1 code implementation • EMNLP 2021 • Yun Ma, Qing Li
In this paper, we explore Non-AutoRegressive (NAR) decoding for unsupervised text style transfer.
no code implementations • EMNLP 2020 • Xinhong Chen, Qing Li, JianPing Wang
The causal relationships between emotions and causes in text have recently received a lot of attention.
no code implementations • EMNLP 2020 • Xin Wu, Yi Cai, Yang Kai, Tao Wang, Qing Li
Meta-embedding learning, which combines complementary information in different word embeddings, have shown superior performances across different Natural Language Processing tasks.
1 code implementation • EMNLP 2021 • Yun Ma, Yangbin Chen, Xudong Mao, Qing Li
In this paper, we propose a collaborative learning framework for unsupervised text style transfer using a pair of bidirectional decoders, one decoding from left to right while the other decoding from right to left.
no code implementations • 20 May 2023 • Yao Du, Qing Li, Huawei Fan, Meng Zhan, Jinghua Xiao, Xingang Wang
Power systems dominated by renewable energy encounter frequently large, random disturbances, and a critical challenge faced in power-system management is how to anticipate accurately whether the perturbed systems will return to the functional state after the transient or collapse.
1 code implementation • CVPR 2023 • Qing Li, Huifang Feng, Kanle Shi, Yue Gao, Yi Fang, Yu-Shen Liu, Zhizhong Han
In this work, we introduce signed hyper surfaces (SHS), which are parameterized by multi-layer perceptron (MLP) layers, to learn to estimate oriented normals from point clouds in an end-to-end manner.
no code implementations • 10 May 2023 • Thanveer Shaik, Xiaohui Tao, Haoran Xie, Lin Li, Xiaofeng Zhu, Qing Li
Machine unlearning (MU) is gaining increasing attention due to the need to remove or modify predictions made by machine learning (ML) models.
no code implementations • 6 May 2023 • Da Ren, Qing Li
Non-autoregressive models have been widely studied in the Complete Information Scenario (CIS), in which the models have complete input information to obtain corresponding output.
no code implementations • 5 May 2023 • Zongxiong Chen, Jiahui Geng, Derui Zhu, Herbert Woisetschlaeger, Qing Li, Sonja Schimmler, Ruben Mayer, Chunming Rong
The aim of dataset distillation is to encode the rich features of an original dataset into a tiny dataset.
no code implementations • 30 Apr 2023 • Shaodong Wang, Qing Li, Wenli Zhang
Representing medical concepts for healthcare analytical tasks requires incorporating medical domain knowledge and prior information from patient description data.
no code implementations • 25 Feb 2023 • Haiyang Liu, Chunjiang Zhu, Detian Zhang, Qing Li
The key challenge is to effectively model complex spatial-temporal dependencies and correlations in modern traffic data.
no code implementations • 24 Feb 2023 • Xunlian Luo, Chunjiang Zhu, Detian Zhang, Qing Li
However, existing approaches use independent components to model temporal and spatial dependencies and thus ignore the heterogeneous characteristics of traffic flow that vary with time and space.
no code implementations • 16 Feb 2023 • Xiao Chen, Wenqi Fan, Jingfan Chen, Haochen Liu, Zitao Liu, Zhaoxiang Zhang, Qing Li
Pairwise learning strategies are prevalent for optimizing recommendation models on implicit feedback data, which usually learns user preference by discriminating between positive (i. e., clicked by a user) and negative items (i. e., obtained by negative sampling).
no code implementations • 6 Feb 2023 • Chengyi Liu, Wenqi Fan, Yunqing Liu, Jiatong Li, Hang Li, Hui Liu, Jiliang Tang, Qing Li
Given the great success of diffusion models in image generation, increasing efforts have been made to leverage these techniques to advance graph generation in recent years.
no code implementations • 23 Jan 2023 • Yuan Feng, Hyeran Jeon, Filip Blagojevic, Cyril Guyot, Qing Li, Dong Li
Transformer models gain popularity because of their superior inference accuracy and inference throughput.
no code implementations • 17 Dec 2022 • Shaopeng Wei, Yu Zhao, Xingyan Chen, Qing Li, Fuzhen Zhuang, Ji Liu, Gang Kou
Different from previous surveys on graph learning, we provide a holistic review that analyzes current works from the perspective of graph structure, and discusses the latest applications, trends, and challenges in graph learning.
no code implementations • 11 Dec 2022 • XiaoDong Li, Pangjing Wu, Chenxin Zou, Qing Li
Designing an intelligent volume-weighted average price (VWAP) strategy is a critical concern for brokers, since traditional rule-based strategies are relatively static that cannot achieve a lower transaction cost in a dynamic market.
Hierarchical Reinforcement Learning
reinforcement-learning
+1
no code implementations • 28 Nov 2022 • Yu Zhao, Huaming Du, Qing Li, Fuzhen Zhuang, Ji Liu, Gang Kou
In contrast, this paper attempts to provide a systematic literature survey of enterprise risk analysis approaches from Big Data perspective, which reviews more than 250 representative articles in the past almost 50 years (from 1968 to 2023).
1 code implementation • 28 Nov 2022 • Li Yuan, Yi Cai, Jin Wang, Qing Li
This paper is the first to propose jointly performing MNER and MRE as a joint multimodal entity-relation extraction task (JMERE).
1 code implementation • 28 Nov 2022 • Jiangyong Huang, William Yicheng Zhu, Baoxiong Jia, Zan Wang, Xiaojian Ma, Qing Li, Siyuan Huang
Current computer vision models, unlike the human visual system, cannot yet achieve general-purpose visual understanding.
no code implementations • 27 Nov 2022 • Yu Guo, Zhilong Xie, Xingyan Chen, Huangen Chen, Leilei Wang, Huaming Du, Shaopeng Wei, Yu Zhao, Qing Li, Gang Wu
We address the problem by introducing a novel joint method on top of BERT which explicitly models the multiple sub-tokens features after wordpiece tokenization, thereby contributing to the two tasks.
1 code implementation • 14 Oct 2022 • Xiaojian Ma, Silong Yong, Zilong Zheng, Qing Li, Yitao Liang, Song-Chun Zhu, Siyuan Huang
We propose a new task to benchmark scene understanding of embodied agents: Situated Question Answering in 3D Scenes (SQA3D).
Ranked #1 on
Referring Expression
on SQA3D
1 code implementation • 13 Oct 2022 • Qing Li, Yu-Shen Liu, Jin-San Cheng, Cheng Wang, Yi Fang, Zhizhong Han
To address these issues, we introduce hyper surface fitting to implicitly learn hyper surfaces, which are represented by multi-layer perceptron (MLP) layers that take point features as input and output surface patterns in a high dimensional feature space.
Ranked #1 on
Surface Normals Estimation
on PCPNet
no code implementations • 4 Oct 2022 • Qing Li, Yixin Zhu, Yitao Liang, Ying Nian Wu, Song-Chun Zhu, Siyuan Huang
In experiments, NSR achieves state-of-the-art performance in three benchmarks from different domains: SCAN for semantic parsing, PCFG for string manipulation, and HINT for arithmetic reasoning.
1 code implementation • 21 Sep 2022 • Guanhua Zhang, Yihua Zhang, Yang Zhang, Wenqi Fan, Qing Li, Sijia Liu, Shiyu Chang
Specifically, FairReprogram considers the case where models can not be changed and appends to the input a set of perturbations, called the fairness trigger, which is tuned towards the fairness criteria under a min-max formulation.
no code implementations • 21 Sep 2022 • Wenqi Fan, Xiangyu Zhao, Xiao Chen, Jingran Su, Jingtong Gao, Lin Wang, Qidong Liu, Yiqi Wang, Han Xu, Lei Chen, Qing Li
As one of the most successful AI-powered applications, recommender systems aim to help people make appropriate decisions in an effective and efficient way, by providing personalized suggestions in many aspects of our lives, especially for various human-oriented online services such as e-commerce platforms and social media sites.
no code implementations • 18 Aug 2022 • Jiahao Wu, Wenqi Fan, Jingfan Chen, Shengcai Liu, Qing Li, Ke Tang
In this work, to address such limitation, we propose a novel Disentangled contrastive learning framework for social Recommendations DcRec.
no code implementations • 4 Aug 2022 • Da Ren, Qing Li
Text generative models trained via Maximum Likelihood Estimation (MLE) suffer from the notorious exposure bias problem, and Generative Adversarial Networks (GANs) are shown to have potential to tackle this problem.
1 code implementation • 4 Aug 2022 • Kang You, Pan Gao, Qing Li
Point cloud is a crucial representation of 3D contents, which has been widely used in many areas such as virtual reality, mixed reality, autonomous driving, etc.
no code implementations • 21 Jul 2022 • Jingfan Chen, Wenqi Fan, Guanghui Zhu, Xiangyu Zhao, Chunfeng Yuan, Qing Li, Yihua Huang
Recent studies have shown that deep neural networks-based recommender systems are vulnerable to adversarial attacks, where attackers can inject carefully crafted fake user profiles (i. e., a set of items that fake users have interacted with) into a target recommender system to achieve malicious purposes, such as promote or demote a set of target items.
1 code implementation • 19 Jul 2022 • Xudong Mao, Liujuan Cao, Aurele T. Gnanha, Zhenguo Yang, Qing Li, Rongrong Ji
The recently proposed pivotal tuning model makes significant progress towards reconstruction and editability, by using a two-step approach that first inverts the input image into a latent code, called pivot code, and then alters the generator so that the input image can be accurately mapped into the pivot code.
no code implementations • 4 Jul 2022 • Xueying Zhan, Zeyu Dai, Qingzhong Wang, Qing Li, Haoyi Xiong, Dejing Dou, Antoni B. Chan
In this paper, we propose a sampling scheme, Monte-Carlo Pareto Optimization for Active Learning (POAL), which selects optimal subsets of unlabeled samples with fixed batch size from the unlabeled data pool.
1 code implementation • 4 Jun 2022 • Zeyu Dai, Shengcai Liu, Ke Tang, Qing Li
In this paper, we propose to restrict the perturbations to a small salient region to generate adversarial examples that can hardly be perceived.
1 code implementation • 8 May 2022 • Qing Li, Wengang Zhou, Zhenbo Lu, Houqiang Li
Actor-critic Reinforcement Learning (RL) algorithms have achieved impressive performance in continuous control tasks.
no code implementations • 10 Mar 2022 • Qing Li, Shangguang Wang, Xiao Ma, Ao Zhou, Fangchun Yang
Recently, Low Earth Orbit (LEO) satellites experience rapid development and satellite edge computing emerges to address the limitation of bent-pipe architecture in existing satellite systems.
no code implementations • 23 Feb 2022 • Kaige Wang, Tianming Wang, Jianchuang Qu, Huatao Jiang, Qing Li, Lin Chang
Firstly, the gap between the low-level vision task represented by rain removal and the high-level vision task represented by object detection is significant, and the low-level vision task can hardly contribute to the high-level vision task.
1 code implementation • 1 Feb 2022 • Yu Zhao, Shaopeng Wei, Yu Guo, Qing Yang, Xingyan Chen, Qing Li, Fuzhen Zhuang, Ji Liu, Gang Kou
This study for the first time considers both types of risk and their joint effects in bankruptcy prediction.
no code implementations • 28 Jan 2022 • Xulu Zhang, Zhenqun Yang, Hao Tian, Qing Li, XiaoYong Wei
In many applications, we need the matching evidence to be indicated rather than just have the ranked list (e. g., the locations of the target proteins/cells/lesions in medical images).
no code implementations • 21 Jan 2022 • Guangwu Qian, Zhen-Qun Yang, Xu-Lu Zhang, YaoWei Wang, Qing Li, Xiao-Yong Wei
Class Activation Mapping (CAM) has been widely adopted to generate saliency maps which provides visual explanations for deep neural networks (DNNs).
1 code implementation • 11 Jan 2022 • Yu Zhao, Huaming Du, Ying Liu, Shaopeng Wei, Xingyan Chen, Fuzhen Zhuang, Qing Li, Ji Liu, Gang Kou
Stock Movement Prediction (SMP) aims at predicting listed companies' stock future price trend, which is a challenging task due to the volatile nature of financial markets.
1 code implementation • 24 Dec 2021 • Yu Zhao, Shaopeng Wei, Huaming Du, Xingyan Chen, Qing Li, Fuzhen Zhuang, Ji Liu, Gang Kou
To address this issue, we propose a novel Dual Hierarchical Attention Networks (DHAN) based on the bi-typed multi-relational heterogeneous graphs to learn comprehensive node representations with the intra-class and inter-class attention-based encoder under a hierarchical mechanism.
no code implementations • 14 Dec 2021 • Qing Li, Boqing Gong, Yin Cui, Dan Kondratyuk, Xianzhi Du, Ming-Hsuan Yang, Matthew Brown
The experiments show that the resultant unified foundation transformer works surprisingly well on both the vision-only and text-only tasks, and the proposed knowledge distillation and gradient masking strategy can effectively lift the performance to approach the level of separately-trained models.
no code implementations • 10 Dec 2021 • Qing Li, Xiaojiang Peng, Chuan Yan, Pan Gao, Qi Hao
In SEN, a student network is kept in a collaborative manner with supervised learning and self-supervised learning, and a teacher network conducts temporal consistency to learn useful representations and ensure the quality of point clouds reconstruction.
no code implementations • 29 Oct 2021 • Yu Zhao, Jia Song, Huali Feng, Fuzhen Zhuang, Qing Li, Xiaojie Wang, Ji Liu
Keyphrase provides accurate information of document content that is highly compact, concise, full of meanings, and widely used for discourse comprehension, organization, and text retrieval.
no code implementations • 18 Oct 2021 • Jiahui Geng, Yongli Mou, Feifei Li, Qing Li, Oya Beyan, Stefan Decker, Chunming Rong
We find that image restoration fails even if there is only one incorrectly inferred label in the batch; we also find that when batch images have the same label, the corresponding image is restored as a fusion of that class of images.
1 code implementation • 15 Oct 2021 • Songbai Liu, Qiuzhen Lin, Kay Chen Tan, Qing Li
Evolutionary transfer multiobjective optimization (ETMO) has been becoming a hot research topic in the field of evolutionary computation, which is based on the fact that knowledge learning and transfer across the related optimization exercises can improve the efficiency of others.
2 code implementations • ACL 2022 • Junyi Ao, Rui Wang, Long Zhou, Chengyi Wang, Shuo Ren, Yu Wu, Shujie Liu, Tom Ko, Qing Li, Yu Zhang, Zhihua Wei, Yao Qian, Jinyu Li, Furu Wei
Motivated by the success of T5 (Text-To-Text Transfer Transformer) in pre-trained natural language processing models, we propose a unified-modal SpeechT5 framework that explores the encoder-decoder pre-training for self-supervised speech/text representation learning.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+7
no code implementations • 11 Oct 2021 • Rui Wang, Junyi Ao, Long Zhou, Shujie Liu, Zhihua Wei, Tom Ko, Qing Li, Yu Zhang
In this work, we propose a novel multi-view self-attention mechanism and present an empirical study of different Transformer variants with or without the proposed attention mechanism for speaker recognition.
no code implementations • 29 Sep 2021 • Ziang Zhou, Jieming Shi, Shengzhong Zhang, Zengfeng Huang, Qing Li
Therefore, we propose an effective framework, Stabilized self-training with Negative sampling (SN), which is applicable to existing GNNs to stabilize the training process and enhance the training data, and consequently, boost classification accuracy on graphs with few labeled data.
no code implementations • 29 Sep 2021 • Zeyu Dai, Shengcai Liu, Ke Tang, Qing Li
To address this issue, in this paper we propose to use segmentation priors for black-box attacks such that the perturbations are limited in the salient region.
no code implementations • 29 Sep 2021 • Xiaobo Liang, Runze Mao, Lijun Wu, Juntao Li, Weiqing Liu, Qing Li, Min Zhang
The common approach of consistency training is performed on the data-level, which typically utilizes the data augmentation strategy (or adversarial training) to make the predictions from the augmented input and the original input to be consistent, so that the model is more robust and attains better generalization ability.
no code implementations • ICCV 2021 • Yixin Chen, Qing Li, Deqian Kong, Yik Lun Kei, Song-Chun Zhu, Tao Gao, Yixin Zhu, Siyuan Huang
To the best of our knowledge, this is the first embodied reference dataset that allows us to study referring expressions in daily physical scenes to understand referential behavior, human communication, and human-robot interaction.
1 code implementation • 12 Aug 2021 • Wenqi Fan, Xiaorui Liu, Wei Jin, Xiangyu Zhao, Jiliang Tang, Qing Li
The key of recommender systems is to predict how likely users will interact with items based on their historical online behaviors, e. g., clicks, add-to-cart, purchases, etc.
no code implementations • 9 Aug 2021 • Huimin Zhou, Qing Li, Yong Jiang, Rongwei Yang, Zhuyun Qi
In the current deep learning based recommendation system, the embedding method is generally employed to complete the conversion from the high-dimensional sparse feature vector to the low-dimensional dense feature vector.
no code implementations • 7 Aug 2021 • Wenqi Fan, Wei Jin, Xiaorui Liu, Han Xu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, JianPing Wang, Charu Aggarwal
Despite the great success, recent studies have shown that GNNs are highly vulnerable to adversarial attacks, where adversaries can mislead the GNNs' prediction by modifying graphs.
1 code implementation • Conference 2021 • Xingcai Wu, Yucheng Xie, Jiaqi Zeng, Zhenguo Yang, Yi Yu, Qing Li, and Wenyin Liu
In this paper, we propose an adversarial learning framework with mask reconstruction (ALMR) for image inpainting with textual guidance, which consists of a two-stage generator and dual discriminators.
no code implementations • 4 Jul 2021 • Xueying Zhan, Qing Li, Antoni B. Chan
In this paper, we introduce a multiple-criteria based active learning algorithm, which incorporates three complementary criteria, i. e., informativeness, representativeness and diversity, to make appropriate selections in the active learning rounds under different data types.
no code implementations • 28 Jun 2021 • Tieyun Qian, Yile Liang, Qing Li, Xuan Ma, Ke Sun, Zhiyong Peng
Improving the recommendation of tail items can promote novelty and bring positive effects to both users and providers, and thus is a desirable property of recommender systems.
1 code implementation • ICCV 2021 • Yining Hong, Qing Li, Song-Chun Zhu, Siyuan Huang
In this work, we study grounded grammar induction of vision and language in a joint learning framework.
no code implementations • 8 Mar 2021 • Qing Li, Xiaojiang Peng, Yu Qiao, Qi Hao
The multi-label learning module leverages a memory feature bank and assigns each image with a multi-label vector based on the similarities between the image and feature bank.
no code implementations • 2 Mar 2021 • Qing Li, Siyuan Huang, Yining Hong, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu
We believe the HINT dataset and the experimental findings are of great interest to the learning community on systematic generalization.
no code implementations • 29 Dec 2020 • Xiu-Shen Wei, Yu-Yan Xu, Yazhou Yao, Jia Wei, Si Xi, Wenyuan Xu, Weidong Zhang, Xiaoxin Lv, Dengpan Fu, Qing Li, Baoying Chen, Haojie Guo, Taolue Xue, Haipeng Jing, Zhiheng Wang, Tianming Zhang, Mingwen Zhang
WebFG 2020 is an international challenge hosted by Nanjing University of Science and Technology, University of Edinburgh, Nanjing University, The University of Adelaide, Waseda University, etc.
no code implementations • 27 Dec 2020 • Yining Hong, Qing Li, Ran Gong, Daniel Ciao, Siyuan Huang, Song-Chun Zhu
Solving algebra story problems remains a challenging task in artificial intelligence, which requires a detailed understanding of real-world situations and a strong mathematical reasoning capability.
1 code implementation • 19 Dec 2020 • Yining Hong, Qing Li, Daniel Ciao, Siyuan Huang, Song-Chun Zhu
To generate more diverse solutions, \textit{tree regularization} is applied to guide the efficient shrinkage and exploration of the solution space, and a \textit{memory buffer} is designed to track and save the discovered various fixes for each problem.
Ranked #1 on
Math Word Problem Solving
on Math23K
(weakly-supervised metric)
no code implementations • 5 Dec 2020 • Tingwei Li, Ruiwen Zhang, Qing Li
To appropriately describe the relations between joints in the skeleton graph, we propose a multi-scale graph strategy, adopting a full-scale graph, part-scale graph, and core-scale graph to capture the local features of each joint and the contour features of important joints.
1 code implementation • COLING 2020 • Changmeng Zheng, Yi Cai, Guanjie Zhang, Qing Li
Entities are the major proportion and build up the topic of text summaries.
no code implementations • COLING 2020 • Haopeng Ren, Yi Cai, Xiaofeng Chen, Guohua Wang, Qing Li
Relation Classification (RC) plays an important role in natural language processing (NLP).
no code implementations • COLING 2020 • Xinhong Chen, Qing Li, JianPing Wang
Existing approaches address the task by first extracting emotion and cause clauses via two binary classifiers separately, and then training another binary classifier to pair them up.
no code implementations • 9 Nov 2020 • Qing Li, Jiasong Zhu, Jun Liu, Rui Cao, Qingquan Li, Sen Jia, Guoping Qiu
Despite the rapid progress in this topic, there are lacking of a comprehensive review, which is needed to summarize the current progress and provide the future directions.
1 code implementation • ECCV 2020 • Xiaojiang Peng, Kai Wang, Zhaoyang Zeng, Qing Li, Jianfei Yang, Yu Qiao
Specifically, this plug-and-play AFM first leverages a \textit{group-to-attend} module to construct groups and assign attention weights for group-wise samples, and then uses a \textit{mixup} module with the attention weights to interpolate massive noisy-suppressed samples.
no code implementations • 30 Sep 2020 • Jun Yang, Qing Li, Yixuan Sun
Tailings ponds are places for storing industrial waste.
no code implementations • 29 Sep 2020 • Yangbin Chen, Yun Ma, Tom Ko, Jian-Ping Wang, Qing Li
MetaMix can be integrated with any of the MAML-based algorithms and learn the decision boundaries generalizing better to new tasks.
1 code implementation • 3 Aug 2020 • Changmeng Zheng, Zhiwei Wu, Tao Wang, Cai Yi, Qing Li
To better exploit visual and textual information in NER, we propose an adversarial gated bilinear attention neural network (AGBAN).
no code implementations • 9 Jul 2020 • Ying Xiang, Qing Li, Yueying Li, Huan Yang, Yuefeng Nie, Hai-Hu Wen
The angle dependent resistivity at a fixed temperature and different magnetic fields cannot be scaled to one curve, which deviates from the prediction of the anisotropic Ginzburg-Landau theory.
Superconductivity Materials Science Strongly Correlated Electrons
no code implementations • ECCV 2020 • Qing Li, Siyuan Huang, Yining Hong, Song-Chun Zhu
Humans can progressively learn visual concepts from easy to hard questions.
no code implementations • ACL 2020 • Jiemin Wu, Yanghui Rao, Zusheng Zhang, Haoran Xie, Qing Li, Fu Lee Wang, Ziye Chen
Mixed counting models that use the negative binomial distribution as the prior can well model over-dispersed and hierarchically dependent random variables; thus they have attracted much attention in mining dispersed document topics.
no code implementations • ACL 2020 • Qingbao Huang, Jielong Wei, Yi Cai, Changmeng Zheng, Junying Chen, Ho-fung Leung, Qing Li
Visual question answering aims to answer the natural language question about a given image.
no code implementations • 27 Jun 2020 • Jun Liu, Qing Li, Rui Cao, Wenming Tang, Guoping Qiu
To the best of our knowledge, this work is the first extremely lightweight neural network trained on monocular video sequences for real-time unsupervised monocular depth estimation, which opens up the possibility of implementing deep learning-based real-time unsupervised monocular depth prediction on low-cost embedded devices.
no code implementations • 23 Jun 2020 • Kanglin Liu, Qing Li, Guoping Qiu
We present PoseGANs, a conditional generative adversarial networks (cGANs) based framework for the implementation of pose-to-image translation.
1 code implementation • ICML 2020 • Qing Li, Siyuan Huang, Yining Hong, Yixin Chen, Ying Nian Wu, Song-Chun Zhu
In this paper, we address these issues and close the loop of neural-symbolic learning by (1) introducing the \textbf{grammar} model as a \textit{symbolic prior} to bridge neural perception and symbolic reasoning, and (2) proposing a novel \textbf{back-search} algorithm which mimics the top-down human-like learning procedure to propagate the error through the symbolic reasoning module efficiently.
no code implementations • 17 May 2020 • Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jian-Ping Wang, Jiliang Tang, Qing Li
In this work, we present our framework CopyAttack, which is a reinforcement learning based black-box attack method that harnesses real users from a source domain by copying their profiles into the target domain with the goal of promoting a subset of items.
no code implementations • 22 Feb 2020 • Xianming Li, Zongxi Li, Yingbin Zhao, Haoran Xie, Qing Li
The dominant text classification studies focus on training classifiers using textual instances only or introducing external knowledge (e. g., hand-craft features and domain expert knowledge).
no code implementations • 28 Dec 2019 • Tieyun Qian, Yile Liang, Qing Li
More importantly, for a cold start user/item that does not have any interactions, such methods are unable to learn the preference embedding of the user/item since there is no link to this user/item in the graph.
no code implementations • 23 Dec 2019 • Wenkai Han, Chenglu Wen, Cheng Wang, Xin Li, Qing Li
Point2Node can dynamically explore correlation among all graph nodes from different levels, and adaptively aggregate the learned features.
1 code implementation • 7 Oct 2019 • Ziang Zhou, Jieming Shi, Shengzhong Zhang, Zengfeng Huang, Qing Li
However, under extreme cases when very few labels are available (e. g., 1 labeled node per class), GNNs suffer from severe performance degradation.
no code implementations • 28 Sep 2019 • Qing Li, Xiaojiang Peng, Yu Qiao, Qiang Peng
In this paper, instead of using a pre-defined graph which is inflexible and may be sub-optimal for multi-label classification, we propose the A-GCN, which leverages the popular Graph Convolutional Networks with an Adaptive label correlation graph to model label dependencies.
no code implementations • ICCV 2019 • Nilavra Bhattacharya, Qing Li, Danna Gurari
Visual question answering is the task of returning the answer to a question about an image.
no code implementations • 26 Jul 2019 • Qing Li, Xiaojiang Peng, Liangliang Cao, Wenbin Du, Hao Xing, Yu Qiao
Instead of collecting product images by labor-and time-intensive image capturing, we take advantage of the web and download images from the reviews of several e-commerce websites where the images are casually captured by consumers.
no code implementations • 16 Jul 2019 • Wenqi Fan, Yao Ma, Dawei Yin, Jian-Ping Wang, Jiliang Tang, Qing Li
Meanwhile, most of these models treat neighbors' information equally without considering the specific recommendations.
1 code implementation • 30 May 2019 • Wenqi Fan, Tyler Derr, Yao Ma, JianPing Wang, Jiliang Tang, Qing Li
Recent years have witnessed rapid developments on social recommendation techniques for improving the performance of recommender systems due to the growing influence of social networks to our daily life.
4 code implementations • 10 May 2019 • Xudong Mao, Yun Ma, Zhenguo Yang, Yangbin Chen, Qing Li
Existing methods only impose the locally-Lipschitz constraint around the training points while miss the other areas, such as the points in-between training data.
no code implementations • CVPR 2019 • Qing Li, Shaoyang Chen, Cheng Wang, Xin Li, Chenglu Wen, Ming Cheng, Jonathan Li
We present a novel deep convolutional network pipeline, LO-Net, for real-time lidar odometry estimation.
1 code implementation • 4 Apr 2019 • Zhenguo Yang, Zehang Lin, Min Cheng, Qing Li, Wenyin Liu
In this work, we construct and release a multi-domain and multi-modality event dataset (MMED), containing 25, 165 textual news articles collected from hundreds of news media sites (e. g., Yahoo News, Google News, CNN News.)
1 code implementation • 22 Mar 2019 • Gregory Moille, Qing Li, Xiyuan Lu, Kartik Srinivasan
We present the development of pyLLE, a freely accessible and cross-platform Lugiato-Lefever equation solver programmed in Python and Julia and optimized for the simulation of microresonator frequency combs.
Mathematical Software Optics
7 code implementations • 19 Feb 2019 • Wenqi Fan, Yao Ma, Qing Li, Yuan He, Eric Zhao, Jiliang Tang, Dawei Yin
These advantages of GNNs provide great potential to advance social recommendation since data in social recommender systems can be represented as user-user social graph and user-item graph; and learning latent factors of users and items is the key.
Ranked #3 on
Recommendation Systems
on Epinions
(using extra training data)
no code implementations • 15 Feb 2019 • Rui Cao, Qian Zhang, Jiasong Zhu, Qing Li, Qingquan Li, Bozhi Liu, Guoping Qiu
With the rapid growing of remotely sensed imagery data, there is a high demand for effective and efficient image retrieval tools to manage and exploit such data.
1 code implementation • 14 Jan 2019 • Zhenguo Yang, Zehang Lin, Peipei Kang, Jianming Lv, Qing Li, Wenyin Liu
In this paper, we propose to learn shared semantic space with correlation alignment (${S}^{3}CA$) for multimodal data representations, which aligns nonlinear correlations of multimodal data distributions in deep neural networks designed for heterogeneous data.
no code implementations • 4 Jan 2019 • Qing Li, Jiasong Zhu, Rui Cao, Ke Sun, Jonathan M. Garibaldi, Qingquan Li, Bozhi Liu, Guoping Qiu
6DOF camera relocalization is an important component of autonomous driving and navigation.
1 code implementation • 26 Dec 2018 • Yangbin Chen, Tom Ko, Lifeng Shang, Xiao Chen, Xin Jiang, Qing Li
In this paper, we investigate the feasibility of applying few-shot learning algorithms to a speech task.
no code implementations • 13 Jul 2018 • Lige Zhang, Xiaolin Qin, Qing Li, Haoyue Peng, Yu Hou
Compared with various schemes, the simulation results of the proposed scheme are better than that of the reference schemes in visual quality and time consumption.
1 code implementation • 7 May 2018 • Xudong Mao, Qing Li
To tackle this problem, we propose Regularized Conditional GAN (RegCGAN) which is capable of learning to generate corresponding images in the absence of paired training data.
no code implementations • ECCV 2018 • Qing Li, Qingyi Tao, Shafiq Joty, Jianfei Cai, Jiebo Luo
Most existing works in visual question answering (VQA) are dedicated to improving the accuracy of predicted answers, while disregarding the explanations.
1 code implementation • CVPR 2018 • Jianming Lv, Weihang Chen, Qing Li, Can Yang
Most of the proposed person re-identification algorithms conduct supervised training and testing on single labeled datasets with small size, so directly deploying these trained models to a large-scale real-world camera network may lead to poor performance due to underfitting.
no code implementations • CVPR 2018 • Danna Gurari, Qing Li, Abigale J. Stangl, Anhong Guo, Chi Lin, Kristen Grauman, Jiebo Luo, Jeffrey P. Bigham
The study of algorithms to automatically answer visual questions currently is motivated by visual question answering (VQA) datasets constructed in artificial VQA settings.
no code implementations • EMNLP 2018 • Qing Li, Jianlong Fu, Dongfei Yu, Tao Mei, Jiebo Luo
Most existing approaches adopt the pipeline of representing an image via pre-trained CNNs, and then using the uninterpretable CNN features in conjunction with the question to predict the answer.
2 code implementations • 18 Dec 2017 • Xudong Mao, Qing Li, Haoran Xie, Raymond Y. K. Lau, Zhen Wang, Stephen Paul Smolley
To overcome such a problem, we propose in this paper the Least Squares Generative Adversarial Networks (LSGANs) which adopt the least squares loss for both the discriminator and the generator.
no code implementations • ICCV 2017 • Yang Song, Fan Zhang, Qing Li, Heng Huang, Lauren J. O'Donnell, Weidong Cai
Texture classification has been extensively studied in computer vision.
no code implementations • 5 Jul 2017 • Xudong Mao, Qing Li, Haoran Xie
Recently, several methods based on generative adversarial network (GAN) have been proposed for the task of aligning cross-domain images or learning a joint distribution of cross-domain images.
no code implementations • ACL 2017 • Xueying Zhan, Yao-Wei Wang, Yanghui Rao, Haoran Xie, Qing Li, Fu Lee Wang, Tak-Lam Wong
This paper focuses on the task of noisy label aggregation in social media, where users with different social or culture backgrounds may annotate invalid or malicious tags for documents.
Cultural Vocal Bursts Intensity Prediction
Image Classification
+2
no code implementations • 30 Jun 2017 • Qing Li, Qiang Peng, Chuan Yan
In this paper, we propose a special framework, which is the multiple VLAD encoding method with the CNNs features for image classification.
no code implementations • 23 Nov 2016 • Jianming Lv, Qing Li, Xintong Wang
Precise destination prediction of taxi trajectories can benefit many intelligent location based services such as accurate ad for passengers.
23 code implementations • ICCV 2017 • Xudong Mao, Qing Li, Haoran Xie, Raymond Y. K. Lau, Zhen Wang, Stephen Paul Smolley
To overcome such a problem, we propose in this paper the Least Squares Generative Adversarial Networks (LSGANs) which adopt the least squares loss function for the discriminator.
no code implementations • CVPR 2015 • Yang Song, Weidong Cai, Qing Li, Fan Zhang, David Dagan Feng, Heng Huang
Texture, as a fundamental characteristic of objects, has attracted much attention in computer vision research.
no code implementations • 25 Nov 2014 • Xiaosong Hu, Wen Zhu, Qing Li
Nowadays, online clothes-selling business has become popular and extremely attractive because of its convenience and cheap-and-fine price.