{"id":"W2997720193","doi":"10.1609/aaai.v34i04.6116","title":"Efficient Projection-Free Online Methods with Stochastic Recursive Gradient","year":2020,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"Regret; Logarithm; Projection (relational algebra); Mathematical optimization; Computer science; Estimator; Regular polygon; Convex optimization; Algorithm; Mathematics; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001792598,0.0003139842,0.0004981707,0.0002763185,0.0003200727,0.0002750004,0.003170743,0.00009347224,0.0002433444],"category_scores_gemma":[0.01716744,0.0001817467,0.0001623015,0.002818297,0.0008412708,0.0001801168,0.0006937419,0.0006652481,0.0001327698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009238192,"about_ca_system_score_gemma":0.0002411452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002779113,"about_ca_topic_score_gemma":0.00002033929,"domain_scores_codex":[0.9950144,0.00009815078,0.00095662,0.0009893375,0.002415556,0.0005259275],"domain_scores_gemma":[0.9944142,0.0009850941,0.00073506,0.0005457329,0.003032306,0.0002876294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00344212,0.001379285,0.000168609,0.00009254401,0.0001295858,0.000006401782,0.0160391,0.09465931,0.03186542,0.2705164,0.001680268,0.580021],"study_design_scores_gemma":[0.0001253846,0.001506674,0.0001728164,0.0002018108,0.00003214072,0.00001280065,0.01117029,0.5936064,0.1727732,0.2197622,0.0002451885,0.0003911261],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1755107,0.00005622128,0.7937316,0.02502866,0.0006242075,0.002088381,0.00009075338,0.0001383463,0.002731149],"genre_scores_gemma":[0.9667203,0.000006644138,0.0324497,0.0002701282,0.0001757899,0.00005440427,8.65656e-7,0.00002804875,0.0002940756],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7912096,"threshold_uncertainty_score":0.9911114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3080010328745577,"score_gpt":0.4640144936352166,"score_spread":0.1560134607606589,"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."}}