{
  "version": "https://jsonfeed.org/version/1.1",
  "title": "Chijun Sima updates",
  "home_page_url": "https://www.chijunsima.com/",
  "feed_url": "https://www.chijunsima.com/feed.json",
  "description": "News and selected publications from the academic homepage of Chijun Sima.",
  "language": "en",
  "icon": "https://www.chijunsima.com/icon-512.svg",
  "favicon": "https://www.chijunsima.com/favicon.svg",
  "authors": [
    {
      "name": "Chijun Sima",
      "url": "https://www.chijunsima.com/"
    }
  ],
  "items": [
    {
      "id": "https://www.chijunsima.com/#news-1",
      "url": "https://www.chijunsima.com/#news",
      "title": "Reviewing for CVPR 2025",
      "content_text": "Reviewing for CVPR 2025",
      "date_published": "2025-01-01T00:00:00+08:00",
      "tags": [
        "news"
      ]
    },
    {
      "id": "https://www.chijunsima.com/#news-2",
      "url": "https://www.chijunsima.com/#news",
      "title": "Ekko published at OSDI 2022; invited talks at Tencent's WeChat division, DataFun, TechBeat",
      "content_text": "Ekko published at OSDI 2022; invited talks at Tencent's WeChat division, DataFun, TechBeat",
      "date_published": "2022-09-01T00:00:00+08:00",
      "tags": [
        "news"
      ]
    },
    {
      "id": "https://www.chijunsima.com/#news-3",
      "url": "https://www.chijunsima.com/#news",
      "title": "Tencent Technology Breakthrough Award (Gold Prize) — Project Lead, Ekko",
      "content_text": "Tencent Technology Breakthrough Award (Gold Prize) — Project Lead, Ekko",
      "date_published": "2022-08-01T00:00:00+08:00",
      "tags": [
        "news"
      ]
    },
    {
      "id": "https://www.chijunsima.com/#ekko-osdi-2022",
      "url": "https://www.chijunsima.com/#publications",
      "external_url": "https://www.usenix.org/conference/osdi22/presentation/sima",
      "title": "Ekko: A Large-Scale Deep Learning Recommender System with Low-Latency Model Update",
      "content_text": "OSDI '22. Low-latency model update system for multi-terabyte deep learning recommendation models, achieving 2.4s update latency, 10,000x model-size scaling, and large production impact in WeChat.",
      "date_published": "2022-01-01T00:00:00+08:00",
      "tags": [
        "publication"
      ]
    },
    {
      "id": "https://www.chijunsima.com/#dba-kernel-ieee-access-2019",
      "url": "https://www.chijunsima.com/#publications",
      "title": "Dynamic Barycenter Averaging Kernel in RBF Networks for Time Series Classification",
      "content_text": "IEEE Access. Time-series classification work on dynamic barycenter averaging kernels in RBF networks.",
      "date_published": "2019-01-01T00:00:00+08:00",
      "tags": [
        "publication"
      ]
    }
  ],
  "_meta": {
    "updatedAt": "2026-04-02T00:00:00+08:00"
  }
}