{
  "abstract": "Asynchronous SGD is a popular algorithm for distributed learning where each client's gradient update is applied on arrival. This leads to a speed-up, but also an increased vulnerability to attacks, as fast clients can dominate the total update. We introduce Throttle, a Byzantine-robust generalization of asynchronous SGD where the key idea is to exponentially down-weight updates from faster clients by a factor $q$. Both asynchronous SGD ($q=1$) and synchronous Byzantine-robust SGD ($q\\to\\infty$) correspond to specific settings of Throttle. We provide a theoretical analysis of the convergence rate and validate the robustness to attacks both theoretically and empirically. Remarkably, our experiments show that this down-weighting mechanism can also improve performance over standard asynchronous SGD even in the non-Byzantine setting.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.39357",
  "author_total": 5,
  "authors": [
    {
      "name": "Kaoru Otsuka"
    },
    {
      "name": "Maxime Meyer"
    },
    {
      "name": "Yuki Takezawa"
    },
    {
      "name": "Makoto Yamada"
    },
    {
      "name": "Anastasia Koloskova"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6ymkqv7149x01.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.39357",
  "fulltext_url": null,
  "id": "6ymkqv7149x01",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.39357",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.DC"
    ],
    [
      "arxiv",
      "cs.LG"
    ],
    [
      "arxiv",
      "math.OC"
    ],
    [
      "openalex",
      "1702|Stochastic Gradient Optimization Techniques"
    ]
  ],
  "openalex": "W7215114238",
  "pdf_url": "https://arxiv.org/pdf/2609.39357",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-30",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/6ymkqv7149x01.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:25:49Z",
      "native_id": "2609.39357",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.39357"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:math.OC",
      "subfield": "optimisation-control"
    }
  ],
  "title": "Robustifying Asynchronous SGD via Soft Throttling",
  "title_text": "Robustifying Asynchronous SGD via Soft Throttling",
  "type": "preprint",
  "updated_at": "2026-10-30T12:25:49Z",
  "url": "https://research.draconitic.com/paper/6ymkqv7149x01",
  "venue": "arXiv",
  "versions": []
}