839 citations · 1k across the 18 of their papers we have counts for
18 papers
Information Theory-Guided Heuristic Progressive Multi-View Coding
Jiangmeng Li, Hang Gao, Wenwen Qiang +1
Multi-view representation learning aims to capture comprehensive information from multiple views of a shared context. Recent works intuitively apply contrastive learning to differe…
CompoNeRF: Text-guided Multi-object Compositional NeRF with Editable 3D Scene Layout
Haotian Bai, Yuanhuiyi Lyu, Lutao Jiang +4
Text-to-3D form plays a crucial role in creating editable 3D scenes for AR/VR. Recent advances have shown promise in merging neural radiance fields (NeRFs) with pre-trained diffusi…
Customized Conversational Recommender Systems
Shuokai Li, Yongchun Zhu, Ruobing Xie +5
Conversational recommender systems (CRS) aim to capture user's current intentions and provide recommendations through real-time multi-turn conversational interactions. As a human-m…
Interventional Contrastive Learning with Meta Semantic Regularizer
Wenwen Qiang, Jiangmeng Li, Changwen Zheng +2
Contrastive learning (CL)-based self-supervised learning models learn visual representations in a pairwise manner. Although the prevailing CL model has achieved great progress, in…
MetAug: Contrastive Learning via Meta Feature Augmentation
Jiangmeng Li, Wenwen Qiang, Changwen Zheng +2
What matters for contrastive learning? We argue that contrastive learning heavily relies on informative features, or "hard" (positive or negative) features. Early works include mor…
Hyperbolic Graph Neural Networks: A Review of Methods and Applications
Menglin Yang, Min Zhou, Tong Zhang +5
Graph representation learning in Euclidean space, despite its widespread adoption and proven utility in many domains, often struggles to effectively capture the inherent hierarchic…
Online POI Recommendation: Learning Dynamic Geo-Human Interactions in Streams
Dongjie Wang, Kunpeng Liu, Hui Xiong +1
In this paper, we focus on the problem of modeling dynamic geo-human interactions in streams for online POI recommendations. Specifically, we formulate the in-stream geo-human inte…
Learning to Walk with Dual Agents for Knowledge Graph Reasoning
Denghui Zhang, Zixuan Yuan, Hao Liu +2
Graph walking based on reinforcement learning (RL) has shown great success in navigating an agent to automatically complete various reasoning tasks over an incomplete knowledge gra…
Multi-Domain Transformer-Based Counterfactual Augmentation for Earnings Call Analysis
Zixuan Yuan, Yada Zhu, Wei Zhang +3
Earnings call (EC), as a periodic teleconference of a publicly-traded company, has been extensively studied as an essential market indicator because of its high analytical value in…
Cyberphysical Sequencing for Distributed Asset Management with Broad Traceability
Joshua Siegel, Gregory Falco
Cyber-Physical systems (CPS) have complex lifecycles involving multiple stakeholders, and the transparency of both hardware and software components' supply chain is opaque at best.…
Information Theory-Guided Heuristic Progressive Multi-View Coding
Jiangmeng Li, Wenwen Qiang, Hang Gao +5
Multi-view representation learning captures comprehensive information from multiple views of a shared context. Recent works intuitively apply contrastive learning (CL) to learn rep…
A Comprehensive Survey on Graph Anomaly Detection with Deep Learning
Xiaoxiao Ma, Jia Wu, Shan Xue +5
Anomalies represent rare observations (e.g., data records or events) that deviate significantly from others. Over several decades, research on anomaly mining has received increasin…
Heterogeneous Graph Representation Learning with Relation Awareness
Le Yu, Leilei Sun, Bowen Du +3
Representation learning on heterogeneous graphs aims to obtain meaningful node representations to facilitate various downstream tasks, such as node classification and link predicti…
T-Net: A Semi-supervised Deep Model for Turbulence Forecasting
Denghui Zhang, Yanchi Liu, Wei Cheng +5
Accurate air turbulence forecasting can help airlines avoid hazardous turbulence, guide the routes that keep passengers safe, maximize efficiency, and reduce costs. Traditional tur…
E-BERT: A Phrase and Product Knowledge Enhanced Language Model for E-commerce
Denghui Zhang, Zixuan Yuan, Yanchi Liu +3
Pre-trained language models such as BERT have achieved great success in a broad range of natural language processing tasks. However, BERT cannot well support E-commerce related tas…
Exploiting Interpretable Patterns for Flow Prediction in Dockless Bike Sharing Systems
Jingjing Gu, Qiang Zhou, Jingyuan Yang +4
Unlike the traditional dock-based systems, dockless bike-sharing systems are more convenient for users in terms of flexibility. However, the flexibility of these dockless systems c…
Deep Cross Networks with Aesthetic Preference for Cross-domain Recommendation
Jian Liu, Pengpeng Zhao, Yanchi Liu +5
When purchasing appearance-first products, e.g., clothes, product appearance aesthetics plays an important role in the decision process. Moreover, user's aesthetic preference, whic…
Detecting Blackholes and Volcanoes in Directed Networks
Zhongmou Li, Hui Xiong, Yanchi Liu
In this paper, we formulate a novel problem for finding blackhole and volcano patterns in a large directed graph. Specifically, a blackhole pattern is a group which is made of a se…