{"id":"W3176263050","doi":"10.48550/arxiv.2011.09929","title":"Sample Complexity of Linear Quadratic Gaussian (LQG) Control for Output\\n Feedback Systems","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Control Systems and Identification","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Linear-quadratic-Gaussian control; Optimal projection equations; Control theory (sociology); Linear-quadratic regulator; Controller (irrigation); Mathematics; Robust control; Optimal control; Gaussian; Convex optimization; Open-loop controller; Computer science; Mathematical optimization; Control system; Regular polygon; Control engineering; Control (management); Engineering; Closed loop; Artificial intelligence","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":[0.003899612,0.001167029,0.001421456,0.0004340157,0.0005382549,0.001524827,0.001357491,0.001352315,0.002241961],"category_scores_gemma":[0.02133506,0.0006842343,0.0006902287,0.0004283321,0.002061831,0.002254167,0.002109506,0.002599816,0.0002205628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002129153,"about_ca_system_score_gemma":0.001994903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003774812,"about_ca_topic_score_gemma":0.002757212,"domain_scores_codex":[0.9974617,0.0009364826,0.0001227658,0.0004888216,0.0007947956,0.0001955014],"domain_scores_gemma":[0.9767049,0.02016685,0.001191025,0.0008260287,0.0008811073,0.000230021],"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":[0.0002424841,0.00006292992,0.0006829996,0.0002215903,0.00005003622,0.00009246475,0.0001301577,0.9326859,0.002237455,0.04387657,0.0004797308,0.01923781],"study_design_scores_gemma":[0.000009026879,0.00002993004,0.0001099838,0.000005394998,0.000002686185,0.000005617502,0.000006147694,0.9873407,0.0004458984,0.01195497,0.00008513802,0.000004533808],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0230575,0.0002721406,0.9739948,0.0003864451,0.0000271838,0.00004504915,0.00005911013,0.0001959746,0.001961853],"genre_scores_gemma":[0.9157127,0.0003286826,0.08057036,0.0002059829,0.00009393342,0.0002985696,0.0002879652,0.0001358992,0.002365993],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003899612,"threshold_uncertainty_score":0.02062339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1150047981889775,"score_gpt":0.1926877997760013,"score_spread":0.07768300158702378,"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."}}