AAAI 2021

1,961 papers

Self-Supervised Self-Supervision by Combining Deep Learning and Probabilistic Logic

Hunter Lang, Hoifung Poon

Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders

Bhushan Kotnis, Carolin Lawrence, Mathias Niepert

Learning by Fixing: Solving Math Word Problems with Weak Supervision

Yining Hong, Qing Li, Daniel Ciao, Siyuan Huang, Song-chun Zhu

Learning Game-Theoretic Models of Multiagent Trajectories Using Implicit Layers

Philipp Geiger, Christoph-Nikolas Straehle

Planning from Pixels in Atari with Learned Symbolic Representations

Andrea Dittadi, Frederik K. Drachmann, Thomas Bolander

Aligning Artificial Neural Networks and Ontologies towards Explainable AI

Manuel de Sousa Ribeiro, João Leite

Dynamic Neuro-Symbolic Knowledge Graph Construction for Zero-shot Commonsense Question Answering

Antoine Bosselut, Ronan Le Bras, Yejin Choi

Interpretable Actions: Controlling Experts with Understandable Commands

Shumeet Baluja, David Marwood, Michele Covell

Conversational Neuro-Symbolic Commonsense Reasoning

Forough Arabshahi, Jennifer Lee, Mikayla Gawarecki, Kathryn Mazaitis, Amos Azaria

C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods Ahead of COVID-19 Outbreak

Congxi Xiao, Jingbo Zhou, Jizhou Huang, An Zhuo, Ji Liu

Tracking Disease Outbreaks from Sparse Data with Bayesian Inference

Bryan Wilder, Michael Mina, Milind Tambe

Context Matters: Graph-based Self-supervised Representation Learning for Medical Images

Li Sun, Ke Yu, Kayhan Batmanghelich

Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks

Arijit Sehanobish, Neal Ravindra, David van Dijk

Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19

Alexander Rodriguez, Nikhil Muralidhar, Bijaya Adhikari, Anika Tabassum, Naren Ramakrishnan

MiniSeg: An Extremely Minimum Network for Efficient COVID-19 Segmentation

Yu Qiu, Yun Liu, Shijie Li, Jing Xu

Transfer Graph Neural Networks for Pandemic Forecasting

George Panagopoulos, Giannis Nikolentzos, Michalis Vazirgiannis

STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization

Nikos Kargas, Cheng Qian, Nicholas D. Sidiropoulos, Cao Xiao, Lucas M. Glass

Automated Model Design and Benchmarking of Deep Learning Models for COVID-19 Detection with Chest CT Scans

XIN HE, Shihao Wang, Xiaowen Chu, Shaohuai Shi, Jiangping Tang

Persistence of Anti-vaccine Sentiment in Social Networks Through Strategic Interactions

A S M Ahsan-Ul Haque, Mugdha Thakur, Matthew Bielskas, Achla Marathe, Anil Vullikanti

Savable but Lost Lives when ICU Is Overloaded: a Model from 733 Patients in Epicenter Wuhan, China

Tingting Dan, Yang Li, Ziwei Zhu, Xijie Chen, Wuxiu Quan

Catch Me if I Can: Detecting Strategic Behaviour in Peer Assessment

Ivan Stelmakh, Nihar B. Shah, Aarti Singh

A Novice-Reviewer Experiment to Address Scarcity of Qualified Reviewers in Large Conferences

Ivan Stelmakh, Nihar B. Shah, Aarti Singh, Hal Daume III

A Market-Inspired Bidding Scheme for Peer Review Paper Assignment

Reshef Meir, Jérôme Lang, Julien Lesca, Nicholas Mattei, Natan Kaminsky

Uncovering Latent Biases in Text: Method and Application to Peer Review

Emaad Manzoor, Nihar B. Shah

Argument Mining Driven Analysis of Peer-Reviews

Michael Fromm, Evgeniy Faerman, Max Berrendorf, Siddharth Bhargava, Ruoxia Qi

Relation-Aware Neighborhood Matching Model for Entity Alignment

Yao Zhu, Hongzhi Liu, Zhonghai Wu, Yingpeng Du

Adversarial Directed Graph Embedding

Shijie Zhu, Jianxin Li, Hao Peng, Senzhang Wang, Lifang He

Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks

Cunchao Zhu, Muhao Chen, Changjun Fan, Guangquan Cheng, Yan Zhang

Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction

Qiang Zhou, Jingjing Gu, Xinjiang Lu, Fuzhen Zhuang, Yanchao Zhao

Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay

Fan Zhou, Chengtai Cao

Cold-start Sequential Recommendation via Meta Learner

Yujia Zheng, Siyi Liu, Zekun Li, Shu Wu

Heterogeneous Graph Structure Learning for Graph Neural Networks

Jianan Zhao, Xiao Wang, Chuan Shi, Binbin Hu, Guojie Song

A Graph-based Relevance Matching Model for Ad-hoc Retrieval

Yufeng Zhang, Jinghao Zhang, Zeyu Cui, Shu Wu, Liang Wang

Generalized Relation Learning with Semantic Correlation Awareness for Link Prediction

Yao Zhang, Xu Zhang, Jun Wang, Hongru Liang, Wenqiang Lei

Tripartite Collaborative Filtering with Observability and Selection for Debiasing Rating Estimation on Missing-Not-at-Random Data

Qi Zhang, Longbing Cao, Chongyang Shi, Liang Hu

Taxonomy Completion via Triplet Matching Network

Jieyu Zhang, Xiangchen Song, Ying Zeng, Jiaze Chen, Jiaming Shen

AugSplicing: Synchronized Behavior Detection in Streaming Tensors

Jiabao Zhang, Shenghua Liu, Wenting Hou, Siddharth Bhatia, Huawei Shen

Self-Supervised Prototype Representation Learning for Event-Based Corporate Profiling

Zixuan Yuan, Hao Liu, Renjun Hu, Denghui Zhang, Hui Xiong

Dual Sparse Attention Network For Session-based Recommendation

Jiahao Yuan, Zihan Song, Mingyou Sun, Xiaoling Wang, Wayne Xin Zhao

Deep Graph-neighbor Coherence Preserving Network for Unsupervised Cross-modal Hashing

Jun Yu, Hao Zhou, Yibing Zhan, Dacheng Tao

Coupled Layer-wise Graph Convolution for Transportation Demand Prediction

Junchen Ye, Leilei Sun, Bowen Du, Yanjie Fu, Hui Xiong

Interpretable Clustering on Dynamic Graphs with Recurrent Graph Neural Networks

Yuhang Yao, Carlee Joe-Wong

Relaxed Clustered Hawkes Process for Student Procrastination Modeling in MOOCs

Mengfan Yao, Siqian Zhao, Shaghayegh Sahebi, Reza Feyzi Behnagh

Why Do Attributes Propagate in Graph Convolutional Neural Networks?

Liang Yang, Chuan Wang, Junhua Gu, Xiaochun Cao, bingxin niu

Capturing Delayed Feedback in Conversion Rate Prediction via Elapsed-Time Sampling

Jia-Qi Yang, Xiang Li, Shuguang Han, Tao Zhuang, De-Chuan Zhan

Rethinking Graph Regularization for Graph Neural Networks

Han Yang, Kaili Ma, James Cheng

Dynamic Knowledge Graph Alignment

Yuchen Yan, Lihui Liu, Yikun Ban, Baoyu Jing, Hanghang Tong

A Unified Pretraining Framework for Passage Ranking and Expansion

Ming Yan, Chenliang Li, Bin Bi, Wei Wang, Songfang Huang

Transformer-Style Relational Reasoning with Dynamic Memory Updating for Temporal Network Modeling

Dongkuan Xu, Junjie Liang, Wei Cheng, Hua Wei, Haifeng Chen

Towards Consumer Loan Fraud Detection: Graph Neural Networks with Role-Constrained Conditional Random Field

Bingbing Xu, Huawei Shen, Bingjie Sun, Rong An, Qi Cao

Out-of-Town Recommendation with Travel Intention Modeling

Haoran Xin, Xinjiang Lu, Tong Xu, Hao Liu, Jingjing Gu

Hierarchical Reinforcement Learning for Integrated Recommendation

Ruobing Xie, Shaoliang Zhang, Rui Wang, Feng Xia, Leyu Lin

A General Offline Reinforcement Learning Framework for Interactive Recommendation

Teng Xiao, Donglin Wang

Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation

Xin Xia, Hongzhi Yin, Junliang Yu, Qinyong Wang, Lizhen Cui

AttnMove: History Enhanced Trajectory Recovery via Attentional Network

Tong Xia, Yunhan Qi, Jie Feng, Fengli Xu, Funing Sun

Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation

Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Xiyue Zhang

Inductive Graph Neural Networks for Spatiotemporal Kriging

Yuankai Wu, Dingyi Zhuang, Aurelie Labbe, Lijun Sun

Hybrid-order Stochastic Block Model

Xunxun Wu, Chang-Dong Wang, Pengfei Jiao

Fairness-aware News Recommendation with Decomposed Adversarial Learning

Chuhan Wu, Fangzhao Wu, Xiting Wang, Yongfeng Huang, Xing Xie

Learning to Truncate Ranked Lists for Information Retrieval

Chen Wu, Ruqing Zhang, Jiafeng Guo, Yixing Fan, Yanyan Lan

How Do We Move: Modeling Human Movement with System Dynamics

Hua Wei, Dongkuan Xu, Junjie Liang, Zhenhui (Jessie) Li

Learning to Recommend from Sparse Data via Generative User Feedback

Wenlin Wang

Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation

Kai Wang, Zhene Zou, Qilin Deng, Jianrong Tao, Runze Wu

Coupling Macro-Sector-Micro Financial Indicators for Learning Stock Representations with Less Uncertainty

Guifeng Wang, Longbing Cao, Hongke Zhao, Qi Liu, Enhong Chen

Reinforced Imitative Graph Representation Learning for Mobile User Profiling: An Adversarial Training Perspective

Dongjie Wang, Pengyang Wang, Kunpeng Liu, Yuanchun Zhou, Charles E Hughes

GSNet: Learning Spatial-Temporal Correlations from Geographical and Semantic Aspects for Traffic Accident Risk Forecasting

Beibei Wang, Youfang Lin, Shengnan Guo, Huaiyu Wan

GaussianPath:A Bayesian Multi-Hop Reasoning Framework for Knowledge Graph Reasoning

Guojia Wan, Bo Du

Dynamic Memory based Attention Network for Sequential Recommendation

Qiaoyu Tan, Jianwei Zhang, Ninghao Liu, Xiao Huang, Hongxia Yang

Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs

Li Sun, Zhongbao Zhang, Jiawei Zhang, Feiyang Wang, Hao Peng

A Hybrid Probabilistic Approach for Table Understanding

Kexuan Sun, Harsha Rayudu, Jay Pujara

Detecting Beneficial Feature Interactions for Recommender Systems

Yixin Su, Rui Zhang, Sarah Erfani, Zhenghua Xu

Group Testing on a Network

Arlei Silva, Ambuj Singh

Knowledge-Driven Distractor Generation for Cloze-Style Multiple Choice Questions

Siyu Ren, Kenny Q. Zhu

DocParser: Hierarchical Document Structure Parsing from Renderings

Johannes Rausch, Octavio Martinez, Fabian Bissig, Ce Zhang, Stefan Feuerriegel

U-BERT: Pre-training User Representations for Improved Recommendation

Zhaopeng Qiu, Xian Wu, Jingyue Gao, Wei Fan

Robust Spatio-Temporal Purchase Prediction via Deep Meta Learning

Huiling Qin, Songyu Ke, Xiaodu Yang, Haoran Xu, Xianyuan Zhan

Learning Accurate and Interpretable Decision Rule Sets from Neural Networks

Litao Qiao, Weijia Wang, Bill Lin

Communicative Message Passing for Inductive Relation Reasoning

Sijie Mai, Shuangjia Zheng, Yuedong Yang, Haifeng Hu

Knowledge-Enhanced Top-K Recommendation in Poincaré Ball

Chen Ma, Liheng Ma, Yingxue Zhang, Haolun Wu, Xue Liu

Learning to Pre-train Graph Neural Networks

Yuanfu Lu, Xunqiang Jiang, Yuan Fang, Chuan Shi

Relative and Absolute Location Embedding for Few-Shot Node Classification on Graph

Zemin Liu, Yuan Fang, Chenghao Liu, Steven C.H. Hoi

Visual Pivoting for (Unsupervised) Entity Alignment

Fangyu Liu, Muhao Chen, Dan Roth, Nigel Collier

Noninvasive Self-attention for Side Information Fusion in Sequential Recommendation

Chang Liu, Xiaoguang Li, Guohao Cai, Zhenhua Dong, Hong Zhu

Pre-training Context and Time Aware Location Embeddings from Spatial-Temporal Trajectories for User Next Location Prediction

Yan Lin, Huaiyu Wan, Shengnan Guo, Youfang Lin

HMS: A Hierarchical Solver with Dependency-Enhanced Understanding for Math Word Problem

Xin lin, Zhenya Huang, Hongke Zhao, Enhong Chen, Qi Liu

FedRec++: Lossless Federated Recommendation with Explicit Feedback

Feng Liang, Weike Pan, Zhong Ming

Cross-Oilfield Reservoir Classification via Multi-Scale Sensor Knowledge Transfer

Zhi Li, Zhefeng Wang, Zhicheng Wei, Xiangguang Zhou, Yijun Wang

GraphMSE: Efficient Meta-path Selection in Semantically Aligned Feature Space for Graph Neural Networks

Yi Li, Yilun Jin, Guojie Song, Zihao Zhu, Chuan Shi

Rejection Sampling for Weighted Jaccard Similarity Revisited

Xiaoyun Li, Ping Li

Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting

Mengzhang Li, Zhanxing Zhu

Hierarchical Negative Binomial Factorization for Recommender Systems on Implicit Feedback

Li-Yen Kuo, Ming-syan Chen

Disposable Linear Bandits for Online Recommendations

Melda Korkut, Andrew Li

PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation

Minseok Kim, Hwanjun Song, Doyoung Kim, Kijung Shin, Jae-Gil Lee

Randomized Generation of Adversary-aware Fake Knowledge Graphs to Combat Intellectual Property Theft

Snow Kang, Cristian Molinaro, Andrea Pugliese, V. S. Subrahmanian

On Estimating Recommendation Evaluation Metrics under Sampling

Ruoming Jin, Dong Li, Benjamin Mudrak, Jing Gao, Zhi Liu

LREN: Low-Rank Embedded Network for Sample-Free Hyperspectral Anomaly Detection

Kai Jiang, Weiying Xie, Jie Lei, Tao Jiang, Yunsong Li

Anomaly Attribution with Likelihood Compensation

Tsuyoshi Ide, Amit Dhurandhar, Jiri Navratil, Moninder Singh, Naoki Abe

Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation

Chao Huang, Jiahui Chen, Lianghao Xia, Yong Xu, Peng Dai

Knowledge-aware Coupled Graph Neural Network for Social Recommendation

Chao Huang, Huance Xu, Yong Xu, Peng Dai, Lianghao Xia

Online Learning in Variable Feature Spaces under Incomplete Supervision

Yi He, Xu Yuan, Sheng Chen, Xindong Wu