{"id":"W4386578476","doi":"","title":"Towards Privacy Aware Deep Learning for Embedded Systems","year":2022,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Deep learning; Information privacy; Computer security; Human–computer interaction; Internet privacy; 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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.008959687,0.0002067592,0.0002534921,0.0001739566,0.001350401,0.0005037109,0.002376308,0.00006215536,0.00006884574],"category_scores_gemma":[0.002647771,0.0002353291,0.0001455001,0.000667711,0.00006437273,0.0004225226,0.002116014,0.0006028946,0.0000131856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001814892,"about_ca_system_score_gemma":0.000215915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003086952,"about_ca_topic_score_gemma":0.00004178588,"domain_scores_codex":[0.9900643,0.007942143,0.0003802855,0.0006537776,0.0005554527,0.0004040198],"domain_scores_gemma":[0.9953133,0.001936567,0.0003818224,0.001352815,0.0008857257,0.0001297289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001564106,0.0002804266,0.001056612,0.00008929199,0.00005762583,0.00001150128,0.02786903,0.1062404,0.0007690658,0.7497104,0.0004941151,0.1134059],"study_design_scores_gemma":[0.0006040076,0.000001358063,0.0004731051,0.00008596134,0.00001099932,0.00002917706,0.0005435486,0.9374087,0.000933618,0.001621921,0.05799798,0.0002896052],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005182377,0.0003309924,0.9767554,0.006431273,0.0004422828,0.000432272,0.000004990046,0.0005117818,0.009908563],"genre_scores_gemma":[0.8553866,0.00002071787,0.1386053,0.0001428114,0.00002441738,0.0002276107,0.00008890797,0.00003812387,0.00546559],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8502042,"threshold_uncertainty_score":0.9999497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01377738016322066,"score_gpt":0.2438185168851677,"score_spread":0.230041136721947,"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."}}