{"id":"W2753160622","doi":"","title":"Optimization as a Model for Few-Shot Learning","year":2017,"lang":"en","type":"article","venue":"International Conference on Learning Representations","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":2447,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computer science; Initialization; Artificial intelligence; Meta learning (computer science); Convergence (economics); Deep learning; Metric (unit); Artificial neural network; Machine learning; Set (abstract data type); Parametrization (atmospheric modeling); Competitive learning; Class (philosophy); Domain (mathematical analysis); Learning to learn; Mathematics; Task (project management)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1464190826716082,"score_gpt":0.4031299499396052,"score_spread":0.256710867267997,"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."}}