{
  "schema_version": "0.1.0",
  "record_type": "research-topic",
  "topic_id": "adaptive-scheduling",
  "label": "Adaptive Scheduling",
  "title": "Adaptive Scheduling Research",
  "description": "Adaptive Scheduling research papers in the Naser Ezzati-Jivan publication catalog.",
  "introduction": "This topic page groups Naser Ezzati-Jivan research papers related to adaptive scheduling. Each linked record provides the paper's problem, method, findings, limitations, keywords, and authoritative source links.",
  "aliases": [
    "adaptive scheduling"
  ],
  "search_terms": [
    "Adaptive Scheduling"
  ],
  "related_topics": [],
  "canonical_url": "https://threadslab.org/research-publications/topics/adaptive-scheduling.html",
  "paper_count": 2,
  "papers": [
    {
      "paper_id": "deba-adaptive-batch-scheduling",
      "title": "One Size Does Not Fit All: Architecture-Aware Adaptive Batch Scheduling with DEBA",
      "year": 2025,
      "authors": [
        "François Belias",
        "Naser Ezzati-Jivan",
        "Foutse Khomh"
      ],
      "page_url": "https://threadslab.org/research-publications/papers/deba-adaptive-batch-scheduling/",
      "canonical_source_url": "https://arxiv.org/abs/2511.03809",
      "core_contribution": "DEBA is an architecture-aware adaptive batch scheduler that uses training-stability signals to decide when and how to change batch size.",
      "tags": [
        "deep-learning-systems",
        "adaptive-scheduling",
        "performance-optimization",
        "architecture-aware-methods"
      ],
      "keywords": [
        "DEBA",
        "adaptive batch size",
        "gradient variance",
        "training speedup",
        "ResNet",
        "DenseNet",
        "EfficientNet",
        "ViT"
      ]
    },
    {
      "paper_id": "multi-level-adaptive-execution-tracing-performance-analysis",
      "title": "Multi-level Adaptive Execution Tracing for Efficient Performance Analysis",
      "year": 2023,
      "authors": [
        "Mohammed Adib Khan",
        "Naser Ezzati-Jivan"
      ],
      "page_url": "https://threadslab.org/research-publications/papers/multi-level-adaptive-execution-tracing-performance-analysis/",
      "canonical_source_url": "https://doi.org/10.1109/SERA57763.2023.10197790",
      "core_contribution": "The paper presents a multi-level adaptive tracing workflow that uses lightweight stress detection and performance evidence to change the application/kernel instrumentation scope during an investigation.",
      "tags": [
        "kernel-tracing",
        "system-tracing",
        "performance-analysis",
        "adaptive-scheduling"
      ],
      "keywords": [
        "adaptive execution tracing",
        "time-series trends",
        "multi-level tracing",
        "kernel tracing",
        "performance analysis",
        "SERA 2023"
      ]
    }
  ]
}