{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/graph-clustering/papers/3","list_of":"/task/graph-clustering","task":"Graph Clustering","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":3,"pages_in_order":4,"rows_per_page":100,"rows":[201,300],"of":393,"counts":{"archive_papers_tagged":393,"with_a_code_link":180,"where_syntology_ran_a_sample":33,"not_listed_spam_title":0,"listed":393,"listed_where_code_ran":33,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":31,"every_run_a_failure_of_syntologys_instrument":2,"listed_with_a_run_with_no_instrument_failure":31,"listed_every_run_a_failure_of_syntologys_instrument":2,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/graph-clustering","prev":"/task/graph-clustering/papers/2","next":"/task/graph-clustering/papers/4","papers":[{"url":null,"slug":"dual-optimized-adaptive-graph-reconstruction","title":"Dual-Optimized Adaptive Graph Reconstruction for Multi-View Graph Clustering","date":"2024-10-30","arxiv_id":"2410.22983","repositories_listed":0,"syntology":null},{"url":null,"slug":"federated-temporal-graph-clustering","title":"Federated Temporal Graph Clustering","date":"2024-10-16","arxiv_id":"2410.12343","repositories_listed":0,"syntology":null},{"url":null,"slug":"similarity-enhanced-homophily-for-multi-view","title":"SiMilarity-Enhanced Homophily for Multi-View Heterophilous Graph Clustering","date":"2024-10-04","arxiv_id":"2410.03596","repositories_listed":0,"syntology":null},{"url":null,"slug":"toper-topological-embeddings-in-graph","title":"TopER: Topological Embeddings in Graph Representation Learning","date":"2024-10-02","arxiv_id":"2410.01778","repositories_listed":0,"syntology":null},{"url":null,"slug":"hyperedge-modeling-in-hypergraph-neural","title":"Hyperedge Modeling in Hypergraph Neural Networks by using Densest Overlapping Subgraphs","date":"2024-09-16","arxiv_id":"2409.10340","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-task-curriculum-graph-contrastive","title":"Multi-Task Curriculum Graph Contrastive Learning with Clustering Entropy Guidance","date":"2024-08-22","arxiv_id":"2408.12071","repositories_listed":0,"syntology":null},{"url":null,"slug":"structure-enhanced-contrastive-learning-for","title":"Structure-enhanced Contrastive Learning for Graph Clustering","date":"2024-08-19","arxiv_id":"2408.09790","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-clustering-with-cross-view-feature","title":"Graph Clustering with Cross-View Feature Propagation","date":"2024-08-12","arxiv_id":"2408.06029","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-and-adaptive-spectral-embedding-for","title":"Scalable and Adaptive Spectral Embedding for Attributed Graph Clustering","date":"2024-08-11","arxiv_id":"2408.05765","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-supervised-contrastive-graph-clustering","title":"Self-Supervised Contrastive Graph Clustering Network via Structural Information Fusion","date":"2024-08-08","arxiv_id":"2408.04339","repositories_listed":0,"syntology":null},{"url":null,"slug":"modularity-aided-consistent-attributed-graph","title":"Modularity aided consistent attributed graph clustering via coarsening","date":"2024-07-09","arxiv_id":"2407.07128","repositories_listed":0,"syntology":null},{"url":null,"slug":"stability-preserving-model-reduction-of","title":"Stability-Preserving Model Reduction of Networked Lur'e Systems","date":"2024-07-02","arxiv_id":"2407.02202","repositories_listed":0,"syntology":null},{"url":null,"slug":"expander-hierarchies-for-normalized-cuts-on","title":"Expander Hierarchies for Normalized Cuts on Graphs","date":"2024-06-20","arxiv_id":"2406.14111","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-models-and-knowledge-graphs-1","title":"Large Language Models and Knowledge Graphs for Astronomical Entity Disambiguation","date":"2024-06-17","arxiv_id":"2406.11400","repositories_listed":0,"syntology":null},{"url":null,"slug":"statistical-arbitrage-in-multi-pair-trading","title":"Statistical arbitrage in multi-pair trading strategy based on graph clustering algorithms in US equities market","date":"2024-06-15","arxiv_id":"2406.10695","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-near-linear-time-approximation-algorithm","title":"A Near-Linear Time Approximation Algorithm for Beyond-Worst-Case Graph Clustering","date":"2024-06-07","arxiv_id":"2406.04857","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-view-stochastic-block-models","title":"Multi-View Stochastic Block Models","date":"2024-06-07","arxiv_id":"2406.04860","repositories_listed":0,"syntology":null},{"url":null,"slug":"biharmonic-distance-of-graphs-and-its-higher","title":"Biharmonic Distance of Graphs and its Higher-Order Variants: Theoretical Properties with Applications to Centrality and Clustering","date":"2024-06-04","arxiv_id":"2406.07574","repositories_listed":0,"syntology":null},{"url":null,"slug":"cascade-based-randomization-for-inferring","title":"Cascade-based Randomization for Inferring Causal Effects under Diffusion Interference","date":"2024-05-20","arxiv_id":"2405.12340","repositories_listed":0,"syntology":null},{"url":null,"slug":"dgcformer-deep-graph-clustering-transformer","title":"DGCformer: Deep Graph Clustering Transformer for Multivariate Time Series Forecasting","date":"2024-05-14","arxiv_id":"2405.08440","repositories_listed":0,"syntology":null},{"url":null,"slug":"incorporating-higher-order-structural","title":"Incorporating Higher-order Structural Information for Graph Clustering","date":"2024-03-17","arxiv_id":"2403.11087","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-learning-methods-to-extract-empathy","title":"Graph learning methods to extract empathy supporting regions in a naturalistic stimuli fMRI","date":"2024-03-11","arxiv_id":"2403.07089","repositories_listed":0,"syntology":null},{"url":null,"slug":"provable-filter-for-real-world-graph","title":"Provable Filter for Real-world Graph Clustering","date":"2024-03-06","arxiv_id":"2403.03666","repositories_listed":0,"syntology":null},{"url":null,"slug":"randomized-algorithms-for-symmetric","title":"Randomized Algorithms for Symmetric Nonnegative Matrix Factorization","date":"2024-02-13","arxiv_id":"2402.08134","repositories_listed":0,"syntology":null},{"url":null,"slug":"blockchain-enabled-clustered-and-scalable","title":"Blockchain-enabled Clustered and Scalable Federated Learning (BCS-FL) Framework in UAV Networks","date":"2024-02-07","arxiv_id":"2402.05973","repositories_listed":0,"syntology":null},{"url":null,"slug":"maskclustering-view-consensus-based-mask","title":"MaskClustering: View Consensus based Mask Graph Clustering for Open-Vocabulary 3D Instance Segmentation","date":"2024-01-15","arxiv_id":"2401.07745","repositories_listed":0,"syntology":null},{"url":null,"slug":"masked-autoencoder-for-graph-clustering","title":"Masked AutoEncoder for Graph Clustering without Pre-defined Cluster Number k","date":"2024-01-09","arxiv_id":"2401.04741","repositories_listed":0,"syntology":null},{"url":null,"slug":"vsr-net-vessel-like-structure-rehabilitation","title":"VSR-Net: Vessel-like Structure Rehabilitation Network with Graph Clustering","date":"2023-12-20","arxiv_id":"2312.13116","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-low-rank-non-convex-norm-method-for","title":"A low-rank non-convex norm method for multiview graph clustering","date":"2023-12-18","arxiv_id":"2312.11157","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-uniform-clusters-on-hypersphere-for","title":"Learning Uniform Clusters on Hypersphere for Deep Graph-level Clustering","date":"2023-11-23","arxiv_id":"2311.13953","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-durel-annotation-tool-human-and","title":"The DURel Annotation Tool: Human and Computational Measurement of Semantic Proximity, Sense Clusters and Semantic Change","date":"2023-11-21","arxiv_id":"2311.12664","repositories_listed":0,"syntology":null},{"url":null,"slug":"community-aware-efficient-graph-contrastive","title":"Community-Aware Efficient Graph Contrastive Learning via Personalized Self-Training","date":"2023-11-18","arxiv_id":"2311.11073","repositories_listed":0,"syntology":null},{"url":null,"slug":"local-graph-clustering-with-noisy-labels","title":"Local Graph Clustering with Noisy Labels","date":"2023-10-12","arxiv_id":"2310.08031","repositories_listed":0,"syntology":null},{"url":null,"slug":"clustering-without-an-eigengap","title":"Gap-Free Clustering: Sensitivity and Robustness of SDP","date":"2023-08-29","arxiv_id":"2308.15642","repositories_listed":0,"syntology":null},{"url":null,"slug":"unified-and-dynamic-graph-for-temporal","title":"Unified and Dynamic Graph for Temporal Character Grouping in Long Videos","date":"2023-08-27","arxiv_id":"2308.14105","repositories_listed":0,"syntology":null},{"url":null,"slug":"transforming-graphs-for-enhanced-attribute","title":"Transforming Graphs for Enhanced Attribute Clustering: An Innovative Graph Transformer-Based Method","date":"2023-06-20","arxiv_id":"2306.11307","repositories_listed":0,"syntology":null},{"url":null,"slug":"arxiv4tgc-large-scale-datasets-for-temporal","title":"arXiv4TGC: Large-Scale Datasets for Temporal Graph Clustering","date":"2023-06-08","arxiv_id":"2306.04962","repositories_listed":0,"syntology":null},{"url":null,"slug":"g-2-uardfl-safeguarding-federated-learning","title":"G$^2$uardFL: Safeguarding Federated Learning Against Backdoor Attacks through Attributed Client Graph Clustering","date":"2023-06-08","arxiv_id":"2306.04984","repositories_listed":0,"syntology":null},{"url":null,"slug":"progressive-sub-graph-clustering-algorithm","title":"Progressive Sub-Graph Clustering Algorithm for Semi-Supervised Domain Adaptation Speaker Verification","date":"2023-05-22","arxiv_id":"2305.12703","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-factor-sequential-re-ranking-with","title":"Multi-factor Sequential Re-ranking with Perception-Aware Diversification","date":"2023-05-21","arxiv_id":"2305.12420","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-operators-on-graphs-spectral","title":"Transfer operators on graphs: Spectral clustering and beyond","date":"2023-05-19","arxiv_id":"2305.11766","repositories_listed":0,"syntology":null},{"url":null,"slug":"two-to-five-truths-in-non-negative-matrix","title":"Two to Five Truths in Non-Negative Matrix Factorization","date":"2023-05-06","arxiv_id":"2305.05389","repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastive-graph-clustering-in-curvature","title":"Contrastive Graph Clustering in Curvature Spaces","date":"2023-05-05","arxiv_id":"2305.03555","repositories_listed":0,"syntology":null},{"url":null,"slug":"human-semantic-segmentation-using-millimeter","title":"Human Semantic Segmentation using Millimeter-Wave Radar Sparse Point Clouds","date":"2023-04-27","arxiv_id":"2304.14132","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-prior-stochastic-block-model","title":"Neural-prior stochastic block model","date":"2023-03-17","arxiv_id":"2303.09995","repositories_listed":0,"syntology":null},{"url":null,"slug":"utilizing-technical-data-to-discover-similar","title":"Utilizing Technical Data to Discover Similar Companies in Dhaka Stock Exchange","date":"2023-01-11","arxiv_id":"2301.04455","repositories_listed":0,"syntology":null},{"url":null,"slug":"sample-level-multi-view-graph-clustering","title":"Sample-Level Multi-View Graph Clustering","date":"2023-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"constant-approximation-for-normalized","title":"Constant Approximation for Normalized Modularity and Associations Clustering","date":"2022-12-29","arxiv_id":"2212.14334","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-learning-the-structure-of-clusters-in","title":"On Learning the Structure of Clusters in Graphs","date":"2022-12-29","arxiv_id":"2212.14345","repositories_listed":0,"syntology":null},{"url":null,"slug":"influence-based-mini-batching-for-graph","title":"Influence-Based Mini-Batching for Graph Neural Networks","date":"2022-12-18","arxiv_id":"2212.09083","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-a-fast-3d-spectral-approach-to","title":"Learning a Fast 3D Spectral Approach to Object Segmentation and Tracking over Space and Time","date":"2022-12-15","arxiv_id":"2212.08058","repositories_listed":0,"syntology":null},{"url":null,"slug":"dual-information-enhanced-multi-view","title":"Dual Information Enhanced Multi-view Attributed Graph Clustering","date":"2022-11-28","arxiv_id":"2211.14987","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-and-effective-conductance-based","title":"Scalable and Effective Conductance-based Graph Clustering","date":"2022-11-22","arxiv_id":"2211.12511","repositories_listed":0,"syntology":null},{"url":null,"slug":"optimal-graph-filters-for-clustering","title":"Learning Optimal Graph Filters for Clustering of Attributed Graphs","date":"2022-11-09","arxiv_id":"2211.04634","repositories_listed":0,"syntology":null},{"url":null,"slug":"stochastic-parallelizable-eigengap-dilation","title":"Stochastic Parallelizable Eigengap Dilation for Large Graph Clustering","date":"2022-07-29","arxiv_id":"2207.14589","repositories_listed":0,"syntology":null},{"url":null,"slug":"flow-based-clustering-and-spectral-clustering","title":"flow-based clustering and spectral clustering: a comparison","date":"2022-06-20","arxiv_id":"2206.10019","repositories_listed":0,"syntology":null},{"url":null,"slug":"conversation-group-detection-with-spatio","title":"Conversation Group Detection With Spatio-Temporal Context","date":"2022-06-02","arxiv_id":"2206.02559","repositories_listed":0,"syntology":null},{"url":null,"slug":"simple-contrastive-graph-clustering","title":"Simple Contrastive Graph Clustering","date":"2022-05-11","arxiv_id":"2205.07865","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-graph-clustering-via-mutual-information","title":"Deep Graph Clustering via Mutual Information Maximization and Mixture Model","date":"2022-05-10","arxiv_id":"2205.05168","repositories_listed":0,"syntology":null},{"url":null,"slug":"reducing-neural-architecture-search-spaces","title":"Reducing Neural Architecture Search Spaces with Training-Free Statistics and Computational Graph Clustering","date":"2022-04-29","arxiv_id":"2204.14103","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-reduction-of-consensus-network-systems","title":"Model Reduction of Consensus Network Systems via Selection of Optimal Edge Weights and Nodal Time-Scales","date":"2022-03-27","arxiv_id":"2203.14377","repositories_listed":0,"syntology":null},{"url":null,"slug":"spectral-graph-clustering-for-intentional","title":"Spectral Graph Clustering for Intentional Islanding Operations in Resilient Hybrid Energy Systems","date":"2022-03-13","arxiv_id":"2203.06579","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-clustering-with-boltzmann-machines","title":"Graph clustering with Boltzmann machines","date":"2022-03-04","arxiv_id":"2203.02471","repositories_listed":0,"syntology":null},{"url":null,"slug":"skew-symmetric-adjacency-matrices-for","title":"Skew-Symmetric Adjacency Matrices for Clustering Directed Graphs","date":"2022-03-02","arxiv_id":"2203.01388","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-dynamic-mode-decomposition-approach-for","title":"A Dynamic Mode Decomposition Approach for Decentralized Spectral Clustering of Graphs","date":"2022-02-26","arxiv_id":"2203.00004","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-dual-correlation-reduction-network","title":"Improved Dual Correlation Reduction Network","date":"2022-02-25","arxiv_id":"2202.12533","repositories_listed":0,"syntology":null},{"url":null,"slug":"recovering-unbalanced-communities-in-the","title":"Recovering Unbalanced Communities in the Stochastic Block Model With Application to Clustering with a Faulty Oracle","date":"2022-02-17","arxiv_id":"2202.08522","repositories_listed":0,"syntology":null},{"url":null,"slug":"matrix-completion-with-hierarchical-graph-1","title":"Matrix Completion with Hierarchical Graph Side Information","date":"2022-01-02","arxiv_id":"2201.01728","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-deep-graph-clustering-with-random","title":"Scalable Deep Graph Clustering with Random-walk based Self-supervised Learning","date":"2021-12-31","arxiv_id":"2112.15530","repositories_listed":0,"syntology":null},{"url":null,"slug":"multilayer-graph-contrastive-clustering","title":"Multilayer Graph Contrastive Clustering Network","date":"2021-12-28","arxiv_id":"2112.14021","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-modular-framework-for-centrality-and","title":"A Modular Framework for Centrality and Clustering in Complex Networks","date":"2021-11-23","arxiv_id":"2111.11623","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-correlation-clustering-with-asymmetric","title":"Robust Correlation Clustering with Asymmetric Noise","date":"2021-10-15","arxiv_id":"2110.08385","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-supervised-contrastive-attributed-graph","title":"Self-supervised Contrastive Attributed Graph Clustering","date":"2021-10-15","arxiv_id":"2110.08264","repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-graph-clustering","title":"Weakly Supervised Graph Clustering","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-attributed-graph-clustering-with-self","title":"Deep attributed graph clustering with self-separation regularization and parameter-free cluster estimation","date":"2021-07-15","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-agglomerative-graph-clustering","title":"Hierarchical Agglomerative Graph Clustering in Nearly-Linear Time","date":"2021-06-10","arxiv_id":"2106.05610","repositories_listed":0,"syntology":null},{"url":null,"slug":"vertex-centric-visual-programming-for-graph","title":"Vertex-Centric Visual Programming for Graph Neural Networks","date":"2021-06-09","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"local-algorithms-for-estimating-effective","title":"Local Algorithms for Estimating Effective Resistance","date":"2021-06-07","arxiv_id":"2106.03476","repositories_listed":0,"syntology":null},{"url":null,"slug":"ell-2-norm-flow-diffusion-in-near-linear-time","title":"$\\ell_2$-norm Flow Diffusion in Near-Linear Time","date":"2021-05-30","arxiv_id":"2105.14629","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-survey-on-community-detection","title":"A Comprehensive Survey on Community Detection with Deep Learning","date":"2021-05-26","arxiv_id":"2105.12584","repositories_listed":0,"syntology":null},{"url":null,"slug":"seeing-all-from-a-few-nodes-selection-using","title":"Seeing All From a Few: Nodes Selection Using Graph Pooling for Graph Clustering","date":"2021-04-30","arxiv_id":"2105.05320","repositories_listed":0,"syntology":null},{"url":null,"slug":"seastar-vertex-centric-programming-for-graph","title":"Seastar: vertex-centric programming for graph neural networks","date":"2021-04-21","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"qd-gcn-query-driven-graph-convolutional","title":"Query Driven-Graph Neural Networks for Community Search: From Non-Attributed, Attributed, to Interactive Attributed","date":"2021-04-08","arxiv_id":"2104.03583","repositories_listed":0,"syntology":null},{"url":null,"slug":"multilayer-graph-clustering-with-optimized","title":"Multilayer Graph Clustering with Optimized Node Embedding","date":"2021-03-30","arxiv_id":"2103.16534","repositories_listed":0,"syntology":null},{"url":null,"slug":"weighted-graph-nodes-clustering-via-gumbel","title":"Weighted Graph Nodes Clustering via Gumbel Softmax","date":"2021-02-22","arxiv_id":"2102.10775","repositories_listed":0,"syntology":null},{"url":null,"slug":"effective-and-scalable-clustering-on-massive","title":"Effective and Scalable Clustering on Massive Attributed Graphs","date":"2021-02-07","arxiv_id":"2102.03826","repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-supervised-hyperspectral-image","title":"Semi-supervised Hyperspectral Image Classification with Graph Clustering Convolutional Networks","date":"2020-12-20","arxiv_id":"2012.10932","repositories_listed":0,"syntology":null},{"url":null,"slug":"product-graph-learning-from-multi-domain-data","title":"Product Graph Learning from Multi-domain Data with Sparsity and Rank Constraints","date":"2020-12-15","arxiv_id":"2012.08090","repositories_listed":0,"syntology":null},{"url":null,"slug":"gnn-xml-graph-neural-networks-for-extreme","title":"GNN-XML: Graph Neural Networks for Extreme Multi-label Text Classification","date":"2020-12-10","arxiv_id":"2012.05860","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-model-selection-in-switching-linear","title":"Efficient model selection in switching linear dynamic systems by graph clustering","date":"2020-12-08","arxiv_id":"2012.04543","repositories_listed":0,"syntology":null},{"url":null,"slug":"higher-order-spectral-clustering-of-directed","title":"Higher-Order Spectral Clustering of Directed Graphs","date":"2020-11-10","arxiv_id":"2011.05080","repositories_listed":0,"syntology":null},{"url":null,"slug":"monash-summ-longsumm-20-scisummpip-an","title":"Monash-Summ@LongSumm 20 SciSummPip: An Unsupervised Scientific Paper Summarization Pipeline","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"scisummpip-an-unsupervised-scientific-paper","title":"SciSummPip: An Unsupervised Scientific Paper Summarization Pipeline","date":"2020-10-19","arxiv_id":"2010.09190","repositories_listed":0,"syntology":null},{"url":null,"slug":"smoothness-sensor-adaptive-smoothness","title":"Smoothness Sensor: Adaptive Smoothness-Transition Graph Convolutions for Attributed Graph Clustering","date":"2020-09-12","arxiv_id":"2009.05743","repositories_listed":0,"syntology":null},{"url":null,"slug":"k-way-p-spectral-clustering-on-grassmann","title":"Multiway $p$-spectral graph cuts on Grassmann manifolds","date":"2020-08-30","arxiv_id":"2008.13210","repositories_listed":0,"syntology":null},{"url":null,"slug":"kcoremotif-an-efficient-graph-clustering","title":"KCoreMotif: An Efficient Graph Clustering Algorithm for Large Networks by Exploiting k-core Decomposition and Motifs","date":"2020-08-21","arxiv_id":"2008.10380","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-agent-reinforcement-learning-with-graph","title":"BGC: Multi-Agent Group Belief with Graph Clustering","date":"2020-08-20","arxiv_id":"2008.08808","repositories_listed":0,"syntology":null},{"url":null,"slug":"balanced-order-batching-with-task-oriented","title":"Balanced Order Batching with Task-Oriented Graph Clustering","date":"2020-08-19","arxiv_id":"2008.09018","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-free-optimal-control-of-linear-multi","title":"Model-Free Optimal Control of Linear Multi-Agent Systems via Decomposition and Hierarchical Approximation","date":"2020-08-14","arxiv_id":"2008.06604","repositories_listed":0,"syntology":null},{"url":null,"slug":"sketching-semidefinite-programs-for-faster","title":"Sketching semidefinite programs for faster clustering","date":"2020-08-10","arxiv_id":"2008.04270","repositories_listed":0,"syntology":null}],"record_sha256":"e20283e617670cf7391864e3a1bf389d6e78644cddb17b777c2b4b496737a42f","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}