1 code implementation • 28 Apr 2024 • Minjie Wang, Quan Gan, David Wipf, Zhenkun Cai, Ning li, Jianheng Tang, Yanlin Zhang, Zizhao Zhang, Zunyao Mao, Yakun Song, Yanbo Wang, Jiahang Li, Han Zhang, Guang Yang, Xiao Qin, Chuan Lei, Muhan Zhang, Weinan Zhang, Christos Faloutsos, Zheng Zhang
Although RDBs store vast amounts of rich, informative data spread across interconnected tables, the progress of predictive machine learning models as applied to such tasks arguably falls well behind advances in other domains such as computer vision or natural language processing.
no code implementations • 25 Feb 2024 • Nuo Chen, Yuhan Li, Jianheng Tang, Jia Li
Large language models (LLMs) have achieved impressive success across several fields, but their proficiency in understanding and resolving complex graph problems is less explored.
1 code implementation • NeurIPS 2023 • Jianheng Tang, Fengrui Hua, Ziqi Gao, Peilin Zhao, Jia Li
With a long history of traditional Graph Anomaly Detection (GAD) algorithms and recently popular Graph Neural Networks (GNNs), it is still not clear (1) how they perform under a standard comprehensive setting, (2) whether GNNs can outperform traditional algorithms such as tree ensembles, and (3) how about their efficiency on large-scale graphs.
1 code implementation • 11 May 2023 • Jianheng Tang, Kangfei Zhao, Jia Li
In this paper, we introduce FGWEA, an unsupervised entity alignment framework that leverages the Fused Gromov-Wasserstein (FGW) distance, allowing for a comprehensive comparison of entity semantics and KG structures within a joint optimization framework.
1 code implementation • 10 Apr 2023 • Weiqi Zhang, Guanlve Li, Jianheng Tang, Jia Li, Fugee Tsung
Data imputation is a prevalent and important task due to the ubiquitousness of missing data.
2 code implementations • 12 Mar 2023 • Jiajin Li, Jianheng Tang, Lemin Kong, Huikang Liu, Jia Li, Anthony Man-Cho So, Jose Blanchet
This observation allows us to provide an approximation bound for the distance between the fixed-point set of BAPG and the critical point set of GW.
1 code implementation • NeurIPS 2023 • Lemin Kong, Jiajin Li, Jianheng Tang, Anthony Man-Cho So
Gromov-Wasserstein (GW) distance is a powerful tool for comparing and aligning probability distributions supported on different metric spaces.
1 code implementation • 30 Jan 2023 • Jianheng Tang, Weiqi Zhang, Jiajin Li, Kangfei Zhao, Fugee Tsung, Jia Li
As the graphs to be aligned are usually constructed from different sources, the inconsistency issues of structures and features between two graphs are ubiquitous in real-world applications.
no code implementations • 17 Jan 2023 • Jianheng Tang, Kejia Fan, Wenxuan Xie, Luomin Zeng, Feijiang Han, Guosheng Huang, Tian Wang, Anfeng Liu, Shaobo Zhang
In this paper, an incentive mechanism named Semi-supervision based Combinatorial Multi-Armed Bandit reverse Auction (SCMABA) is proposed to solve the recruitment problem of multiple unknown and strategic workers in MCS.
no code implementations • 30 Nov 2022 • Ziqi Gao, Yifan Niu, Jiashun Cheng, Jianheng Tang, Tingyang Xu, Peilin Zhao, Lanqing Li, Fugee Tsung, Jia Li
In this work, we present a regularized graph autoencoder for graph attribute imputation, named MEGAE, which aims at mitigating spectral concentration problem by maximizing the graph spectral entropy.
1 code implementation • 31 May 2022 • Jianheng Tang, Jiajin Li, Ziqi Gao, Jia Li
Graph Neural Networks (GNNs) are widely applied for graph anomaly detection.
no code implementations • 17 May 2022 • Jiajin Li, Jianheng Tang, Lemin Kong, Huikang Liu, Jia Li, Anthony Man-Cho So, Jose Blanchet
In this paper, we study the design and analysis of a class of efficient algorithms for computing the Gromov-Wasserstein (GW) distance tailored to large-scale graph learning tasks.
1 code implementation • 29 Apr 2022 • Wenge Liu, Yi Cheng, Hao Wang, Jianheng Tang, Yafei Liu, Ruihui Zhao, Wenjie Li, Yefeng Zheng, Xiaodan Liang
In this paper, we explore how to bring interpretability to data-driven DSMD.
1 code implementation • ACL 2021 • Jinghui Qin, Xiaodan Liang, Yining Hong, Jianheng Tang, Liang Lin
Previous math word problem solvers following the encoder-decoder paradigm fail to explicitly incorporate essential math symbolic constraints, leading to unexplainable and unreasonable predictions.
1 code implementation • Findings (ACL) 2021 • Jiaqi Chen, Jianheng Tang, Jinghui Qin, Xiaodan Liang, Lingbo Liu, Eric P. Xing, Liang Lin
Therefore, we propose a Geometric Question Answering dataset GeoQA, containing 4, 998 geometric problems with corresponding annotated programs, which illustrate the solving process of the given problems.
Ranked #4 on Mathematical Reasoning on PGPS9K
1 code implementation • 22 Dec 2020 • Shuai Lin, Pan Zhou, Xiaodan Liang, Jianheng Tang, Ruihui Zhao, Ziliang Chen, Liang Lin
Besides, we develop a Graph-Evolving Meta-Learning (GEML) framework that learns to evolve the commonsense graph for reasoning disease-symptom correlations in a new disease, which effectively alleviates the needs of a large number of dialogues.
1 code implementation • 15 Oct 2020 • Wenge Liu, Jianheng Tang, Yi Cheng, Wenjie Li, Yefeng Zheng, Xiaodan Liang
To push forward the future research on building expert-sensitive medical dialogue system, we proposes two kinds of medical dialogue tasks based on MedDG dataset.
1 code implementation • 4 Feb 2020 • Jinghui Qin, Zheng Ye, Jianheng Tang, Xiaodan Liang
Target-guided open-domain conversation aims to proactively and naturally guide a dialogue agent or human to achieve specific goals, topics or keywords during open-ended conversations.
2 code implementations • ACL 2019 • Jianheng Tang, Tiancheng Zhao, Chenyan Xiong, Xiaodan Liang, Eric P. Xing, Zhiting Hu
We study the problem of imposing conversational goals on open-domain chat agents.
1 code implementation • 30 Jan 2019 • Lin Xu, Qixian Zhou, Ke Gong, Xiaodan Liang, Jianheng Tang, Liang Lin
Besides the challenges for conversational dialogue systems (e. g. topic transition coherency and question understanding), automatic medical diagnosis further poses more critical requirements for the dialogue rationality in the context of medical knowledge and symptom-disease relations.