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ACM Transactions on Intelligent Systems and Technology, Volume 13
Volume 13, Number 1, February 2022
- Kai Zheng, Yong Li, Cyrus Shahabi, Hongzhi Yin
:
Introduction to the Special Issue on Intelligent Trajectory Analytics: Part I. 1:1-1:2 - Yuandong Wang
, Hongzhi Yin
, Tong Chen
, Chunyang Liu, Ben Wang, Tianyu Wo, Jie Xu:
Passenger Mobility Prediction via Representation Learning for Dynamic Directed and Weighted Graphs. 2:1-2:25 - Wen-Cheng Chen, Wan-Lun Tsai, Huan-Hua Chang, Min-Chun Hu
, Wei-Ta Chu
:
Instant Basketball Defensive Trajectory Generation. 3:1-3:20 - Fan Zhou, Pengyu Wang
, Xovee Xu
, Wenxin Tai
, Goce Trajcevski
:
Contrastive Trajectory Learning for Tour Recommendation. 4:1-4:25 - Meng Chen
, Qingjie Liu, Weiming Huang
, Teng Zhang, Yixuan Zuo, Xiaohui Yu
:
Origin-Aware Location Prediction Based on Historical Vehicle Trajectories. 5:1-5:18 - Christoffer Löffler
, Luca Reeb, Daniel Dzibela, Robert Marzilger, Nicolas Witt, Björn M. Eskofier, Christopher Mutschler:
Deep Siamese Metric Learning: A Highly Scalable Approach to Searching Unordered Sets of Trajectories. 6:1-6:23 - Heli Sun
, Xianglan Guo, Zhou Yang, Xuguang Chu
, Xinwang Liu, Liang He:
Predicting Future Locations with Semantic Trajectories. 7:1-7:20 - Hui Luo
, Zhifeng Bao
, Gao Cong, J. Shane Culpepper
, Nguyen Lu Dang Khoa:
Let Trajectories Speak Out the Traffic Bottlenecks. 8:1-8:21 - Hongting Niu
, Hengshu Zhu
, Ying Sun, Xinjiang Lu, Jing Sun, Zhiyuan Zhao, Hui Xiong, Bo Lang:
Exploring the Risky Travel Area and Behavior of Car-hailing Service. 9:1-9:22 - Yanliang Zhu, Dongchun Ren
, Yi Xu, Deheng Qian, Mingyu Fan
, Xin Li, Huaxia Xia:
Simultaneous Past and Current Social Interaction-aware Trajectory Prediction for Multiple Intelligent Agents in Dynamic Scenes. 10:1-10:16 - Xin Bi
, Chao Zhang, Fangtong Wang, Zhixun Liu, Xiangguo Zhao, Ye Yuan, Guoren Wang:
An Uncertainty-based Neural Network for Explainable Trajectory Segmentation. 11:1-11:18
- Marcin Waniek
, Tomasz P. Michalak, Michael J. Wooldridge, Talal Rahwan:
How Members of Covert Networks Conceal the Identities of Their Leaders. 12:1-12:29 - Shih-Chia Huang, Quoc-Viet Hoang
, Da-Wei Jaw:
Self-Adaptive Feature Transformation Networks for Object Detection in low luminance Images. 13:1-13:11 - Yu Ting Wen, Hui-Kuo Yang, Wen-Chih Peng:
Mining Willing-to-Pay Behavior Patterns from Payment Datasets. 14:1-14:19 - Yu Zhou
, Haixia Zheng, Xin Huang, Shufeng Hao, Dengao Li, Jumin Zhao:
Graph Neural Networks: Taxonomy, Advances, and Trends. 15:1-15:54 - Cheng-Te Li, Cheng Hsu, Yang Zhang:
FairSR: Fairness-aware Sequential Recommendation through Multi-Task Learning with Preference Graph Embeddings. 16:1-16:21
Volume 13, Number 2, April 2022
- Senzhang Wang, Junbo Zhang, Yanjie Fu, Yong Li:
Introduction to the Special Issue on Deep Learning for Spatio-Temporal Data: Part 2. 17:1-17:4 - Divya Saxena
, Jiannong Cao:
Multimodal Spatio-Temporal Prediction with Stochastic Adversarial Networks. 18:1-18:23 - He Li, Xuejiao Li
, Liangcai Su, Duo Jin, Jianbin Huang, Deshuang Huang:
Deep Spatio-temporal Adaptive 3D Convolutional Neural Networks for Traffic Flow Prediction. 19:1-19:21 - Zhilong Lu, Weifeng Lv, Zhipu Xie, Bowen Du, Guixi Xiong, Leilei Sun, Haiquan Wang:
Graph Sequence Neural Network with an Attention Mechanism for Traffic Speed Prediction. 20:1-20:24 - Renhe Jiang
, Zekun Cai, Zhaonan Wang, Chuang Yang, Zipei Fan, Quanjun Chen, Xuan Song, Ryosuke Shibasaki:
Predicting Citywide Crowd Dynamics at Big Events: A Deep Learning System. 21:1-21:24 - Nan Gao
, Hao Xue
, Wei Shao
, Sichen Zhao, Kyle Kai Qin, Arian Prabowo, Mohammad Saiedur Rahaman
, Flora D. Salim:
Generative Adversarial Networks for Spatio-temporal Data: A Survey. 22:1-22:25 - Yingxue Zhang
, Yanhua Li
, Xun Zhou
, Jun Luo, Zhi-Li Zhang:
Urban Traffic Dynamics Prediction - A Continuous Spatial-temporal Meta-learning Approach. 23:1-23:19 - Haomin Wen
, Youfang Lin
, Huaiyu Wan, Shengnan Guo, Fan Wu, Lixia Wu, Chao Song
, Yinghui Xu:
DeepRoute+: Modeling Couriers' Spatial-temporal Behaviors and Decision Preferences for Package Pick-up Route Prediction. 24:1-24:23 - Zhe Jiang
, Wenchong He, Marcus Stephen Kirby, Arpan Man Sainju
, Shaowen Wang, Lawrence V. Stanislawski, Ethan Shavers, E. Lynn Usery:
Weakly Supervised Spatial Deep Learning for Earth Image Segmentation Based on Imperfect Polyline Labels. 25:1-25:20 - Wenchong He, Arpan Man Sainju
, Zhe Jiang
, Da Yan, Yang Zhou:
Earth Imagery Segmentation on Terrain Surface with Limited Training Labels: A Semi-supervised Approach based on Physics-Guided Graph Co-Training. 26:1-26:22 - Han Bao
, Xun Zhou
, Yiqun Xie
, Yingxue Zhang
, Yanhua Li
:
COVID-GAN+: Estimating Human Mobility Responses to COVID-19 through Spatio-temporal Generative Adversarial Networks with Enhanced Features. 27:1-27:23 - Bin Lu
, Xiaoying Gan
, Haiming Jin, Luoyi Fu, Xinbing Wang, Haisong Zhang:
Make More Connections: Urban Traffic Flow Forecasting with Spatiotemporal Adaptive Gated Graph Convolution Network. 28:1-28:25
- Liang Wang
, Zhiwen Yu, Bin Guo, Dingqi Yang, Lianbo Ma, Zhidan Liu, Fei Xiong:
Data-driven Targeted Advertising Recommendation System for Outdoor Billboard. 29:1-29:23 - Yulin He, Xuan Ye, Joshua Zhexue Huang, Philippe Fournier-Viger:
Bayesian Attribute Bagging-Based Extreme Learning Machine for High-Dimensional Classification and Regression. 30:1-30:26 - Qian Li
, Hao Peng
, Jianxin Li
, Congying Xia
, Renyu Yang
, Lichao Sun
, Philip S. Yu
, Lifang He
:
A Survey on Text Classification: From Traditional to Deep Learning. 31:1-31:41 - Guangliang Gao
, Zhifeng Bao
, Jie Cao
, A. Kai Qin
, Timos Sellis
:
Location-Centered House Price Prediction: A Multi-Task Learning Approach. 32:1-32:25 - Weichao Liang
, Zhiang Wu
, Zhe Li
, Yong Ge
:
CrimeTensor: Fine-Scale Crime Prediction via Tensor Learning with Spatiotemporal Consistency. 33:1-33:24
Volume 13, Number 3, June 2022
- Kai Zheng, Yong Li, Cyrus Shahabi, Hongzhi Yin
:
Introduction to the Special Issue on Intelligent Trajectory Analytics: Part II. 34:1-34:2 - Liwei Deng, Hao Sun, Rui Sun, Yan Zhao, Han Su:
Efficient and Effective Similar Subtrajectory Search: A Spatial-aware Comprehension Approach. 35:1-35:22 - Arun Sharma
, Shashi Shekhar:
Analyzing Trajectory Gaps to Find Possible Rendezvous Region. 36:1-36:23 - Bolong Zheng
, Lingfeng Ming, Qi Hu, Zhipeng Lü, Guanfeng Liu
, Xiaofang Zhou:
Supply-Demand-aware Deep Reinforcement Learning for Dynamic Fleet Management. 37:1-37:19 - Senzhang Wang
, Meiyue Zhang, Hao Miao, Zhaohui Peng, Philip S. Yu:
Multivariate Correlation-aware Spatio-temporal Graph Convolutional Networks for Multi-scale Traffic Prediction. 38:1-38:22 - Yifan Zhang
, Jinghuai Zhang, Jindi Zhang
, Jianping Wang
, Kejie Lu, L. Jeff Hong:
Integrating Algorithmic Sampling-Based Motion Planning with Learning in Autonomous Driving. 39:1-39:27 - Chenglong Fang, Feng Wang, Bin Yao, Jianqiu Xu
:
GPSClean: A Framework for Cleaning and Repairing GPS Data. 40:1-40:22 - Jianbin Huang, Longji Huang, Meijuan Liu, He Li, Qinglin Tan, Xiaoke Ma, Jiangtao Cui, De-Shuang Huang:
Deep Reinforcement Learning-based Trajectory Pricing on Ride-hailing Platforms. 41:1-41:19 - Lin Yao, Zhenyu Chen, Haibo Hu, Guowei Wu, Bin Wu:
Privacy Preservation for Trajectory Publication Based on Differential Privacy. 42:1-42:21 - Nan Han, Shaojie Qiao, Kun Yue, Jianbin Huang, Qiang He, Tingting Tang, Faliang Huang, Chunlin He, Chang-an Yuan:
Algorithms for Trajectory Points Clustering in Location-based Social Networks. 43:1-43:29 - Zhirun Zheng, Zhetao Li, Jie Li, Hongbo Jiang, Tong Li, Bin Guo:
Utility-aware and Privacy-preserving Trajectory Synthesis Model that Resists Social Relationship Privacy Attacks. 44:1-44:28
- Cheolhyeong Kim, Haeseong Moon, Hyung Ju Hwang
:
NEAR: Neighborhood Edge AggregatoR for Graph Classification. 45:1-45:17 - Lili Wei
, Congyan Lang, Liqian Liang, Songhe Feng
, Tao Wang, Shidi Chen:
Weakly Supervised Video Object Segmentation via Dual-attention Cross-branch Fusion. 46:1-46:20 - Runze Yan
, Xinwen Liu, Janine M. Dutcher
, Michael J. Tumminia, Daniella K. Villalba, Sheldon Cohen, J. David Creswell, Kasey G. Creswell, Jennifer Mankoff, Anind K. Dey, Afsaneh Doryab:
A Computational Framework for Modeling Biobehavioral Rhythms from Mobile and Wearable Data Streams. 47:1-47:27 - Yang Hu
, Adriane Chapman, Guihua Wen, Wendy Hall:
What Can Knowledge Bring to Machine Learning? - A Survey of Low-shot Learning for Structured Data. 48:1-48:45 - Fandel Lin
, Hsun-Ping Hsieh
:
Traveling Transporter Problem: Arranging a New Circular Route in a Public Transportation System Based on Heterogeneous Non-Monotonic Urban Data. 49:1-49:25 - Vinayak Gupta
, Srikanta Bedathur:
Doing More with Less: Overcoming Data Scarcity for POI Recommendation via Cross-Region Transfer. 50:1-50:24 - Nurendra Choudhary
, Charu C. Aggarwal, Karthik Subbian, Chandan K. Reddy:
Self-supervised Short-text Modeling through Auxiliary Context Generation. 51:1-51:21
Volume 13, Number 4, August 2022
- Qiang Yang, Yongxin Tong
, Yang Liu, Yangqiu Song, Hao Peng, Boi Faltings:
Introduction to the Special Issue on the Federated Learning: Algorithms, Systems, and Applications: Part 1. 52:1-52:3 - Jun Zhou, Longfei Zheng, Chaochao Chen
, Yan Wang
, Xiaolin Zheng, Bingzhe Wu, Cen Chen, Li Wang, Jianwei Yin:
Toward Scalable and Privacy-preserving Deep Neural Network via Algorithmic-Cryptographic Co-design. 53:1-53:21 - Rodolfo Stoffel Antunes
, Cristiano André da Costa, Arne Küderle, Imrana Abdullahi Yari, Björn M. Eskofier:
Federated Learning for Healthcare: Systematic Review and Architecture Proposal. 54:1-54:23 - Zhiwei Liu
, Liangwei Yang
, Ziwei Fan
, Hao Peng, Philip S. Yu:
Federated Social Recommendation with Graph Neural Network. 55:1-55:24 - Meng Jiang
, Taeho Jung, Ryan Karl, Tong Zhao:
Federated Dynamic Graph Neural Networks with Secure Aggregation for Video-based Distributed Surveillance. 56:1-56:23 - Ziheng Hu
, Hongtao Xie, Lingyun Yu, Xingyu Gao, Zhihua Shang, Yongdong Zhang:
Dynamic-Aware Federated Learning for Face Forgery Video Detection. 57:1-57:25 - Zhenghang Ren
, Liu Yang
, Kai Chen
:
Improving Availability of Vertical Federated Learning: Relaxing Inference on Non-overlapping Data. 58:1-58:20 - Di Chai
, Leye Wang
, Kai Chen
, Qiang Yang:
Efficient Federated Matrix Factorization Against Inference Attacks. 59:1-59:20 - Zelei Liu
, Yuanyuan Chen, Han Yu, Yang Liu, Lizhen Cui:
GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation in Federated Learning. 60:1-60:21 - Sicong Che
, Zhaoming Kong
, Hao Peng
, Lichao Sun
, Alex D. Leow
, Yong Chen
, Lifang He
:
Federated Multi-view Learning for Private Medical Data Integration and Analysis. 61:1-61:23 - Chuhan Wu
, Fangzhao Wu, Lingjuan Lyu, Yongfeng Huang, Xing Xie:
FedCTR: Federated Native Ad CTR Prediction with Cross-platform User Behavior Data. 62:1-62:19 - Sixu Hu
, Yuan Li
, Xu Liu
, Qinbin Li
, Zhaomin Wu
, Bingsheng He
:
The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems. 63:1-63:32 - Yan Kang
, Yang Liu, Xinle Liang
:
FedCVT: Semi-supervised Vertical Federated Learning with Cross-view Training. 64:1-64:16 - Hanchi Ren
, Jingjing Deng
, Xianghua Xie:
GRNN: Generative Regression Neural Network - A Data Leakage Attack for Federated Learning. 65:1-65:24 - Yuanyishu Tian, Yao Wan, Lingjuan Lyu, Dezhong Yao
, Hai Jin, Lichao Sun
:
FedBERT: When Federated Learning Meets Pre-training. 66:1-66:26 - Yuzhu Mao, Zihao Zhao, Guangfeng Yan
, Yang Liu, Tian Lan, Linqi Song
, Wenbo Ding
:
Communication-Efficient Federated Learning with Adaptive Quantization. 67:1-67:26 - Xu Guo
, Han Yu, Boyang Li, Hao Wang, Pengwei Xing, Siwei Feng, Zaiqing Nie, Chunyan Miao:
Federated Learning for Personalized Humor Recognition. 68:1-68:18
Volume 13, Number 5, October 2022
- Qiang Yang, Yongxin Tong
, Yang Liu, Yangqiu Song, Hao Peng, Boi Faltings:
Preface to Federated Learning: Algorithms, Systems, and Applications: Part 2. 69:1-69:2 - Xiaolong Xu, Wentao Liu, Yulan Zhang, Xuyun Zhang
, Wanchun Dou, Lianyong Qi, Md. Zakirul Alam Bhuiyan:
PSDF: Privacy-aware IoV Service Deployment with Federated Learning in Cloud-Edge Computing. 70:1-70:22 - Zhengyi Zhong
, Weidong Bao
, Ji Wang
, Xiaomin Zhu
, Xiongtao Zhang
:
FLEE: A Hierarchical Federated Learning Framework for Distributed Deep Neural Network over Cloud, Edge, and End Device. 71:1-71:24 - Trung Kien Dang
, Xiang Lan
, Jianshu Weng
, Mengling Feng
:
Federated Learning for Electronic Health Records. 72:1-72:17 - Shenghui Li
, Edith C. H. Ngai, Fanghua Ye, Thiemo Voigt:
Auto-weighted Robust Federated Learning with Corrupted Data Sources. 73:1-73:20 - Xue Jiang
, Xuebing Zhou, Jens Grossklags:
SignDS-FL: Local Differentially Private Federated Learning with Sign-based Dimension Selection. 74:1-74:22 - Bixiao Zeng
, Xiaodong Yang, Yiqiang Chen, Hanchao Yu, Yingwei Zhang:
CLC: A Consensus-based Label Correction Approach in Federated Learning. 75:1-75:23 - Chien-Lun Chen
, Sara Babakniya, Marco Paolieri
, Leana Golubchik:
Defending against Poisoning Backdoor Attacks on Federated Meta-learning. 76:1-76:25 - Lunchen Xie
, Jiaqi Liu
, Songtao Lu
, Tsung-Hui Chang
, Qingjiang Shi
:
An Efficient Learning Framework for Federated XGBoost Using Secret Sharing and Distributed Optimization. 77:1-77:28 - Dimitris Stripelis
, Paul M. Thompson
, José Luis Ambite
:
Semi-Synchronous Federated Learning for Energy-Efficient Training and Accelerated Convergence in Cross-Silo Settings. 78:1-78:29 - Georgios Damaskinos, Rachid Guerraoui, Anne-Marie Kermarrec
, Vlad Nitu
, Rhicheek Patra, François Taïani:
FLeet: Online Federated Learning via Staleness Awareness and Performance Prediction. 79:1-79:30 - Yijing Liu
, Dongming Han
, Jianwei Zhang
, Haiyang Zhu
, Mingliang Xu
, Wei Chen
:
Federated Multi-task Graph Learning. 80:1-80:27
- Fuxian Li
, Jie Feng
, Huan Yan
, Depeng Jin
, Yong Li
:
Crowd Flow Prediction for Irregular Regions with Semantic Graph Attention Network. 81:1-81:14 - Zongwei Wang
, Min Gao
, Jundong Li, Junwei Zhang, Jiang Zhong:
Gray-Box Shilling Attack: An Adversarial Learning Approach. 82:1-82:21 - Kai Di
, Yifeng Zhou, Fuhan Yan
, Jiuchuan Jiang, Shaofu Yang, Yichuan Jiang:
A Foraging Strategy with Risk Response for Individual Robots in Adversarial Environments. 83:1-83:29 - Sawan Rai
, Ramesh Chandra Belwal, Atul Gupta:
A Review on Source Code Documentation. 84:1-84:44 - Xiaoyu Chen
, Yingyan Zeng, Sungku Kang, Ran Jin:
INN: An Interpretable Neural Network for AI Incubation in Manufacturing. 85:1-85:23 - Ke Li
, Bin Guo
, Jiaqi Liu, Jiangtao Wang
, Haoyang Ren, Fei Yi
, Zhiwen Yu:
Dynamic Probabilistic Graphical Model for Progressive Fake News Detection on Social Media Platform. 86:1-86:24
Volume 13, Number 6, December 2022
- Rohit Verma
, Sugandh Pargal, Debasree Das, Tanusree Parbat, Sai Shankar Kambalapalli, Bivas Mitra, Sandip Chakraborty:
Impact of Driving Behavior on Commuter's Comfort During Cab Rides: Towards a New Perspective of Driver Rating. 87:1-87:25 - Lin Zhang
, Lixin Fan, Yong Luo, Ling-Yu Duan:
Intrinsic Performance Influence-based Participant Contribution Estimation for Horizontal Federated Learning. 88:1-88:24 - Siyuan Ren, Bin Guo
, Longbing Cao
, Ke Li, Jiaqi Liu, Zhiwen Yu:
DeepExpress: Heterogeneous and Coupled Sequence Modeling for Express Delivery Prediction. 89:1-89:22 - Qian Zheng
, Yueming Wang
, Zhenfang Hu
, Xiaobo Zhang
, Zhaohui Wu
, Gang Pan
:
Jointly Optimizing Expressional and Residual Models for 3D Facial Expression Removal. 90:1-90:17 - Wided Hammedi, Sidi Mohammed Senouci, Philippe Brunet, Metzli Ramirez-Martinez:
Two-Level Optimization to Reduce Waiting Time at Locks in Inland Waterway Transportation. 91:1-91:30 - Mohannad Elhamod
, Jie Bu
, Christopher Singh
, Matthew Redell
, Abantika Ghosh
, Viktor Podolskiy
, Wei-Cheng Lee
, Anuj Karpatne
:
CoPhy-PGNN: Learning Physics-guided Neural Networks with Competing Loss Functions for Solving Eigenvalue Problems. 92:1-92:23 - Yasan Ding
, Bin Guo
, Yan Liu
, Yunji Liang
, Haocheng Shen
, Zhiwen Yu
:
MetaDetector: Meta Event Knowledge Transfer for Fake News Detection. 93:1-93:25 - Yao Zhang
, Wenping Fan
, Qichen Hao
, Xinya Wu
, Min-Ling Zhang
:
CAFE and SOUP: Toward Adaptive VDI Workload Prediction. 94:1-94:28 - Junyi Dong
, Qingze Huo
, Silvia Ferrari
:
A Holistic Approach for Role Inference and Action Anticipation in Human Teams. 95:1-95:24 - Marius Hogräfer
, Marco Angelini
, Giuseppe Santucci
, Hans-Jörg Schulz
:
Steering-by-example for Progressive Visual Analytics. 96:1-96:26 - Xian Wu
, Chao Huang
, Pablo Robles-Granda
, Nitesh V. Chawla
:
Representation Learning on Variable Length and Incomplete Wearable-Sensory Time Series. 97:1-97:21 - Edgar Eduardo Ceh-Varela
, Huiping Cao
, Hady W. Lauw
:
Performance Evaluation of Aggregation-based Group Recommender Systems for Ephemeral Groups. 98:1-98:26 - Anirban Das
, Timothy Castiglia
, Shiqiang Wang
, Stacy Patterson
:
Cross-Silo Federated Learning for Multi-Tier Networks with Vertical and Horizontal Data Partitioning. 99:1-99:27 - Yue Hu
, Ao Qu
, Dan Work
:
Detecting Extreme Traffic Events Via a Context Augmented Graph Autoencoder. 101:1-101:23 - Tamir Tassa
, Alon Ben Horin
:
Privacy-preserving Collaborative Filtering by Distributed Mediation. 102:1-102:26 - Vinayak Gupta
, Srikanta Bedathur
, Sourangshu Bhattacharya
, Abir De
:
Modeling Continuous Time Sequences with Intermittent Observations using Marked Temporal Point Processes. 103:1-103:26 - Jinxiang Ou
, Yunheng Shen
, Feng Wang
, Qiao Liu
, Xuegong Zhang
, Hairong Lv
:
AggEnhance: Aggregation Enhancement by Class Interior Points in Federated Learning with Non-IID Data. 104:1-104:25 - Miguel Costa
, Diogo Costa
, Tiago Gomes
, Sandro Pinto
:
Shifting Capsule Networks from the Cloud to the Deep Edge. 105:1-105:25
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