{"id":"W4304957737","doi":"10.1007/s10107-022-01899-0","title":"An elementary approach to tight worst case complexity analysis of gradient based methods","year":2022,"lang":"en","type":"article","venue":"Mathematical Programming","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Israel Science Foundation","keywords":"Mathematics; Gradient descent; Gradient method; Proximal Gradient Methods; Convergence (economics); Mathematical optimization; Applied mathematics; Stochastic gradient descent; Algorithm; Convex optimization; Regular polygon; Computer science; Artificial intelligence; Artificial neural network; Geometry","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":[0.009717066,0.003842619,0.002513623,0.003285435,0.001699763,0.005291441,0.005258108,0.002748579,0.01049938],"category_scores_gemma":[0.04820067,0.00159189,0.002755778,0.003010128,0.005676197,0.01068035,0.007551739,0.01452788,0.002313333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003319779,"about_ca_system_score_gemma":0.002909542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001589394,"about_ca_topic_score_gemma":0.001826072,"domain_scores_codex":[0.9913383,0.003086113,0.0003211445,0.001031223,0.003496801,0.0007264965],"domain_scores_gemma":[0.9743561,0.01840686,0.0009671833,0.003137741,0.002519565,0.0006125324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00008753147,0.0001165225,0.0002872094,0.0002768105,0.000078261,0.00009484277,0.0001839898,0.08050092,0.002302316,0.8810105,0.008336813,0.02672434],"study_design_scores_gemma":[0.00001049498,0.00005814807,0.0001938578,0.00007645322,0.00003111454,0.0000665431,0.00003028255,0.4141352,0.001308425,0.5788991,0.005162858,0.000027533],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001258625,0.0004844172,0.9898047,0.0009000502,0.0001644389,0.00003899236,0.00007705283,0.0001296933,0.00714199],"genre_scores_gemma":[0.2604559,0.004543494,0.6961448,0.003180946,0.003248433,0.001222437,0.0005968449,0.001710003,0.02889706],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01049938,"threshold_uncertainty_score":0.05138934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06827123328029666,"score_gpt":0.3411812919361203,"score_spread":0.2729100586558237,"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."}}