{"id":"W4289655252","doi":"10.1109/isit50566.2022.9834449","title":"The Optimal Sample Complexity of Matrix Completion with Hierarchical Similarity Graphs","year":2022,"lang":"en","type":"article","venue":"2022 IEEE International Symposium on Information Theory (ISIT)","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"National Science Foundation","keywords":"Matrix completion; Computer science; Stochastic block model; Recommender system; Matrix (chemical analysis); Rank (graph theory); Low-rank approximation; Computational complexity theory; Similarity (geometry); Context (archaeology); Sample complexity; Theoretical computer science; Algorithm; Mathematics; Combinatorics; Artificial intelligence; Machine learning; Cluster analysis","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007199433,0.00154114,0.00263544,0.0009208605,0.0009586613,0.002372026,0.003074024,0.002409676,0.003578879],"category_scores_gemma":[0.05199872,0.001215682,0.001020739,0.001552667,0.002438858,0.005988314,0.003164819,0.003592467,0.0007224879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002314122,"about_ca_system_score_gemma":0.003098705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005161197,"about_ca_topic_score_gemma":0.004606361,"domain_scores_codex":[0.9944031,0.002924713,0.0002299741,0.001135965,0.0008478687,0.0004583487],"domain_scores_gemma":[0.928524,0.06124298,0.002499856,0.004190936,0.002000649,0.001541498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0009995197,0.0005420994,0.002818292,0.0005125023,0.0001784768,0.000220743,0.0003395471,0.8372015,0.003525433,0.07173225,0.006208279,0.07572141],"study_design_scores_gemma":[0.00003943297,0.00006606893,0.0001963786,0.000008815417,0.00000845042,0.00003383193,0.00002546178,0.959235,0.000478275,0.03969491,0.0002003714,0.00001286058],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08400807,0.000592969,0.9106051,0.001373817,0.00005775222,0.0002521279,0.0004250123,0.0006408717,0.002044267],"genre_scores_gemma":[0.6314986,0.0005465039,0.3613276,0.0005251182,0.0002186497,0.0005834007,0.001670094,0.0003203691,0.003309739],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007199433,"threshold_uncertainty_score":0.03807473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01200499400515911,"score_gpt":0.2644584007602411,"score_spread":0.252453406755082,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}