NIST · ИТ · 652cb0dc2f9f344ed272
Proxima: A Proxy Model-Based Approach to Influence Analysis
Machine learning (ML)-based Artificial Intelligence (AI) systems rely on training data to perform optimally, but the internal workings of how ML models learn from and use this data are often a black- box. Influence analysis provides valuable insights into
NIST · ИТОфициальный источник · 2024-09-25
{
"title_en": "Proxima: A Proxy Model-Based Approach to Influence Analysis",
"designation": "",
"series": "",
"status": "",
"date": "2024-09-25",
"date_original": "September 25, 2024",
"url": "https://www.nist.gov/publications/proxima-proxy-model-based-approach-influence-analysis",
"source": "NIST Publications",
"display_en": "",
"authors_en": "Sunny Shree, Yu Lei, Raghu Kacker , David Kuhn",
"abstract_excerpt_en": "Machine learning (ML)-based Artificial Intelligence (AI) systems rely on training data to perform optimally, but the internal workings of how ML models learn from and use this data are often a black- box. Influence analysis provides valuable insights into",
"id": "652cb0dc2f9f344ed272",
"sources": [
"NIST Publications"
],
"source_records": [
{
"title_en": "Proxima: A Proxy Model-Based Approach to Influence Analysis",
"designation": "",
"series": "",
"status": "",
"date": "2024-09-25",
"date_original": "September 25, 2024",
"url": "https://www.nist.gov/publications/proxima-proxy-model-based-approach-influence-analysis",
"source": "NIST Publications",
"display_en": "",
"authors_en": "Sunny Shree, Yu Lei, Raghu Kacker , David Kuhn",
"abstract_excerpt_en": "Machine learning (ML)-based Artificial Intelligence (AI) systems rely on training data to perform optimally, but the internal workings of how ML models learn from and use this data are often a black- box. Influence analysis provides valuable insights into"
}
],
"translation_state": "none",
"possible_title_matches": 1
}