{"id":"W3171402832","doi":"10.48550/arxiv.2106.02154","title":"Laplacian-Based Dimensionality Reduction Including Spectral Clustering, Laplacian Eigenmap, Locality Preserving Projection, Graph Embedding, and Diffusion Map: Tutorial and Survey","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Spectral clustering; Laplacian matrix; Diffusion map; Adjacency matrix; Dimensionality reduction; Laplace operator; Nonlinear dimensionality reduction; Mathematics; Cluster analysis; Adjacency list; Spectral graph theory; Pattern recognition (psychology); Embedding; Locality; Graph; Computer science; Artificial intelligence; Algorithm; Combinatorics; Voltage graph; Line graph","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":[0.001111499,0.00160799,0.001698888,0.003052921,0.0005113198,0.001832969,0.001300694,0.001328191,0.003759424],"category_scores_gemma":[0.002720657,0.0007218792,0.0013486,0.005982017,0.001224996,0.003427558,0.001464566,0.00202745,0.002364129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007714891,"about_ca_system_score_gemma":0.0008837887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001532279,"about_ca_topic_score_gemma":0.001360758,"domain_scores_codex":[0.9992145,0.0001662464,0.00006779708,0.0002100793,0.0003030068,0.00003828683],"domain_scores_gemma":[0.9991253,0.0004450916,0.00004957768,0.0001148943,0.0002286449,0.00003646757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000424409,0.0001266452,0.0006959995,0.002369278,0.0001729996,0.0001219062,0.0002743457,0.01764661,0.004538532,0.08879223,0.03573316,0.8494858],"study_design_scores_gemma":[0.00002958172,0.0002951296,0.003103013,0.0006654134,0.0002019681,0.00202167,0.0004151517,0.2560244,0.01179522,0.3347339,0.390464,0.0002506718],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.004523053,0.1677406,0.8106923,0.002078483,0.0009010337,0.00008622205,0.0003004649,0.001115087,0.01256272],"genre_scores_gemma":[0.08588485,0.307661,0.5805405,0.001516738,0.004197233,0.0004013528,0.001785445,0.0009135086,0.01709933],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.003759424,"threshold_uncertainty_score":0.01257652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07931015357348536,"score_gpt":0.2284259706240454,"score_spread":0.1491158170505601,"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."}}