{
  "schema_version": "0.1.0",
  "record_type": "research-topic",
  "topic_id": "gradient-boosting",
  "label": "Gradient Boosting",
  "title": "Gradient Boosting Research",
  "description": "Gradient Boosting research papers in the Naser Ezzati-Jivan publication catalog.",
  "introduction": "This topic page groups Naser Ezzati-Jivan research papers related to gradient boosting. Each linked record provides the paper's problem, method, findings, limitations, keywords, and authoritative source links.",
  "aliases": [
    "gradient boosting"
  ],
  "search_terms": [
    "Gradient Boosting"
  ],
  "related_topics": [],
  "canonical_url": "https://threadslab.org/research-publications/topics/gradient-boosting.html",
  "paper_count": 1,
  "papers": [
    {
      "paper_id": "automatic-reduction-execution-trace-data-volume",
      "title": "Automatic Reduction of Execution Trace Data Volume Using Gradient Boosting in Large-Scale Microservice Systems",
      "year": 2024,
      "authors": [
        "Amir Haghshenas",
        "Naser Ezzati-Jivan",
        "Michel Dagenais"
      ],
      "page_url": "https://threadslab.org/research-publications/papers/automatic-reduction-execution-trace-data-volume/",
      "canonical_source_url": "https://doi.org/10.21428/594757db.fe8b76cf",
      "core_contribution": "The paper uses gradient boosting and feature importance to reduce the amount of trace data needed for microservice performance modeling.",
      "tags": [
        "microservices",
        "trace-reduction",
        "gradient-boosting",
        "performance-modeling",
        "resource-analysis"
      ],
      "keywords": [
        "trace data volume",
        "feature importance",
        "CPU demand",
        "memory demand",
        "Alibaba microservices",
        "inter-service communication"
      ]
    }
  ]
}