code implementation • 20 Aug 2021 • Junyu Luo, Jianlei Yang, Xucheng Ye, Xin Guo, Weisheng Zhao
Federated learning aims to protect users' privacy while performing data analysis from different participants.
no code implementations • 5 Aug 2021 • Haotian Gu, Xin Guo, Xiaoli Wei, Renyuan Xu
This paper proposes a framework of localized training and decentralized execution to study MARL with network of states.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 7 Jun 2021 • Xin Guo, Jianlei Yang, Haoyi Zhou, Xucheng Ye, JianXin Li
In order to overcome these security problems, RoSearch is proposed as a comprehensive framework to search the student models with better adversarial robustness when performing knowledge distillation.
no code implementations • 17 May 2021 • Haotian Gu, Xin Guo, Xinyu Li
Adversarial training has gained great popularity as one of the most effective defenses for deep neural network and more generally for gradient-based machine learning models against adversarial perturbations on data points.
no code implementations • 29 Apr 2021 • Xin Guo, Zhongming Jin, Chong Chen, Helei Nie, Jianqiang Huang, Deng Cai, Xiaofei He, Xiansheng Hua
In this paper, we propose a DiscRiminative-gEnerative duAl Memory (DREAM) anomaly detection model to take advantage of a few anomalies and solve data imbalance.
no code implementations • 25 Apr 2021 • Haoyang Cao, Xin Guo
Ever since its debut, generative adversarial networks (GANs) have attracted tremendous amount of attention.
no code implementations • 19 Apr 2021 • Xin Guo, Anran Hu, Yufei Zhang
We study finite-time horizon continuous-time linear-convex reinforcement learning problems in an episodic setting.
no code implementations • 31 Mar 2021 • Lintao Li, Longwei Yang, Xin Guo, Yuanming Shi, Haiming Wang, Wei Chen, Khaled B. Letaief
Federated learning (FL) is a collaborative machine learning paradigm, which enables deep learning model training over a large volume of decentralized data residing in mobile devices without accessing clients' private data.
1 code implementation • 27 Jan 2021 • Peixiao Zheng, Xin Guo, Lin Qi
In this paper, we proposed an edge-labeling-based directed gated graph network (DGGN) for few-shot learning, which utilizes gated recurrent units to implicitly update the similarity between nodes.
no code implementations • 29 Dec 2020 • Xin Guo, Yang Liu, Tangman Yin, Blair Morrison, Mattia Pagani, Okky Daulay, Wim Bogaerts, Benjamin J. Eggleton, Alvaro Casas-Bedoya, David Marpaung
Optical modulation plays arguably the utmost important role in microwave photonic (MWP) systems.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Xin Guo, Yu Tian, Qinghan Xue, Panos Lampropoulos, Steven Eliuk, Kenneth Barner, Xiaolong Wang
Catastrophic forgetting in neural networks indicates the performance decreasing of deep learning models on previous tasks while learning new tasks.
no code implementations • 30 Sep 2020 • Xin Guo, Renyuan Xu, Thaleia Zariphopoulou
In addition, this study leads to a policy-gradient algorithm for exploration in MFG.
1 code implementation • 17 Sep 2020 • Xin Guo, Yifan Zhao, Jia Li
To explore the relationship between music and dance movements, we propose a cross-modal alignment module that focuses on dancing video clips, accompanied on pre-designed music, to learn a system that can judge the consistency between the visual features of pose sequences and the acoustic features of music.
no code implementations • 16 Sep 2020 • Yao Wang, Xin Guo, Shao-Bo Lin
Numerically, we carry out a series of simulations to show the promising performance of KReBooT in terms of its good generalization, near over-fitting resistance and structure constraints.
no code implementations • 30 Jul 2020 • Xin Guo, Zhengxu Yu, Chao Xiang, Zhongming Jin, Jianqiang Huang, Deng Cai, Xiaofei He, Xian-Sheng Hua
Most deep-learning-based image classification methods assume that all samples are generated under an independent and identically distributed (IID) setting.
no code implementations • 27 Jun 2020 • Matteo Basei, Xin Guo, Anran Hu, Yufei Zhang
We study finite-time horizon continuous-time linear-quadratic reinforcement learning problems in an episodic setting, where both the state and control coefficients are unknown to the controller.
no code implementations • 16 Jun 2020 • Xinjie Lan, Xin Guo, Kenneth E. Barner
We study PAC-Bayesian generalization bounds for Multilayer Perceptrons (MLPs) with the cross entropy loss.
no code implementations • 12 Jun 2020 • Xin Guo, Yusuke Kikuchi, Guan Wang, Jinglin Yi, Qiong Zou, Rui Zhou
Retinopathy of prematurity (ROP) is an abnormal blood vessel development in the retina of a prematurely-born infant or an infant with low birth weight.
no code implementations • 3 Jun 2020 • Haoyang Cao, Xin Guo
This paper analyzes the training process of GANs via stochastic differential equations (SDEs).
no code implementations • 9 May 2020 • Xin Guo, Jiequn Han, Mahan Tajrobehkar, Wenpin Tang
Motivated by the super-diffusivity of self-repelling random walk, which has roots in statistical physics, this paper develops a new perturbation mechanism for optimization algorithms.
no code implementations • 13 Mar 2020 • Xin Guo, Anran Hu, Renyuan Xu, Junzi Zhang
This paper presents a general mean-field game (GMFG) framework for simultaneous learning and decision-making in stochastic games with a large population.
no code implementations • 11 Mar 2020 • Lin Jia, Kewen Li, Yu Jiang, Xin Guo, Ting zhao
According to the current trend, based on the three models, the total number of people expected to be infected is 49852-57447 in Wuhan, 12972-13405 in non-Hubei areas and 80261-85140 in China respectively.
Populations and Evolution
no code implementations • 20 Feb 2020 • Xin Guo, Luisa F. Polanía, Kenneth E. Barner
This paper presents an audiovisual-based emotion recognition hybrid network.
no code implementations • 10 Feb 2020 • Haotian Gu, Xin Guo, Xiaoli Wei, Renyuan Xu
Multi-agent reinforcement learning (MARL), despite its popularity and empirical success, suffers from the curse of dimensionality.
no code implementations • 10 Feb 2020 • Haoyang Cao, Xin Guo, Mathieu Laurière
Generative adversarial networks (GANs) have enjoyed tremendous success in image generation and processing, and have recently attracted growing interests in financial modelings.
no code implementations • 2 Oct 2019 • Bin Zhu, Xin Guo, Kenneth Barner, Charles Boncelet
The task is to predict the cohesive level for a group of people in images.
1 code implementation • 19 Sep 2019 • Xin Guo, Luisa F. Polania, Bin Zhu, Charles Boncelet, Kenneth E. Barner
A graph neural network (GNN) for image understanding based on multiple cues is proposed in this paper.
no code implementations • ECCV 2020 • Xucheng Ye, Pengcheng Dai, Junyu Luo, Xin Guo, Yingjie Qi, Jianlei Yang, Yiran Chen
Sparsification is an efficient approach to accelerate CNN inference, but it is challenging to take advantage of sparsity in training procedure because the involved gradients are dynamically changed.
1 code implementation • 6 May 2019 • Wen Chen, Pipei Huang, Jiaming Xu, Xin Guo, Cheng Guo, Fei Sun, Chao Li, Andreas Pfadler, Huan Zhao, Binqiang Zhao
In particular, there exist two requirements for fashion outfit recommendation: the Compatibility of the generated fashion outfits, and the Personalization in the recommendation process.
no code implementations • 21 Mar 2019 • Xin Guo, Charles-Albert Lehalle, Renyuan Xu
This part is on the time scale of each transaction of liquid corporate bonds, and is by applying a transient impact model to estimate the price impact kernel using a non-parametric method.
no code implementations • 22 Oct 2018 • Tianyi Lin, Zhiyue Hu, Xin Guo
As topic sparsity of individual documents in online social media increases, so does the difficulty of analyzing the online text sources using traditional methods.
no code implementations • 10 Sep 2018 • Xin Guo, Wenpin Tang, Renyuan Xu
In this paper we propose and analyze a class of $N$-player stochastic games that include finite fuel stochastic games as a special case.
no code implementations • 17 Jan 2018 • Xin Guo, Luisa F. Polanía, Kenneth E. Barner
Compared to the size of databases for face recognition, far less labeled data is available for training smile detection systems.
no code implementations • 23 May 2017 • Xin Guo, Johnny Hong, Nan Yang
Construction of ambiguity set in robust optimization relies on the choice of divergences between probability distributions.
no code implementations • 19 May 2017 • Xin Guo, Johnny Hong, Tianyi Lin, Nan Yang
Wasserstein Generative Adversarial Networks (WGANs) provide a versatile class of models, which have attracted great attention in various applications.
no code implementations • 11 Aug 2016 • Shao-Bo Lin, Xin Guo, Ding-Xuan Zhou
We study distributed learning with the least squares regularization scheme in a reproducing kernel Hilbert space (RKHS).
no code implementations • CVPR 2013 • Xin Guo, Dong Liu, Brendan Jou, Mojun Zhu, Anni Cai, Shih-Fu Chang
Object co-detection aims at simultaneous detection of objects of the same category from a pool of related images by exploiting consistent visual patterns present in candidate objects in the images.
2 code implementations • 28 May 2012 • Wen-Jun Shen, Hau-San Wong, Quan-Wu Xiao, Xin Guo, Stephen Smale
We attempt to set a mathematical foundation of immunology and amino acid chains.