{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002336466,0.0008157771,0.001004966,0.0003600643,0.0003576333,0.001433457,0.001414922,0.0015048,0.002943009],"category_scores_gemma":[0.007789579,0.0005290754,0.0005180464,0.0004168369,0.001353531,0.002943731,0.003741803,0.003982764,0.0006993019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001054381,"about_ca_system_score_gemma":0.001106149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001345562,"about_ca_topic_score_gemma":0.002013647,"domain_scores_codex":[0.9986582,0.0004210988,0.0000515769,0.0002154463,0.0004730524,0.0001806614],"domain_scores_gemma":[0.9966415,0.001889324,0.0001915087,0.0007801364,0.0003875899,0.0001099605],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003708095,0.0001548891,0.00109365,0.0002796368,0.0001213809,0.0001132547,0.0001414485,0.6751804,0.01727909,0.09159052,0.007857666,0.2058171],"study_design_scores_gemma":[0.000004301661,0.00001852663,0.00006193067,0.000008920215,0.000004577671,0.00001204666,0.000007127078,0.9647947,0.002700316,0.03145419,0.0009303821,0.000002948287],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01155455,0.0003726501,0.9849315,0.000793388,0.00005616809,0.00002575126,0.00008937575,0.0007037909,0.001472816],"genre_scores_gemma":[0.7566227,0.0007778057,0.2300293,0.001025741,0.0001616456,0.00009991087,0.0004292214,0.0003402849,0.01051335],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002943009,"threshold_uncertainty_score":0.01235658,"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."}}