no code implementations • COLING 2022 • Jiayi Liu, Wei Wei, Zhixuan Chu, Xing Gao, Ji Zhang, Tan Yan, Yulin kang
Although the Conditional Variational Auto-Encoder (CVAE) model can generate more diversified responses than the traditional Seq2Seq model, the responses often have low relevance with the input words or are illogical with the question.
no code implementations • 9 Mar 2023 • Luxuan Yang, Ting Gao, Min Dai, Yubin Lu, Wei Wei, Cheng Fang, Yufu Lan, Jinqiao Duan
One is that our proposed method can automatically generate correct labels for noisy time series patterns, while at the same time, the method is capable of boosting classification performance on this new labeled dataset.
1 code implementation • 2 Mar 2023 • Mengru Chen, Chao Huang, Lianghao Xia, Wei Wei, Yong Xu, Ronghua Luo
In light of this, we propose a Heterogeneous Graph Contrastive Learning (HGCL), which is able to incorporate heterogeneous relational semantics into the user-item interaction modeling with contrastive learning-enhanced knowledge transfer across different views.
1 code implementation • 21 Feb 2023 • Wei Wei, Chao Huang, Lianghao Xia, Chuxu Zhang
The online emergence of multi-modal sharing platforms (eg, TikTok, Youtube) is powering personalized recommender systems to incorporate various modalities (eg, visual, textual and acoustic) into the latent user representations.
no code implementations • 30 Dec 2022 • Rui Xie, Wei Wei, Yue Chen
In this paper, a bi-objective distributionally robust optimization (DRO) model is proposed to determine the capacities of wind power generation and ESSs considering the wake effect.
no code implementations • 28 Nov 2022 • Shuo Liang, Wei Wei, Xian-Ling Mao, Yuanyuan Fu, Rui Fang, Dangyang Chen
Hence, we propose a novel approach, Span TAgging and Greedy infErence (STAGE), to extract sentiment triplets in span-level, where each span may consist of multiple words and play different roles simultaneously.
no code implementations • 15 Nov 2022 • Zilong Wang, Yichao Zhou, Wei Wei, Chen-Yu Lee, Sandeep Tata
Understanding visually-rich business documents to extract structured data and automate business workflows has been receiving attention both in academia and industry.
no code implementations • 19 Oct 2022 • Yucong Lin, Hongming Xiao, Jiani Liu, Zichao Lin, Keming Lu, Feifei Wang, Wei Wei
Knowledge-enhanced methods that take advantage of auxiliary knowledge graphs recently emerged in relation extraction, and they surpass traditional text-based relation extraction methods.
no code implementations • 17 Oct 2022 • Xiaofei Wen, Wei Wei, Xian-Ling Mao
To address the problem, in this paper we propose a novel approach, named Sequential Global Topic Attention (SGTA) to exploit topic transition over all conversations in a subtle way for better modeling post-to-response topic-transition and guiding the response generation to the current conversation.
no code implementations • 17 Oct 2022 • Ruihan Zhang, Wei Wei, Xian-Ling Mao, Rui Fang, Dangyang Chen
Conventional event detection models under supervised learning settings suffer from the inability of transfer to newly-emerged event types owing to lack of sufficient annotations.
1 code implementation • 11 Oct 2022 • Yuxiang Nie, Heyan Huang, Wei Wei, Xian-Ling Mao
The proposed model mainly focuses on the evidence selection phase of long document question answering.
no code implementations • 2 Oct 2022 • Xue Liu, Dan Sun, Xiaobo Cao, Hao Ye, Wei Wei
Graph embedding provides a feasible methodology to conduct pattern classification for graph-structured data by mapping each data into the vectorial space.
1 code implementation • 23 Sep 2022 • Rong-Cheng Tu, Xian-Ling Mao, Kevin Qinghong Lin, Chengfei Cai, Weize Qin, Hongfa Wang, Wei Wei, Heyan Huang
Recently, to improve the unsupervised image retrieval performance, plenty of unsupervised hashing methods have been proposed by designing a semantic similarity matrix, which is based on the similarities between image features extracted by a pre-trained CNN model.
no code implementations • 20 Sep 2022 • Jiayi Liu, Wei Wei, Zhixuan Chu, Xing Gao, Ji Zhang, Tan Yan, Yulin kang
Although the Conditional Variational AutoEncoder (CVAE) model can generate more diversified responses than the traditional Seq2Seq model, the responses often have low relevance with the input words or are illogical with the question.
no code implementations • 27 Aug 2022 • Ziyang Wang, Huoyu Liu, Wei Wei, Yue Hu, Xian-Ling Mao, Shaojian He, Rui Fang, Dangyang Chen
Different from the previous contrastive learning-based methods for SR, MCLSR learns the representations of users and items through a cross-view contrastive learning paradigm from four specific views at two different levels (i. e., interest- and feature-level).
1 code implementation • 23 Aug 2022 • Yifan Liu, Wei Wei, Jiayi Liu, Xianling Mao, Rui Fang, Dangyang Chen
Endowing chatbots with a consistent personality plays a vital role for agents to deliver human-like interactions.
1 code implementation • 22 Aug 2022 • Ding Zou, Wei Wei, Ziyang Wang, Xian-Ling Mao, Feida Zhu, Rui Fang, Dangyang Chen
Specifically, we first construct local and non-local graphs for user/item in KG, exploring more KG facts for KGR.
1 code implementation • 10 Aug 2022 • Zezhi Shao, Zhao Zhang, Fei Wang, Wei Wei, Yongjun Xu
These results suggest that we can design efficient and effective models as long as they solve the indistinguishability of samples, without being limited to STGNNs.
1 code implementation • 17 Jul 2022 • Lei Zhang, Yuxuan Sun, Wei Wei
Instead of directly exploiting the pseudo labels produced by the teacher detector, we take the first attempt at reducing their deviation from ground truth using dual polishing learning, where two differently structured polishing networks are elaborately developed and trained using synthesized paired pseudo labels and the corresponding ground truth for categories and bounding boxes on the given annotated objects, respectively.
1 code implementation • 14 Jul 2022 • Zhiqiang Lang, Chongxing Song, Lei Zhang, Wei Wei
Binary neural network (BNN) provides a promising solution to deploy parameter-intensive deep single image super-resolution (SISR) models onto real devices with limited storage and computational resources.
no code implementations • 20 Jun 2022 • Ruizhi Zhang, Qiaozi Wang, Qiming Yang, Wei Wei
Temporal network link prediction is an important task in the field of network science, and has a wide range of applications in practical scenarios.
1 code implementation • 18 Jun 2022 • Ziyang Wang, Wei Wei, Chenwei Xu, Jun Xu, Xian-Ling Mao
Existing studies on person-job fit, however, mainly focus on calculating the similarity between the candidate resumes and the job postings on the basis of their contents, without taking the recruiters' experience (i. e., historical successful recruitment records) into consideration.
1 code implementation • 18 Jun 2022 • Zezhi Shao, Zhao Zhang, Wei Wei, Fei Wang, Yongjun Xu, Xin Cao, Christian S. Jensen
However, intuitively, traffic data encompasses two different kinds of hidden time series signals, namely the diffusion signals and inherent signals.
Ranked #3 on
Traffic Prediction
on METR-LA
no code implementations • 11 Jun 2022 • Jingcheng Zhou, Wei Wei, Xing Li, Bowen Pang, Zhiming Zheng
Deep learning utilizing deep neural networks (DNNs) has achieved a lot of success recently in many important areas such as computer vision, natural language processing, and recommendation systems.
no code implementations • 11 May 2022 • Yu-Ming Shang, Heyan Huang, Xin Sun, Wei Wei, Xian-Ling Mao
Extracting relational triples from unstructured text is an essential task in natural language processing and knowledge graph construction.
1 code implementation • 6 May 2022 • Weiran Pan, Wei Wei, Feida Zhu
Fine-grained entity typing (FET) aims to assign proper semantic types to entity mentions according to their context, which is a fundamental task in various entity-leveraging applications.
1 code implementation • 5 May 2022 • Yuhang Liu, Wei Wei, Daowan Peng, Feida Zhu
In recent years, the pre-training-then-fine-tuning paradigm has yielded immense success on a wide spectrum of cross-modal tasks, such as visual question answering (VQA), in which a visual-language (VL) model is first optimized via self-supervised task objectives, e. g., masked language modeling (MLM) and image-text matching (ITM), and then fine-tuned to adapt to downstream task (e. g., VQA) via a brand-new objective function, e. g., answer prediction.
no code implementations • 5 May 2022 • Wei Wei, Huang Hengguan, Gu Xiangming, Wang Hao, Wang Ye
Content mismatch usually occurs when data from one modality is translated to another, e. g. language learners producing mispronunciations (errors in speech) when reading a sentence (target text) aloud.
no code implementations • 3 May 2022 • Yuxiang Feng, Weilin Xie, Yinxia Meng, Jiang Yang, Qiang Yang, Yan Ren, Tianwai Bo, Zhongwei Tan, Wei Wei, Yi Dong
Coherent fading has been regarded as a critical issue in phase-sensitive optical frequency domain reflectometry ({\phi}-OFDR) based distributed fiber-optic sensing.
1 code implementation • 28 Apr 2022 • Qiming Yang, Wei Wei, Ruizhi Zhang, Bowen Pang, Xiangnan Feng
To address this issue, in this paper, we design a new community attribute based link prediction strategy HAP and propose a two-step community enhancement algorithm with automatic evolution process based on HAP.
1 code implementation • 19 Apr 2022 • Ding Zou, Wei Wei, Xian-Ling Mao, Ziyang Wang, Minghui Qiu, Feida Zhu, Xin Cao
Different from traditional contrastive learning methods which generate two graph views by uniform data augmentation schemes such as corruption or dropping, we comprehensively consider three different graph views for KG-aware recommendation, including global-level structural view, local-level collaborative and semantic views.
1 code implementation • ACL 2022 • Heqi Zheng, Xiao Zhang, Zewen Chi, Heyan Huang, Tan Yan, Tian Lan, Wei Wei, Xian-Ling Mao
In this paper, we propose XPR, a cross-lingual phrase retriever that extracts phrase representations from unlabeled example sentences.
1 code implementation • Findings (ACL) 2022 • Shuo Liang, Wei Wei, Xian-Ling Mao, Fei Wang, Zhiyong He
Aspect-based sentiment analysis (ABSA) is a fine-grained sentiment analysis task that aims to align aspects and corresponding sentiments for aspect-specific sentiment polarity inference.
no code implementations • 31 Mar 2022 • Wei Wei, Xiaoli Chen, Ting Gao, Jinqiao Duan
One of the challenges to calculate the most likely transition path for stochastic dynamical systems under non-Gaussian L\'evy noise is that the associated rate function can not be explicitly expressed by paths.
1 code implementation • 23 Feb 2022 • Sen Zhao, Wei Wei, Ding Zou, Xianling Mao
Specifically, MIDGN disentangles the user's intents from two different perspectives, respectively: 1) In the global level, MIDGN disentangles the user's intent coupled with inter-bundle items; 2) In the Local level, MIDGN disentangles the user's intent coupled with items within each bundle.
no code implementations • 20 Feb 2022 • He Meng, Hongjie Jia, Tao Xu, Wei Wei, Yuhan Wu, Lemeng Liang, Shuqi Cai, Zuozheng Liu, Rujing Wang
The international mega-event, such as the Winter Olympic Game, has been considered as one of the most carbon intensive activities worldwide.
1 code implementation • 17 Feb 2022 • Wei Wei, Chao Huang, Lianghao Xia, Yong Xu, Jiashu Zhao, Dawei Yin
In addition, to capture the diverse multi-behavior patterns, we design a contrastive meta network to encode the customized behavior heterogeneity for different users.
no code implementations • 1 Feb 2022 • Wei Wei, Jingjing Wang, Jun Du, Zhengru Fang, Chunxiao Jiang, Yong Ren
Simulations show that underwater disturbances have a large impact on the system considering communication delay.
no code implementations • 23 Jan 2022 • Chenghao Fan, Ziao Li, Wei Wei
(2) Style misclassification.
no code implementations • 22 Jan 2022 • Chaofan Sun, Ken Seng Tan, Wei Wei
In contrast to the risk-free closeout, the replacement closeout renders a nonlinear valuation system, which constitutes the major difficulty in the valuation of the counterparty credit risk.
no code implementations • 14 Dec 2021 • Wei-Cheng Tseng, Wei Wei, Da-Cheng Juan, Min Sun
The number of agents can grow or an environment sometimes needs to interact with a changing number of agents in real-world scenarios.
1 code implementation • 12 Nov 2021 • Yu Zhang, Wei Wei, Binxuan Huang, Kathleen M. Carley, Yan Zhang
Real-time location inference of social media users is the fundamental of some spatial applications such as localized search and event detection.
no code implementations • 28 Oct 2021 • Lifan Yuan, Yichi Zhang, Yangyi Chen, Wei Wei
In this paper, we instantiate our framework with an attack algorithm named Textual Projected Gradient Descent (T-PGD).
no code implementations • 29 Sep 2021 • Ling Cheng, Wei Wei, Feida Zhu, Yong liu, Chunyan Miao
However, those fusion-based models, they are still criticized for the lack of geometry information for inter and intra attention refinement.
no code implementations • 26 Sep 2021 • Peng Yang, Feng Liu, Wei Wei, Zhaojian Wang
Estimating the stability boundary is a fundamental and challenging problem in transient stability studies.
1 code implementation • Findings (EMNLP) 2021 • Weiran Pan, Wei Wei, Xian-Ling Mao
Knowledge graph entity typing aims to infer entities' missing types in knowledge graphs which is an important but under-explored issue.
no code implementations • 13 Sep 2021 • Yue Chen, Wei Wei, Cheng Wang, Miadreza Shafie-khah, João P. S. Catalão
Large solar power stations usually locate in remote areas and connect to the main grid via a long transmission line.
1 code implementation • EMNLP 2021 • Yangyi Chen, Jin Su, Wei Wei
Furthermore, we propose a reinforcement-learning based method to train a multi-granularity attack agent through behavior cloning with the expert knowledge from our MAYA algorithm to further reduce the query times.
no code implementations • 31 Aug 2021 • Zezhi Shao, Yongjun Xu, Wei Wei, Fei Wang, Zhao Zhang, Feida Zhu
Graph neural networks for heterogeneous graph embedding is to project nodes into a low-dimensional space by exploring the heterogeneity and semantics of the heterogeneous graph.
no code implementations • 13 Jul 2021 • Xue Liu, Dan Sun, Wei Wei
Considering the preservation of graph entropy, we propose an effective strategy to generate randomly perturbed training data but maintain both graph topology and graph entropy.
no code implementations • 11 Jul 2021 • Xiangzhu Meng, Wei Wei, Wenzhe Liu
LRC-MCF aims to explore the diversity, geometric, consensus and complementary information among different views, by capturing the locality relationship information and the common similarity relationships among multiple views.
no code implementations • 2 Jul 2021 • Jerrick Liu, Nathan Inkawhich, Oliver Nina, Radu Timofte, Sahil Jain, Bob Lee, Yuru Duan, Wei Wei, Lei Zhang, Songzheng Xu, Yuxuan Sun, Jiaqi Tang, Mengru Ma, Gongzhe Li, Xueli Geng, Huanqia Cai, Chengxue Cai, Sol Cummings, Casian Miron, Alexandru Pasarica, Cheng-Yen Yang, Hung-Min Hsu, Jiarui Cai, Jie Mei, Chia-Ying Yeh, Jenq-Neng Hwang, Michael Xin, Zhongkai Shangguan, Zihe Zheng, Xu Yifei, Lehan Yang, Kele Xu, Min Feng
In this paper, we introduce the first Challenge on Multi-modal Aerial View Object Classification (MAVOC) in conjunction with the NTIRE 2021 workshop at CVPR.
1 code implementation • 9 Jun 2021 • Ziyang Wang, Wei Wei, Gao Cong, Xiao-Li Li, Xian-Ling Mao, Minghui Qiu
In GCE-GNN, we propose a novel global-level item representation learning layer, which employs a session-aware attention mechanism to recursively incorporate the neighbors' embeddings of each node on the global graph.
no code implementations • 6 Jun 2021 • Wei Wei, Jiayi Liu, Xianling Mao, Guibing Guo, Feida Zhu, Pan Zhou, Yuchong Hu
The consistency of a response to a given post at semantic-level and emotional-level is essential for a dialogue system to deliver human-like interactions.
no code implementations • 2 Jun 2021 • Zanbo Wang, Wei Wei, Xianling Mao, Shanshan Feng, Pan Zhou, Zhiyong He, Sheng Jiang
To this end, we propose a model called Global Context enhanced Document-level NER (GCDoc) to leverage global contextual information from two levels, i. e., both word and sentence.
1 code implementation • 14 May 2021 • Jun Shi, Huite Yi, Shulan Ruan, Zhaohui Wang, Xiaoyu Hao, Hong An, Wei Wei
The ongoing global pandemic of Coronavirus Disease 2019 (COVID-19) poses a serious threat to public health and the economy.
no code implementations • 8 May 2021 • Hongyan Cai, Danhong Chen, Yunfei Peng, Wei Wei
By studying the solvability of the Riccati equation, we show the existence and uniqueness of the linear equilibrium for the time-inconsistent LQ problem.
no code implementations • 6 Apr 2021 • Kun Qian, Wei Wei, Zhou Yu
The most recent researches on domain adaption focus on giving the model a better initialization, rather than optimizing the adaptation process.
no code implementations • 31 Mar 2021 • Jingcheng Zhou, Wei Wei, Zhiming Zheng
First-order methods like stochastic gradient descent(SGD) are recently the popular optimization method to train deep neural networks (DNNs), but second-order methods are scarcely used because of the overpriced computing cost in getting the high-order information.
no code implementations • 24 Mar 2021 • Wei Wei, Li Guan, Yue Liu, Hao Kang, Haoxiang Li, Ying Wu, Gang Hua
By the proposed physical regularization, our method can generate HDRs which are not only visually appealing but also physically plausible.
1 code implementation • CVPR 2021 • Daizong Liu, Xiaoye Qu, Jianfeng Dong, Pan Zhou, Yu Cheng, Wei Wei, Zichuan Xu, Yulai Xie
This paper addresses the problem of temporal sentence grounding (TSG), which aims to identify the temporal boundary of a specific segment from an untrimmed video by a sentence query.
1 code implementation • 20 Mar 2021 • Shuyu Lu, Ruoyu Chen, Wei Wei, Xinghua Lu
We examined whether machine learning models, more specifically the XGBoost model, can accurately predict patient stage based on EHR, and we further applied the SHapley Additive exPlanations (SHAP) framework to identify informative features and their interpretations.
1 code implementation • EMNLP 2020 • Zhengzhong Liu, Guanxiong Ding, Avinash Bukkittu, Mansi Gupta, Pengzhi Gao, Atif Ahmed, Shikun Zhang, Xin Gao, Swapnil Singhavi, Linwei Li, Wei Wei, Zecong Hu, Haoran Shi, Haoying Zhang, Xiaodan Liang, Teruko Mitamura, Eric P. Xing, Zhiting Hu
Empirical natural language processing (NLP) systems in application domains (e. g., healthcare, finance, education) involve interoperation among multiple components, ranging from data ingestion, human annotation, to text retrieval, analysis, generation, and visualization.
1 code implementation • EMNLP 2021 • Haoming Jiang, Bo Dai, Mengjiao Yang, Tuo Zhao, Wei Wei
An ideal environment for evaluating dialog systems, also known as the Turing test, needs to involve human interaction, which is usually not affordable for large-scale experiments.
no code implementations • 2 Feb 2021 • Xue Liu, Wei Wei, Xiangnan Feng, Xiaobo Cao, Dan Sun
Most existing popular methods for learning graph embedding only consider fixed-order global structural features and lack structures hierarchical representation.
no code implementations • 11 Jan 2021 • Wei Wei, Qiao Huang, Jinqiao Duan
We obtain sample-path large deviations for a class of one-dimensional stochastic differential equations with bounded drifts and heavy-tailed L\'evy processes.
Probability 60H10, 60F10, 60J76
no code implementations • 2 Jan 2021 • Xing Li, Wei Wei, Xiangnan Feng, Zhiming Zheng
Graphs are often used to organize data because of their simple topological structure, and therefore play a key role in machine learning.
1 code implementation • 2 Jan 2021 • Houjin Yu, Xian-Ling Mao, Zewen Chi, Wei Wei, Heyan Huang
Recently, it has attracted much attention to build reliable named entity recognition (NER) systems using limited annotated data.
Ranked #3 on
Named Entity Recognition (NER)
on SciERC
(using extra training data)
Low Resource Named Entity Recognition
named-entity-recognition
+2
no code implementations • ICCV 2021 • Lei Fan, Peixi Xiong, Wei Wei, Ying Wu
To address this demand, in this paper, we propose a unified framework towards Few-sample Lifelong Active Recognition (FLAR), which aims at performing active recognition on progressively arising novel categories that only have few training samples.
no code implementations • 1 Jan 2021 • Rongmei Lin, Hanjun Dai, Li Xiong, Wei Wei
We propose a generative fairness teaching framework that provides a model with not only real samples but also synthesized samples to compensate the data biases during training.
no code implementations • 1 Jan 2021 • Pei-Hsin Wang, Sheng-Iou Hsieh, Shih-Chieh Chang, Yu-Ting Chen, Da-Cheng Juan, Jia-Yu Pan, Wei Wei
Current practices to apply temperature scaling assume either a fixed, or a manually-crafted dynamically changing schedule.
no code implementations • 25 Dec 2020 • Pei-Hsin Wang, Sheng-Iou Hsieh, Shih-Chieh Chang, Yu-Ting Chen, Jia-Yu Pan, Wei Wei, Da-Chang Juan
Temperature scaling has been widely used as an effective approach to control the smoothness of a distribution, which helps the model performance in various tasks.
no code implementations • 21 Dec 2020 • Tian Lan, Xian-Ling Mao, Zhipeng Zhao, Wei Wei, Heyan Huang
Since the pre-trained language models are widely used, retrieval-based open-domain dialog systems, have attracted considerable attention from researchers recently.
1 code implementation • 17 Dec 2020 • Tian Lan, Xian-Ling Mao, Xiaoyan Gao, Wei Wei, Heyan Huang
Specifically, in our proposed DSHC model, a hashing optimizing module that consists of two autoencoder models is stacked on a trained dense representation model, and three loss functions are designed to optimize it.
no code implementations • 15 Dec 2020 • E. A. Huerta, Asad Khan, Xiaobo Huang, Minyang Tian, Maksim Levental, Ryan Chard, Wei Wei, Maeve Heflin, Daniel S. Katz, Volodymyr Kindratenko, Dawei Mu, Ben Blaiszik, Ian Foster
The development of reusable artificial intelligence (AI) models for wider use and rigorous validation by the community promises to unlock new opportunities in multi-messenger astrophysics.
no code implementations • 13 Dec 2020 • Yanqi Liu, Zhigang Li, Wei Wei, Jiehui Zheng, Hongcai Zhang
State-of-the-art dispatchable region (DR) research has studied how system operational constraints influence the DR but has seldom considered the effect of the uncertainty features of RPG outputs.
no code implementations • 10 Dec 2020 • Ziyang Wang, Wei Wei, Xian-Ling Mao, Xiao-Li Li, Shanshan Feng
In RNMSR, we propose to learn the user preference from both instance-level and group-level, respectively: (i) instance-level, which employs GNNs on a similarity-based item-pairwise session graph to capture the users' preference in instance-level.
no code implementations • 10 Dec 2020 • Daizong Liu, Shuangjie Xu, Xiao-Yang Liu, Zichuan Xu, Wei Wei, Pan Zhou
To capture temporal information from previous frames, we use a memory network to refine the mask of current frame by retrieving historic masks in a temporal graph.
One-shot visual object segmentation
Semantic Segmentation
+1
no code implementations • 9 Dec 2020 • Honghao Gao, Xuejie Wang, Xiaojin Ma, Wei Wei, Shahid Mumtaz
First, we discuss the task dependency model, task priority model, energy consumption model, and average latency from the perspective of server clusters and multidependence on mobile tasks.
Decision Making
Edge-computing
+1
Distributed, Parallel, and Cluster Computing
Multiagent Systems
no code implementations • 3 Dec 2020 • Jiangtao Nie, Lei Zhang, Wei Wei, Zhiqiang Lang, Yanning Zhang
One of the main reason comes from the fact that the predefined degeneration models (e. g. blur in spatial domain) utilized by most HSI SR methods often exist great discrepancy with the real one, which results in these deep models overfit and ultimately degrade their performance on real data.
no code implementations • 3 Dec 2020 • Lei Zhang, Fei Zhou, Wei Wei, Yanning Zhang
To mitigate this problem, we present a novel deep metric meta-generation method that turns to an orthogonal direction, ie, learning to adaptively generate a specific metric for a new FSL task based on the task description (eg, a few labelled samples).
no code implementations • NeurIPS 2020 • Hung-Jen Chen, An-Chieh Cheng, Da-Cheng Juan, Wei Wei, Min Sun
To preserve the knowledge we learn from previous instances, we proposed a method to protect the path by restricting the gradient updates of one instance from overriding past updates calculated from previous instances if these instances are not similar.
no code implementations • NeurIPS 2020 • Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister
Finding the k largest or smallest elements from a collection of scores, i. e., top-k operation, is an important model component widely used in information retrieval, machine learning, and data mining.
no code implementations • 20 Nov 2020 • Ziyang Wang, Wei Wei, Gao Cong, Xiao-Li Li, Xian-Ling Mao, Minghui Qiu, Shanshan Feng
Based on BGNN, we propose a novel approach, called Session-based Recommendation with Global Information (SRGI), which infers the user preferences via fully exploring global item-transitions over all sessions from two different perspectives: (i) Fusion-based Model (SRGI-FM), which recursively incorporates the neighbor embeddings of each node on global graph into the learning process of session level item representation; and (ii) Constrained-based Model (SRGI-CM), which treats the global-level item-transition information as a constraint to ensure the learned item embeddings are consistent with the global item-transition.
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Chieh-Yang Chen, Pei-Hsin Wang, Shih-Chieh Chang, Da-Cheng Juan, Wei Wei, Jia-Yu Pan
Despite recent success in neural task-oriented dialogue systems, developing such a real-world system involves accessing large-scale knowledge bases (KBs), which cannot be simply encoded by neural approaches, such as memory network mechanisms.
no code implementations • 16 Nov 2020 • Ziyang Wang, Wei Wei, Xian-Ling Mao, Guibing Guo, Pan Zhou, Shanshan Feng
Due to the huge commercial interests behind online reviews, a tremendousamount of spammers manufacture spam reviews for product reputation manipulation.
no code implementations • 15 Nov 2020 • Wei Wei, Jiayi Liu, Xianling Mao, Guibin Guo, Feida Zhu, Pan Zhou, Yuchong Hu, Shanshan Feng
The consistency of a response to a given post at semantic-level and emotional-level is essential for a dialogue system to deliver human-like interactions.
no code implementations • 13 Nov 2020 • Zhiyong He, Zanbo Wang, Wei Wei, Shanshan Feng, Xianling Mao, Sheng Jiang
Sequence labeling (SL) is a fundamental research problem encompassing a variety of tasks, e. g., part-of-speech (POS) tagging, named entity recognition (NER), text chunking, etc.
no code implementations • 6 Nov 2020 • Rong-Cheng Tu, Xian-Ling Mao, Rongxin Tu, Binbin Bian, Wei Wei, Heyan Huang
Finally, by minimizing the novel \textit{margin-dynamic-softmax loss}, the modality-specific hashing networks can be trained to generate hash codes which can simultaneously preserve the cross-modal similarity and abundant semantic information well.
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Ming Zhu, Aman Ahuja, Da-Cheng Juan, Wei Wei, Chandan K. Reddy
To this end, we present MASH-QA, a Multiple Answer Spans Healthcare Question Answering dataset from the consumer health domain, where answers may need to be excerpted from multiple, non-consecutive parts of text spanned across a long document.
no code implementations • 26 Oct 2020 • Jia-Nan Guo, Xian-Ling Mao, Shu-Yang Lin, Wei Wei, Heyan Huang
However, nearly all the existing network embedding based methods are hard to capture the actual category features of a node because of the linearly inseparable problem in low-dimensional space; meanwhile they cannot incorporate simultaneously network structure information and node label information into network embedding.
no code implementations • NeurIPS Workshop LMCA 2020 • Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister
The top-$k$ operation, i. e., finding the $k$ largest or smallest elements from a collection of scores, is an important model component, which is widely used in information retrieval, machine learning, and data mining.
3 code implementations • 15 Sep 2020 • Kai Zhang, Martin Danelljan, Yawei Li, Radu Timofte, Jie Liu, Jie Tang, Gangshan Wu, Yu Zhu, Xiangyu He, Wenjie Xu, Chenghua Li, Cong Leng, Jian Cheng, Guangyang Wu, Wenyi Wang, Xiaohong Liu, Hengyuan Zhao, Xiangtao Kong, Jingwen He, Yu Qiao, Chao Dong, Maitreya Suin, Kuldeep Purohit, A. N. Rajagopalan, Xiaochuan Li, Zhiqiang Lang, Jiangtao Nie, Wei Wei, Lei Zhang, Abdul Muqeet, Jiwon Hwang, Subin Yang, JungHeum Kang, Sung-Ho Bae, Yongwoo Kim, Geun-Woo Jeon, Jun-Ho Choi, Jun-Hyuk Kim, Jong-Seok Lee, Steven Marty, Eric Marty, Dongliang Xiong, Siang Chen, Lin Zha, Jiande Jiang, Xinbo Gao, Wen Lu, Haicheng Wang, Vineeth Bhaskara, Alex Levinshtein, Stavros Tsogkas, Allan Jepson, Xiangzhen Kong, Tongtong Zhao, Shanshan Zhao, Hrishikesh P. S, Densen Puthussery, Jiji C. V, Nan Nan, Shuai Liu, Jie Cai, Zibo Meng, Jiaming Ding, Chiu Man Ho, Xuehui Wang, Qiong Yan, Yuzhi Zhao, Long Chen, Jiangtao Zhang, Xiaotong Luo, Liang Chen, Yanyun Qu, Long Sun, Wenhao Wang, Zhenbing Liu, Rushi Lan, Rao Muhammad Umer, Christian Micheloni
This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results.
no code implementations • 7 Aug 2020 • Tian Lan, Xian-Ling Mao, Wei Wei, He-Yan Huang
Thus, in this paper, we will measure systematically nearly all representative hierarchical and non-hierarchical models over the same experimental settings to check which kind is better.
no code implementations • 31 Jul 2020 • Xing Li, Wei Wei, Xiangnan Feng, Xue Liu, Zhiming Zheng
The graph structure is a commonly used data storage mode, and it turns out that the low-dimensional embedded representation of nodes in the graph is extremely useful in various typical tasks, such as node classification, link prediction , etc.
no code implementations • 8 Jul 2020 • Hsin-Ping Chou, Shih-Chieh Chang, Jia-Yu Pan, Wei Wei, Da-Cheng Juan
In this work, we propose a new regularization technique, Remix, that relaxes Mixup's formulation and enables the mixing factors of features and labels to be disentangled.
no code implementations • 7 Jul 2020 • Li-Huang Tsai, Shih-Chieh Chang, Yu-Ting Chen, Jia-Yu Pan, Wei Wei, Da-Cheng Juan
In this paper, we propose a noise-agnostic method to achieve robust neural network performance against any noise setting.
no code implementations • 15 Jun 2020 • Wei Wei, Bei Zhou, Georgios Leontidis
This paper proposes an enhanced natural language generation system combining the merits of both rule-based approaches and modern deep learning algorithms, boosting its performance to the extent where the generated textual content is capable of exhibiting agile human-writing styles and the content logic of which is highly controllable.
no code implementations • 2 May 2020 • Shuyin Xia, Daowan Peng, Deyu Meng, Changqing Zhang, Guoyin Wang, Zizhong Chen, Wei Wei
The assigned cluster of the points in the stable area is not changed in the current iteration while the points in the annulus area will be adjusted within a few neighbor clusters in the current iteration.
no code implementations • 30 Apr 2020 • Yi-Lin Tuan, Wei Wei, William Yang Wang
First, we train a large-scale language model and query it as textual knowledge.
1 code implementation • 28 Apr 2020 • Shilin Qu, Fajie Yuan, Guibing Guo, Liguang Zhang, Wei Wei
Specifically, our framework divides proximal information units into chunks, and performs memory access at certain time steps, whereby the number of memory operations can be greatly reduced.
1 code implementation • 6 Apr 2020 • Tian Lan, Xian-Ling Mao, Wei Wei, Xiaoyan Gao, He-Yan Huang
Through extensive experiments, the learning-based metrics are demonstrated that they are the most effective evaluation metrics for open-domain generative dialogue systems.
no code implementations • 7 Mar 2020 • Zhikang Zou, Yifan Liu, Shuangjie Xu, Wei Wei, Shiping Wen, Pan Zhou
Extensive experiments on crowd counting datasets (ShanghaiTech, MALL, WorldEXPO'10, and UCSD) show that our HSRNet can deliver superior results over all state-of-the-art approaches.
no code implementations • 26 Feb 2020 • Daizong Liu, Shuangjie Xu, Pan Zhou, Kun He, Wei Wei, Zichuan Xu
In this work, we propose a Disease Diagnosis Graph Convolutional Network (DD-GCN) that presents a novel view of investigating the inter-dependency among different diseases by using a dynamic learnable adjacency matrix in graph structure to improve the diagnosis accuracy.
no code implementations • 16 Feb 2020 • Yujia Xie, Hanjun Dai, Minshuo Chen, Bo Dai, Tuo Zhao, Hongyuan Zha, Wei Wei, Tomas Pfister
The top-k operation, i. e., finding the k largest or smallest elements from a collection of scores, is an important model component, which is widely used in information retrieval, machine learning, and data mining.
no code implementations • 20 Dec 2019 • Tian Lan, Xian-Ling Mao, He-Yan Huang, Wei Wei
Intuitively, a dialogue model that can control the timing of talking autonomously based on the conversation context can chat with humans more naturally.
no code implementations • 14 Dec 2019 • Dawit Belayneh, Federico Carminati, Amir Farbin, Benjamin Hooberman, Gulrukh Khattak, Miaoyuan Liu, Junze Liu, Dominick Olivito, Vitória Barin Pacela, Maurizio Pierini, Alexander Schwing, Maria Spiropulu, Sofia Vallecorsa, Jean-Roch Vlimant, Wei Wei, Matt Zhang
These networks can serve as fast and computationally light methods for particle shower simulation and reconstruction for current and future experiments at particle colliders.
no code implementations • 3 Dec 2019 • Patrick H. Chen, Wei Wei, Cho-Jui Hsieh, Bo Dai
In this paper, we propose a new method to overcome catastrophic forgetting by adding generative regularization to Bayesian inference framework.
1 code implementation • NeurIPS 2019 • Kecheng Zheng, Zheng-Jun Zha, Wei Wei
Abstraction reasoning is a long-standing challenge in artificial intelligence.
no code implementations • 26 Nov 2019 • E. A. Huerta, Gabrielle Allen, Igor Andreoni, Javier M. Antelis, Etienne Bachelet, Bruce Berriman, Federica Bianco, Rahul Biswas, Matias Carrasco, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Maya Fishbach, Francisco Förster, Daniel George, Tom Gibbs, Matthew Graham, William Gropp, Robert Gruendl, Anushri Gupta, Roland Haas, Sarah Habib, Elise Jennings, Margaret W. G. Johnson, Erik Katsavounidis, Daniel S. Katz, Asad Khan, Volodymyr Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Zsuzsa Marka, Kenton McHenry, Jonah Miller, Claudia Moreno, Mark Neubauer, Steve Oberlin, Alexander R. Olivas, Donald Petravick, Adam Rebei, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard F. Schutz, Alex Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Leo Singer, Brigitta M. Sipőcz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, JinJun Xiong, Zhizhen Zhao
Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data, which vary in volume and speed of data processing, from many different instruments that probe the Universe using different cosmic messengers: electromagnetic waves, cosmic rays, gravitational waves and neutrinos.
no code implementations • 17 Nov 2019 • Hao-Yun Chen, Li-Huang Tsai, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan
Label hierarchies widely exist in many vision-related problems, ranging from explicit label hierarchies existed in image classification to latent label hierarchies existed in semantic segmentation.
no code implementations • 9 Nov 2019 • Tianyu Liu, Wei Wei, William Yang Wang
In this paper, we propose the new task of table-to-text NLG with unseen schemas, which specifically aims to test the generalization of NLG for input tables with attribute types that never appear during training.
2 code implementations • 4 Nov 2019 • Kai Zhang, Shuhang Gu, Radu Timofte, Zheng Hui, Xiumei Wang, Xinbo Gao, Dongliang Xiong, Shuai Liu, Ruipeng Gang, Nan Nan, Chenghua Li, Xueyi Zou, Ning Kang, Zhan Wang, Hang Xu, Chaofeng Wang, Zheng Li, Lin-Lin Wang, Jun Shi, Wenyu Sun, Zhiqiang Lang, Jiangtao Nie, Wei Wei, Lei Zhang, Yazhe Niu, Peijin Zhuo, Xiangzhen Kong, Long Sun, Wenhao Wang
The challenge had 3 tracks.
no code implementations • 23 Sep 2019 • Wei Zhang, Wei Wei, Lingjie Xu, Lingling Jin, Cheng Li
Alibaba has China's largest e-commerce platform.
1 code implementation • 6 Sep 2019 • Yu-Lun Hsieh, Minhao Cheng, Da-Cheng Juan, Wei Wei, Wen-Lian Hsu, Cho-Jui Hsieh
This work proposes a novel algorithm to generate natural language adversarial input for text classification models, in order to investigate the robustness of these models.
no code implementations • 5 Sep 2019 • Wei Wei, Ling Cheng, Xian-Ling Mao, Guangyou Zhou, Feida Zhu
Recently, automatic image caption generation has been an important focus of the work on multimodal translation task.
no code implementations • 24 Aug 2019 • Wei Wei, Zanbo Wang, Xian-Ling Mao, Guangyou Zhou, Pan Zhou, Sheng Jiang
Sequence labeling is a fundamental task in natural language processing and has been widely studied.
no code implementations • 19 Aug 2019 • Cheng Li, Abdul Dakkak, JinJun Xiong, Wei Wei, Lingjie Xu, Wen-mei Hwu
Such an endeavor is challenging as the characteristics of an ML model depend on the interplay between the model, framework, system libraries, and the hardware (or the HW/SW stack).
no code implementations • 12 Aug 2019 • Jia-Nan Guo, Xian-Ling Mao, Xiao-Jian Jiang, Ying-Xiang Sun, Wei Wei, He-Yan Huang
Network embedding is a promising way of network representation, facilitating many signed social network processing and analysis tasks such as link prediction and node classification.
no code implementations • 12 Aug 2019 • Zhikang Zou, Huiliang Shao, Xiaoye Qu, Wei Wei, Pan Zhou
Recently, convolutional neural networks (CNNs) are the leading defacto method for crowd counting.
no code implementations • 29 Jul 2019 • Rong-Cheng Tu, Xian-Ling Mao, Bing Ma, Yong Hu, Tan Yan, Wei Wei, He-Yan Huang
Specifically, by an iterative optimization algorithm, DCHUC jointly learns unified hash codes for image-text pairs in a database and a pair of hash functions for unseen query image-text pairs.
no code implementations • 18 Jul 2019 • Ying Shi, Wei Wei, Zhiming Zheng
Zero-shot learning (ZSL) aims to recognize the novel object categories using the semantic representation of categories, and the key idea is to explore the knowledge of how the novel class is semantically related to the familiar classes.
no code implementations • ACL 2019 • Yu-Lun Hsieh, Minhao Cheng, Da-Cheng Juan, Wei Wei, Wen-Lian Hsu, Cho-Jui Hsieh
This work examines the robustness of self-attentive neural networks against adversarial input perturbations.
no code implementations • 16 Jun 2019 • Qingpeng Cai, Will Hang, Azalia Mirhoseini, George Tucker, Jingtao Wang, Wei Wei
In this paper, we introduce a novel framework to generate better initial solutions for heuristic algorithms using reinforcement learning (RL), named RLHO.
no code implementations • NAACL 2019 • Minhao Cheng, Wei Wei, Cho-Jui Hsieh
Moreover, we show that with the adversarial training, we are able to improve the robustness of negotiation agents by 1. 5 points on average against all our attacks.
no code implementations • ICLR 2019 • Chieh Hubert Lin, Chia-Che Chang, Yu-Sheng Chen, Da-Cheng Juan, Wei Wei, Hwann-Tzong Chen
The fact that the patch generation process is independent to each other inspires a wide range of new applications: firstly, "Patch-Inspired Image Generation" enables us to generate the entire image based on a single patch.
no code implementations • ICCV 2019 • Peng Wang, Bingliang Jiao, Lu Yang, Yifei Yang, Shizhou Zhang, Wei Wei, Yanning Zhang
It is capable of explicitly detecting discriminative parts for each specific vehicle and significantly outperforms the evaluated baselines and state-of-the-art vehicle ReID approaches.
1 code implementation • ICCV 2019 • Chieh Hubert Lin, Chia-Che Chang, Yu-Sheng Chen, Da-Cheng Juan, Wei Wei, Hwann-Tzong Chen
On the computation side, COCO-GAN has a built-in divide-and-conquer paradigm that reduces memory requisition during training and inference, provides high-parallelism, and can generate parts of images on-demand.
Ranked #1 on
Image Generation
on CelebA-HQ 64x64
no code implementations • 24 Mar 2019 • Lei Zhang, Zhiqiang Lang, Peng Wang, Wei Wei, Shengcai Liao, Ling Shao, Yanning Zhang
To address this problem, we propose a pixel-aware deep function-mixture network for SSR, which is composed of a new class of modules, termed function-mixture (FM) blocks.
2 code implementations • ICCV 2019 • Hao-Yun Chen, Jhao-Hong Liang, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan
Adversarial robustness has emerged as an important topic in deep learning as carefully crafted attack samples can significantly disturb the performance of a model.
1 code implementation • ICLR 2019 • Hao-Yun Chen, Pei-Hsin Wang, Chun-Hao Liu, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan
Although being a widely-adopted approach, using cross entropy as the primary objective exploits mostly the information from the ground-truth class for maximizing data likelihood, and largely ignores information from the complement (incorrect) classes.
no code implementations • 1 Feb 2019 • Gabrielle Allen, Igor Andreoni, Etienne Bachelet, G. Bruce Berriman, Federica B. Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Daniel George, Tom Gibbs, Matthew Graham, William Gropp, Anushri Gupta, Roland Haas, E. A. Huerta, Elise Jennings, Daniel S. Katz, Asad Khan, Volodymyr Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Kenton McHenry, J. M. Miller, M. S. Neubauer, Steve Oberlin, Alexander R. Olivas Jr, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard Schutz, Alex Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Brigitta M. Sipőcz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, JinJun Xiong, Zhizhen Zhao
We discuss key aspects to realize this endeavor, namely (i) the design and exploitation of scalable and computationally efficient AI algorithms for Multi-Messenger Astrophysics; (ii) cyberinfrastructure requirements to numerically simulate astrophysical sources, and to process and interpret Multi-Messenger Astrophysics data; (iii) management of gravitational wave detections and triggers to enable electromagnetic and astro-particle follow-ups; (iv) a vision to harness future developments of machine and deep learning and cyberinfrastructure resources to cope with the scale of discovery in the Big Data Era; (v) and the need to build a community that brings domain experts together with data scientists on equal footing to maximize and accelerate discovery in the nascent field of Multi-Messenger Astrophysics.
1 code implementation • NeurIPS 2019 • Albert Shaw, Wei Wei, Weiyang Liu, Le Song, Bo Dai
Neural Architecture Search (NAS) has been quite successful in constructing state-of-the-art models on a variety of tasks.
no code implementations • 27 Nov 2018 • Wei Wei, Xu Lingjie, Jin Lingling, Zhang Wei, Zhang Tianjun
In this work, a synthetic benchmarks framework is firstly proposed to address the above drawbacks of AI benchmarks.
2 code implementations • 26 Nov 2018 • An-Chieh Cheng, Chieh Hubert Lin, Da-Cheng Juan, Wei Wei, Min Sun
Conventional Neural Architecture Search (NAS) aims at finding a single architecture that achieves the best performance, which usually optimizes task related learning objectives such as accuracy.
no code implementations • 7 Nov 2018 • Christoph Dann, Lihong Li, Wei Wei, Emma Brunskill
The performance of a reinforcement learning algorithm can vary drastically during learning because of exploration.
1 code implementation • EMNLP 2018 • Wei Wei, Quoc Le, Andrew Dai, Jia Li
However, current datasets are limited in size, and the environment for training agents and evaluating progress is relatively unsophisticated.
no code implementations • 30 Aug 2018 • Lei Zhang, Peng Wang, Lingqiao Liu, Chunhua Shen, Wei Wei, Yannning Zhang, Anton Van Den Hengel
Towards this goal, we present a simple but effective two-branch network to simultaneously map semantic descriptions and visual samples into a joint space, on which visual embeddings are forced to regress to their class-level semantic embeddings and the embeddings crossing classes are required to be distinguishable by a trainable classifier.
no code implementations • 29 Aug 2018 • An-Chieh Cheng, Jin-Dong Dong, Chi-Hung Hsu, Shu-Huan Chang, Min Sun, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan
Recent breakthroughs in Neural Architectural Search (NAS) have achieved state-of-the-art performance in many tasks such as image classification and language understanding.
1 code implementation • ECCV 2018 • Chia-Che Chang, Chieh Hubert Lin, Che-Rung Lee, Da-Cheng Juan, Wei Wei, Hwann-Tzong Chen
Generative adversarial networks (GANs) often suffer from unpredictable mode-collapsing during training.
Ranked #18 on
Image Generation
on CelebA 64x64
1 code implementation • CVPR 2019 • Wei Wei, Deyu Meng, Qian Zhao, Zongben Xu, Ying Wu
However, previous deep learning methods need to pre-collect a large set of image pairs with/without synthesized rain for training, which tends to make the neural network be biased toward learning the specific patterns of the synthesized rain, while be less able to generalize to real test samples whose rain types differ from those in the training data.
Ranked #7 on
Single Image Deraining
on Test1200
no code implementations • 27 Jun 2018 • Chi-Hung Hsu, Shu-Huan Chang, Jhao-Hong Liang, Hsin-Ping Chou, Chun-Hao Liu, Shih-Chieh Chang, Jia-Yu Pan, Yu-Ting Chen, Wei Wei, Da-Cheng Juan
Recent studies on neural architecture search have shown that automatically designed neural networks perform as good as expert-crafted architectures.
no code implementations • ECCV 2018 • Jin-Dong Dong, An-Chieh Cheng, Da-Cheng Juan, Wei Wei, Min Sun
We propose DPP-Net: Device-aware Progressive Search for Pareto-optimal Neural Architectures, optimizing for both device-related (e. g., inference time and memory usage) and device-agnostic (e. g., accuracy and model size) objectives.
no code implementations • 10 Jun 2018 • Yiqi Yan, Lei Zhang, Jun Li, Wei Wei, Yanning Zhang
Different from traditional hyperspectral super-resolution approaches that focus on improving the spatial resolution, spectral super-resolution aims at producing a high-resolution hyperspectral image from the RGB observation with super-resolution in spectral domain.
no code implementations • 5 Jun 2018 • Lei Zhang, Peng Wang, Chunhua Shen, Lingqiao Liu, Wei Wei, Yanning Zhang, Anton Van Den Hengel
In this study, we revisit this problem from an orthog- onal view, and propose a novel learning strategy to maxi- mize the pixel-wise fitting capacity of a given lightweight network architecture.
no code implementations • CVPR 2018 • Minghan Li, Qi Xie, Qian Zhao, Wei Wei, Shuhang Gu, Jing Tao, Deyu Meng
Based on such understanding, we specifically formulate both characteristics into a multiscale convolutional sparse coding (MS-CSC) model for the video rain streak removal task.
1 code implementation • IEEE Transactions on Smart Grid 2018 • Rui Li, Wei Wei, Shengwei Mei, Qinran Hu, Qiuwei Wu
A mathematic program with equilibrium constraints (MPEC) model is proposed to study the strategic behaviors of a profit-driven energy hub in the electricity market and heating market under the background of energy system integration.
no code implementations • 9 Mar 2018 • Xiaofang Wang, Guoqiang Xiang, Xinyue Zhang, Wei Wei
In this paper, a framework of video face replacement is proposed and it deals with the flicker of swapped face in video sequence.
no code implementations • ICLR 2018 • Wei Wei, Quoc V. Le, Andrew M. Dai, Li-Jia Li
One challenge in applying such techniques to building goal-oriented conversation models is that maximum likelihood-based models are not optimized toward accomplishing goals.
1 code implementation • CVPR 2018 • Zhe Li, Chong Wang, Mei Han, Yuan Xue, Wei Wei, Li-Jia Li, Li Fei-Fei
Accurate identification and localization of abnormalities from radiology images play an integral part in clinical diagnosis and treatment planning.
no code implementations • ICLR 2018 • Rui Liu, Wei Wei, Weiguang Mao, Maria Chikina
Attention models have been intensively studied to improve NLP tasks such as machine comprehension via both question-aware passage attention model and self-matching attention model.
Ranked #31 on
Question Answering
on SQuAD1.1 dev
no code implementations • ICCV 2017 • Wei Wei, Lixuan Yi, Qi Xie, Qian Zhao, Deyu Meng, Zongben Xu
Videos taken in the wild sometimes contain unexpected rain streaks, which brings difficulty in subsequent video processing tasks.
no code implementations • 20 Aug 2017 • Wei Wei, Kennth Joseph, Kathleen Carley
The Recurrent Chinese Restaurant Process (RCRP) is a powerful statistical method for modeling evolving clusters in large scale social media data.
no code implementations • 3 Aug 2017 • Lei Zhang, Wei Wei, Qinfeng Shi, Chunhua Shen, Anton Van Den Hengel, Yanning Zhang
The prior for the non-low-rank structure is established based on a mixture of Gaussians which is shown to be flexible enough, and powerful enough, to inform the completion process for a variety of real tensor data.
1 code implementation • ICCV 2017 • Hao Lu, Lei Zhang, Zhiguo Cao, Wei Wei, Ke Xian, Chunhua Shen, Anton Van Den Hengel
Domain adaption (DA) allows machine learning methods trained on data sampled from one distribution to be applied to data sampled from another.
no code implementations • 17 May 2017 • Wei Wei, Xiaojun Wan
For the identification of misleading headlines, we extract features based on the congruence between headlines and bodies.
no code implementations • EMNLP 2017 • Rui Liu, Junjie Hu, Wei Wei, Zi Yang, Eric Nyberg
Deep neural networks for machine comprehension typically utilizes only word or character embeddings without explicitly taking advantage of structured linguistic information such as constituency trees and dependency trees.
Ranked #40 on
Question Answering
on SQuAD1.1 dev
no code implementations • 23 Feb 2017 • Yujie Qian, Jie Tang, Zhilin Yang, Binxuan Huang, Wei Wei, Kathleen M. Carley
In this paper, we formalize the problem of inferring location from social media into a semi-supervised factor graph model (SSFGM).
no code implementations • CVPR 2016 • Zhen Zhang, Qinfeng Shi, Julian McAuley, Wei Wei, Yanning Zhang, Anton Van Den Hengel
Feature matching is a key problem in computer vision and pattern recognition.
no code implementations • ICCV 2015 • Lei Zhang, Wei Wei, Yanning Zhang, Fei Li, Chunhua Shen, Qinfeng Shi
To reconstruct hyperspectral image (HSI) accurately from a few noisy compressive measurements, we present a novel manifold-structured sparsity prior based hyperspectral compressive sensing (HCS) method in this study.
no code implementations • CVPR 2015 • Lei Zhang, Wei Wei, Yanning Zhang, Chunna Tian, Fei Li
To address this problem, a novel reweighted Laplace prior based hyperspectral compressive sensing method is proposed in this study.