2025
A survey of dynamic graph neural networks.
Frontiers Comput. Sci., June, 2025
Scalable and Effective Graph Neural Networks via Trainable Random Walk Sampling.
IEEE Trans. Knowl. Data Eng., February, 2025
Large-Scale Spectral Graph Neural Networks via Laplacian Sparsification: Technical Report.
CoRR, January, 2025
2024
A survey on large language model based autonomous agents.
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Frontiers Comput. Sci., December, 2024
When Transformer Meets Large Graphs: An Expressive and Efficient Two-View Architecture.
IEEE Trans. Knowl. Data Eng., October, 2024
Efficient Algorithms for Personalized PageRank Computation: A Survey.
IEEE Trans. Knowl. Data Eng., September, 2024
Index-free triangle-based graph local clustering.
Frontiers Comput. Sci., June, 2024
Optimal Matrix Sketching over Sliding Windows.
Proc. VLDB Endow., May, 2024
Learning-based Property Estimation with Polynomials.
Proc. ACM Manag. Data, 2024
Fast Second-Order Online Kernel Learning through Incremental Matrix Sketching and Decomposition.
CoRR, 2024
Matrix Sketching in Bandits: Current Pitfalls and New Framework.
CoRR, 2024
Dynamic and Textual Graph Generation Via Large-Scale LLM-based Agent Simulation.
CoRR, 2024
Scalable and Accurate Graph Reasoning with LLM-based Multi-Agents.
CoRR, 2024
Rethinking the Expressiveness of GNNs: A Computational Model Perspective.
CoRR, 2024
Scalable and Certifiable Graph Unlearning via Lazy Local Propagation.
CoRR, 2024
Towards Effective and Efficient Continual Pre-training of Large Language Models.
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CoRR, 2024
Very Large-Scale Multi-Agent Simulation in AgentScope.
CoRR, 2024
YuLan: An Open-source Large Language Model.
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CoRR, 2024
PRICE: A Pretrained Model for Cross-Database Cardinality Estimation.
CoRR, 2024
A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications.
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CoRR, 2024
Exploring Neural Scaling Law and Data Pruning Methods For Node Classification on Large-scale Graphs.
Proceedings of the ACM on Web Conference 2024, 2024
Spectral Heterogeneous Graph Convolutions via Positive Noncommutative Polynomials.
Proceedings of the ACM on Web Conference 2024, 2024
GTP-ViT: Efficient Vision Transformers via Graph-based Token Propagation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
Revisiting Local Computation of PageRank: Simple and Optimal.
Proceedings of the 56th Annual ACM Symposium on Theory of Computing, 2024
S-MolSearch: 3D Semi-supervised Contrastive Learning for Bioactive Molecule Search.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Intruding with Words: Towards Understanding Graph Injection Attacks at the Text Level.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
PolyFormer: Scalable Node-wise Filters via Polynomial Graph Transformer.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024
EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Approximating Single-Source Personalized PageRank with Absolute Error Guarantees.
Proceedings of the 27th International Conference on Database Theory, 2024
SRAP-Agent: Simulating and Optimizing Scarce Resource Allocation Policy with LLM-based Agent.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
TransPocket: Structural and Geometric Transformer for Ligand Binding Site Detection.
Proceedings of the Database Systems for Advanced Applications, 2024
HierAffinity: Predicting Protein-Ligand Binding Affinity With Hierarchical Modeling.
Proceedings of the Database Systems for Advanced Applications, 2024
Beyond Over-smoothing: Uncovering the Trainability Challenges in Deep Graph Neural Networks.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024
Federated Heterogeneous Contrastive Distillation for Molecular Representation Learning.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024
2023
Enabling Efficient Random Access to Hierarchically Compressed Text Data on Diverse GPU Platforms.
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IEEE Trans. Parallel Distributed Syst., October, 2023
Decoupled Graph Neural Networks for Large Dynamic Graphs.
Proc. VLDB Endow., 2023
Personalized PageRank on Evolving Graphs with an Incremental Index-Update Scheme.
Proc. ACM Manag. Data, 2023
Estimating Single-Node PageRank in Õ(min{d<sub>t</sub>, √m}) Time.
CoRR, 2023
LON-GNN: Spectral GNNs with Learnable Orthonormal Basis.
CoRR, 2023
EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction.
CoRR, 2023
Do Deep Learning Methods Really Perform Better in Molecular Conformation Generation?
CoRR, 2023
Optimal Dynamic Subset Sampling: Theory and Applications.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Clenshaw Graph Neural Networks.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
MGNN: Graph Neural Networks Inspired by Distance Geometry Problem.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Graph Neural Networks with Learnable and Optimal Polynomial Bases.
Proceedings of the International Conference on Machine Learning, 2023
Uni-Mol: A Universal 3D Molecular Representation Learning Framework.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Preformer: Predictive Transformer with Multi-Scale Segment-Wise Correlations for Long-Term Time Series Forecasting.
Proceedings of the IEEE International Conference on Acoustics, 2023
On Range Summary Queries.
Proceedings of the 50th International Colloquium on Automata, Languages, and Programming, 2023
2022
ACM Trans. Database Syst., 2022
Influence Maximization Revisited: Efficient Sampling with Bound Tightened.
ACM Trans. Database Syst., 2022
Building Graphs at Scale via Sequence of Edges: Model and Generation Algorithms.
IEEE Trans. Knowl. Data Eng., 2022
Approximating Probabilistic Group Steiner Trees in Graphs.
Proc. VLDB Endow., 2022
Edge-based Local Push for Personalized PageRank.
Proc. VLDB Endow., 2022
GSN: A Universal Graph Neural Network Inspired by Spring Network.
CoRR, 2022
Optimizing Random Access to Hierarchically-Compressed Data on GPU.
Proceedings of the SC22: International Conference for High Performance Computing, 2022
EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Instant Graph Neural Networks for Dynamic Graphs.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Graph Neural Networks with Node-wise Architecture.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Sampling-based Estimation of the Number of Distinct Values in Distributed Environment.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Predicting Protein-Ligand Binding Affinity via Joint Global-Local Interaction Modeling.
Proceedings of the IEEE International Conference on Data Mining, 2022
Building Graphs at Scale via Sequence of Edges: Model and Generation Algorithms (Extended Abstract).
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022
MGMAE: Molecular Representation Learning by Reconstructing Heterogeneous Graphs with A High Mask Ratio.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
2021
ExactSim: benchmarking single-source SimRank algorithms with high-precision ground truths.
VLDB J., 2021
FlashP: An Analytical Pipeline for Real-time Forecasting of Time-Series Relational Data.
Proc. VLDB Endow., 2021
Learning to be a Statistician: Learned Estimator for Number of Distinct Values.
Proc. VLDB Endow., 2021
Massively Parallel Algorithms for Personalized PageRank.
Proc. VLDB Endow., 2021
Unifying the Global and Local Approaches: An Efficient Power Iteration with Forward Push.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021
BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Approximate Graph Propagation.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
Graph Neural Networks Inspired by Classical Iterative Algorithms.
Proceedings of the 38th International Conference on Machine Learning, 2021
2020
A game-based framework for crowdsourced data labeling.
VLDB J., 2020
SimTab: Accuracy-Guaranteed SimRank Queries through Tighter Confidence Bounds and Multi-Armed Bandits.
Proc. VLDB Endow., 2020
Exact Single-Source SimRank Computation on Large Graphs.
Proceedings of the 2020 International Conference on Management of Data, 2020
Influence Maximization Revisited: Efficient Reverse Reachable Set Generation with Bound Tightened.
Proceedings of the 2020 International Conference on Management of Data, 2020
Scalable Graph Neural Networks via Bidirectional Propagation.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Personalized PageRank to a Target Node, Revisited.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020
Simple and Deep Graph Convolutional Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020
2019
Efficient Algorithms for Approximate Single-Source Personalized PageRank Queries.
ACM Trans. Database Syst., 2019
Parallel Trajectory-to-Location Join.
IEEE Trans. Knowl. Data Eng., 2019
Distribution-Aware Crowdsourced Entity Collection.
IEEE Trans. Knowl. Data Eng., 2019
Efficient Estimation of Heat Kernel PageRank for Local Clustering.
Proceedings of the 2019 International Conference on Management of Data, 2019
PRSim: Sublinear Time SimRank Computation on Large Power-Law Graphs.
Proceedings of the 2019 International Conference on Management of Data, 2019
CrowdGame: A Game-Based Crowdsourcing System for Cost-Effective Data Labeling.
Proceedings of the 2019 International Conference on Management of Data, 2019
Scalable Graph Embeddings via Sparse Transpose Proximities.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019
2018
Parallel trajectory similarity joins in spatial networks.
VLDB J., 2018
Optimal algorithms for selecting top-k combinations of attributes: theory and applications.
VLDB J., 2018
Tight Space Bounds for Two-Dimensional Approximate Range Counting.
ACM Trans. Algorithms, 2018
Cost-Effective Data Annotation using Game-Based Crowdsourcing.
Proc. VLDB Endow., 2018
TopPPR: Top-k Personalized PageRank Queries with Precision Guarantees on Large Graphs.
Proceedings of the 2018 International Conference on Management of Data, 2018
2017
Trajectory Similarity Join in Spatial Networks.
Proc. VLDB Endow., 2017
ProbeSim: Scalable Single-Source and Top-k SimRank Computations on Dynamic Graphs.
Proc. VLDB Endow., 2017
FORA: Simple and Effective Approximate Single-Source Personalized PageRank.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017
Tracking Matrix Approximation over Distributed Sliding Windows.
Proceedings of the 33rd IEEE International Conference on Data Engineering, 2017
Independent Range Sampling, Revisited.
Proceedings of the 25th Annual European Symposium on Algorithms, 2017
2016
Collective Travel Planning in Spatial Networks.
IEEE Trans. Knowl. Data Eng., 2016
Dynamic Shortest Path Monitoring in Spatial Networks.
J. Comput. Sci. Technol., 2016
Matrix Sketching Over Sliding Windows.
Proceedings of the 2016 International Conference on Management of Data, 2016
Probabilistic Nearest Neighbor Query in Traffic-Aware Spatial Networks.
Proceedings of the Web Technologies and Applications - 18th Asia-Pacific Web Conference, 2016
2015
Towards Maximum Independent Sets on Massive Graphs.
Proc. VLDB Endow., 2015
Persistent Data Sketching.
Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, Melbourne, Victoria, Australia, May 31, 2015
2014
Indexing for summary queries: Theory and practice.
ACM Trans. Database Syst., 2014
Equivalence between Priority Queues and Sorting in External Memory.
Proceedings of the Algorithms - ESA 2014, 2014
2013
ACM Trans. Database Syst., 2013
The Space Complexity of 2-Dimensional Approximate Range Counting.
Proceedings of the Twenty-Fourth Annual ACM-SIAM Symposium on Discrete Algorithms, 2013
2011
Beyond simple aggregates: indexing for summary queries.
Proceedings of the 30th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, 2011
2009
Dynamic external hashing: the limit of buffering.
Proceedings of the SPAA 2009: Proceedings of the 21st Annual ACM Symposium on Parallelism in Algorithms and Architectures, 2009