{"id":"W2021995874","doi":"10.1109/tit.2007.907498","title":"Lagrangian Optimization of Two-Description Scalar Quantizers","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Information Theory","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Lagrange multiplier; Parameterized complexity; Bounded function; Monotonic function; Mathematics; Mathematical optimization; Convex function; Function (biology); Computer science; Algorithm; Regular polygon","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":[],"consensus_categories":[],"category_scores_codex":[0.0009500045,0.0001349718,0.0001351463,0.0005828983,0.00016025,0.00006499364,0.0004679902,0.00008232801,0.0000627726],"category_scores_gemma":[0.00001527248,0.0001305678,0.00008335171,0.0005790688,0.0000711453,0.004667617,0.000004395396,0.0001695974,0.00005112249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006755807,"about_ca_system_score_gemma":0.00003020411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008779627,"about_ca_topic_score_gemma":0.000002073073,"domain_scores_codex":[0.9987149,0.0000773665,0.0005399984,0.0001375651,0.0003376996,0.0001925331],"domain_scores_gemma":[0.9987781,0.000157764,0.0002635483,0.0005339788,0.0001911483,0.00007545907],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001613163,0.0001348585,0.000003389684,0.00004142452,0.00002504732,8.908647e-7,0.001349533,0.4695062,0.003813807,0.1855347,0.0001869502,0.3392419],"study_design_scores_gemma":[0.001382713,0.0002630778,0.00007977224,0.0001492274,0.00002598932,0.00002374173,0.0004616477,0.2913989,0.6795707,0.02458218,0.001583019,0.0004790976],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0004833563,0.000008191886,0.9960047,0.00005012059,0.0004434992,0.000243422,0.00002029331,0.0004853258,0.002261075],"genre_scores_gemma":[0.714458,0.00002176013,0.2851716,0.000255169,0.00000958885,0.00001486394,0.00001297476,0.000007189401,0.00004890569],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7139747,"threshold_uncertainty_score":0.53244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01185354991545243,"score_gpt":0.2602401401358047,"score_spread":0.2483865902203523,"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."}}