[23’ICLR] Bo Hui, Da Yan, Xiaolong Ma, and Wei-Shinn Ku, “Rethinking Graph Lottery Tickets: Graph Sparsity Matters,” in the 11th International Conference on Learning Representations (ICLR, 2023).
[23’AAAI] Bo Hui, Yuchen Fang, Tian Xia, Sarp Aykent, and Wei-Shinn Ku, “Constrained Market Share
Maximization by Signal-guided Optimization,” in Proceedings of the 37th AAAI Conference on
Artificial Intelligence (AAAI, 2023).
[23’Neurips] Chao Jiang, Bo Hui, Bohan Liu, Da Ya, “Successfully Applying Lottery Ticket Hypothesis to Diffusion Model”, in 37th Conference on Neural Information Processing Systems workshop on diffusion models (Neurips 2023).
[22’KDD] Bo Hui and Wei-Shinn Ku, “Low-rank Nonnegative Tensor Decomposition in Hyperbolic Space,” in Proceedings of the 28th ACM SIGKDD International Conference on Knowledge
Discovery & Data Mining (KDD, 2022).
[22’ICDE] Bo Hui, Da Yan, Haiquan Chen, and Wei-Shinn Ku, “Time-sensitive POI Recommendation by Tensor Completion with Side Information,” in Proceedings of the 38th IEEE International Conference on Data Engineering (ICDE, 2022).
[22’EMNLP] Bo Hui, Tian Xia, and Wei-Shinn Ku, “A Localized Geometric Method to Match Knowledge in Low-dimensional Hyperbolic Space,” in Conference on Empirical Methods in Natural Language Processing (EMNLP, 2022).
[21’KDD] Bo Hui, Da Yan, Haiquan Chen, and Wei-Shinn Ku, “TrajNet: A Trajectory-Based
Deep Learning Model for Traffic Prediction,” in Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD, 2021).
[21’ICDE] Bo Hui, Haiquan Chen, Da Yan, and Wei-Shinn Ku, “EDGE: Entity-Diffusion Gaussian
Ensemble for Interpretable Tweet Geolocation Prediction,” in Proceedings of the 37th IEEE International Conference on Data Engineering (ICDE, 2021).
[21’ICDM] Bo Hui, Da Yan, Haiquan Chen, and Wei-Shinn Ku, “Trajectory WaveNet: A Trajectory-Based Model for Traffic Forecasting,” in Proceedings of the 21st IEEE International Conference on Data Mining (ICDM, 2021).
[20’CIKM] Bo Hui, Da Yan, Wei-Shinn Ku, and Wenlu Wang, “Predicting Economic Growth by
Region Embedding: A Multigraph Convolutional Network Approach,” in Proceedings of the
29th ACM International Conference on Information and Knowledge Management (CIKM, 2020).
[23’GECCO] Po-wei Harn, Bo Hui, Sai Deepthi Yeddula, Libo Sun, Min-Te Sun, and Wei-Shinn Ku, “A Novel Quadtree-Based Genetic Programming Search for Searchable Encryption Optimization,” in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), Lisboa, Portugal, 2023.
[23’SIGSPATIAL] Sai Deepthi Yeddula, Chen Jiang, Bo Hui and Wei-Shinn Ku, “Traffic Accident Hotspot Prediction Using Temporal Convolutional Networks: A Spatio-Temporal Approach”, in 31st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL, 2023).
[22’BigData] Tian Xia, Bo Hui, and Wei-Shinn Ku, “APIP: Attention-based Protein Representation
Learning for Protein-Ligand Interface Prediction,” in Proceedings of the IEEE International Conference
on Big Data (BigData, 2022).
[22’BigData] Po-Wei Harn, Sai Deepthi Yeddula, Bo Hui, Jie Zhang, Libo Sun, Min-Te Sun, and
Wei-Shinn Ku, “IGRP: Iterative Gradient Rank Pruning for Finding Graph Lottery Ticket,” in Proceedings of the IEEE International Conference
on Big Data (BigData, 2022).
[21’BigData] Bo Hui, Da Yan, and Wei-Shinn Ku, “Node-Polysemy Aware Recommendation by
Matrix Completion with Side Information,” in Proceedings of the IEEE International Conference
on Big Data (BigData, 2021).
[21’MSN] Bo Hui, Chen Jiang, Pavani Ankireddy, Wenlu Wang, and Wei-Shinn Ku, “Indoor Navigation for Users with Mobility Aids Using Smartphones and Neighborhood Networks,” In Proceedings of The 17th International Conference on Mobility, Sensing and Networking (MSN,
2021).