Search Results for author: Kunpeng Zhang

Found 17 papers, 9 papers with code

Large-Scale Traffic Data Imputation with Spatiotemporal Semantic Understanding

1 code implementation27 Jan 2023 Kunpeng Zhang, Lan Wu, Liang Zheng, Na Xie, Zhengbing He

Specifically, the proposed model introduces semantic descriptions consisting of network-wide spatial and temporal information of traffic data to help the GT-TDI model capture spatiotemporal correlations at a network level.

Imputation Traffic Data Imputation

Incorporating Interactive Facts for Stock Selection via Neural Recursive ODEs

no code implementations28 Oct 2022 Qiang Gao, Xinzhu Zhou, Kunpeng Zhang, Li Huang, Siyuan Liu, Fan Zhou

Stock selection attempts to rank a list of stocks for optimizing investment decision making, aiming at minimizing investment risks while maximizing profit returns.

Decision Making

Self-supervised Representation Learning for Trip Recommendation

no code implementations2 Sep 2021 Qiang Gao, Wei Wang, Kunpeng Zhang, Xin Yang, Congcong Miao

Although recent deep recursive models (e. g., RNN) are capable of alleviating these concerns, existing solutions hardly recognize the practical reality, such as the diversity of tourist demands, uncertainties in the trip generation, and the complex visiting preference.

Contrastive Learning point of interests +1

Enhanced Seq2Seq Autoencoder via Contrastive Learning for Abstractive Text Summarization

2 code implementations26 Aug 2021 Chujie Zheng, Kunpeng Zhang, Harry Jiannan Wang, Ling Fan, Zhe Wang

In this paper, we present a denoising sequence-to-sequence (seq2seq) autoencoder via contrastive learning for abstractive text summarization.

Abstractive Text Summarization Contrastive Learning +1

CCGL: Contrastive Cascade Graph Learning

1 code implementation27 Jul 2021 Xovee Xu, Fan Zhou, Kunpeng Zhang, Siyuan Liu

Second, it learns a generic model for graph cascade tasks via self-supervised contrastive pre-training using both unlabeled and labeled data.

Data Augmentation Graph Learning +3

Graph Neural Network Based VC Investment Success Prediction

no code implementations25 May 2021 Shiwei Lyu, Shuai Ling, Kaihao Guo, Haipeng Zhang, Kunpeng Zhang, Suting Hong, Qing Ke, Jinjie Gu

Predicting the start-ups that will eventually succeed is essentially important for the venture capital business and worldwide policy makers, especially at an early stage such that rewards can possibly be exponential.

Representation Learning

Weighting-Based Treatment Effect Estimation via Distribution Learning

1 code implementation26 Dec 2020 Dongcheng Zhang, Kunpeng Zhang

Existing weighting methods for treatment effect estimation are often built upon the idea of propensity scores or covariate balance.

A Two-Phase Approach for Abstractive Podcast Summarization

no code implementations16 Nov 2020 Chujie Zheng, Kunpeng Zhang, Harry Jiannan Wang, Ling Fan

Podcast summarization is different from summarization of other data formats, such as news, patents, and scientific papers in that podcasts are often longer, conversational, colloquial, and full of sponsorship and advertising information, which imposes great challenges for existing models.

Sentence Similarity

Topic-Guided Abstractive Text Summarization: a Joint Learning Approach

1 code implementation20 Oct 2020 Chujie Zheng, Kunpeng Zhang, Harry Jiannan Wang, Ling Fan, Zhe Wang

We introduce a new approach for abstractive text summarization, Topic-Guided Abstractive Summarization, which calibrates long-range dependencies from topic-level features with globally salient content.

Abstractive Text Summarization Extractive Summarization

A Baseline Analysis for Podcast Abstractive Summarization

1 code implementation24 Aug 2020 Chujie Zheng, Harry Jiannan Wang, Kunpeng Zhang, Ling Fan

Podcast summary, an important factor affecting end-users' listening decisions, has often been considered a critical feature in podcast recommendation systems, as well as many downstream applications.

Abstractive Text Summarization Recommendation Systems

Interpreting Twitter User Geolocation

no code implementations ACL 2020 Ting Zhong, Tianliang Wang, Fan Zhou, Goce Trajcevski, Kunpeng Zhang, Yi Yang

Identifying user geolocation in online social networks is an essential task in many location-based applications.

A Survey of Information Cascade Analysis: Models, Predictions, and Recent Advances

3 code implementations22 May 2020 Fan Zhou, Xovee Xu, Goce Trajcevski, Kunpeng Zhang

The deluge of digital information in our daily life -- from user-generated content, such as microblogs and scientific papers, to online business, such as viral marketing and advertising -- offers unprecedented opportunities to explore and exploit the trajectories and structures of the evolution of information cascades.

Feature Engineering Marketing

A Heterogeneous Dynamical Graph Neural Networks Approach to Quantify Scientific Impact

1 code implementation26 Mar 2020 Fan Zhou, Xovee Xu, Ce Li, Goce Trajcevski, Ting Zhong, Kunpeng Zhang

Quantifying and predicting the long-term impact of scientific writings or individual scholars has important implications for many policy decisions, such as funding proposal evaluation and identifying emerging research fields.

Meta-GNN: On Few-shot Node Classification in Graph Meta-learning

no code implementations23 May 2019 Fan Zhou, Chengtai Cao, Kunpeng Zhang, Goce Trajcevski, Ting Zhong, Ji Geng

Meta-learning has received a tremendous recent attention as a possible approach for mimicking human intelligence, i. e., acquiring new knowledge and skills with little or even no demonstration.

Few-Shot Learning General Classification +1

Trajectory-User Linking via Variational AutoEncoder

1 code implementation International Joint Conference on Artificial Intelligence 2018 Fan Zhou, Qiang Gao, Goce Trajcevski, Kunpeng Zhang, Ting Zhong, Fengli Zhang

Trajectory-User Linking (TUL) is an essential task in Geo-tagged social media (GTSM) applications, enabling personalized Point of Interest (POI) recommendation and activity identification.

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