{"id":"W3034755948","doi":"10.1109/icme46284.2020.9102797","title":"Lightweight Compression Of Neural Network Feature Tensors For Collaborative Intelligence","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Artificial neural network; Codec; Data compression; Compression (physics); Edge device; Code (set theory); Feature (linguistics); Inference; Enhanced Data Rates for GSM Evolution","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":[0.0003710139,0.0005541109,0.0002213828,0.0004961253,0.0002323375,0.0004903329,0.0005769547,0.0003803,0.002295438],"category_scores_gemma":[0.002522637,0.0001379274,0.0001872369,0.0006599633,0.0003636104,0.001091359,0.0006797988,0.0008903914,0.0006500813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005417818,"about_ca_system_score_gemma":0.0005281503,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002629921,"about_ca_topic_score_gemma":0.004723524,"domain_scores_codex":[0.9997492,0.00002320113,0.00001570195,0.00003425515,0.0001516386,0.00002594833],"domain_scores_gemma":[0.9993182,0.0002053043,0.00005667505,0.0002100979,0.0001861258,0.00002353887],"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":[0.0003403776,0.00009414261,0.001274531,0.0001058896,0.00003580701,0.000264465,0.0001815115,0.1061123,0.124156,0.01541064,0.007865655,0.7441587],"study_design_scores_gemma":[0.00002139152,0.0001053572,0.001143761,0.00002849983,0.00001217168,0.0002108965,0.00005011405,0.8533311,0.1261853,0.01001263,0.008877302,0.00002149575],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06623341,0.0004733704,0.926895,0.0003437276,0.0001635615,0.00007979093,0.0004008742,0.002211893,0.003198452],"genre_scores_gemma":[0.5840815,0.0004389426,0.4083084,0.0002277282,0.00007821748,0.0001333258,0.000988837,0.0002475225,0.005495468],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002629921,"threshold_uncertainty_score":0.007678986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03242712166723326,"score_gpt":0.2919537167898722,"score_spread":0.2595265951226389,"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."}}