Collective Knowledge Aggregator proof-of-concept
Crowdsourced experiments CK project Partners CK use cases AI powered by CK AI store Get CK

Files:
doc.bib    (1KB)
doc.pdf    (2430KB)

Cross-linking (dependencies):

Meta:
{
  "authors": [
    {
      "name": "0728a400aa1c86fe"
    }
  ], 
  "bib_ref": "cm:29db2248aba45e59:1943b3f46fabaee4", 
  "document_urls": [
    "http://arxiv.org/abs/1308.2410", 
    "http://hal.inria.fr/hal-00850880"
  ], 
  "local_bib": "doc.bib", 
  "local_doc": "doc.pdf", 
  "notes": [
    {
      "bold": "yes", 
      "italic": "yes", 
      "note": "Extended journal version: [$#cm_29db2248aba45e59_6f40bc99c4f7df58#$]"
    }, 
    {
      "italic": "yes", 
      "note": "This work summarizes my long-term vision on collaborative, systematic and reproducible benchmarking, optimization and co-design of computer systems across all software and hardware layers using public Collective Mind repository of knowledge, common plugin-based autotuning framework, big data, predictive analytics (machine learning, data mining, statistical analysis, feature detection), crowdsourcing and collective intelligence"
    }, 
    {
      "bold": "yes", 
      "italic": "yes", 
      "note": "This work extends my previous article [$#cm_29db2248aba45e59_0c44d9a2db3de3c9#$]"
    }, 
    {
      "italic": "yes", 
      "note": "Should be publicly available at some point in autumn, 2014"
    }, 
    {
      "italic": "yes", 
      "note": "Related Collective Mind infrastructure and repository [$#cm_d76ac3bb9a3f744c_bd5c924415bae775#$]"
    }, 
    {
      "bold": "yes", 
      "italic": "yes", 
      "note": "This work supports my initiative on open research and publication model where all experimental results and related material is continuously shared, validated and improved by the community [$#cm_29db2248aba45e59_40a4b58adfb594a8#$]. To set up an example, I continue sharing all benchmarks, datasets, tools, models and experimental results in Collective Mind repository (c-mind.org/repo)"
    }
  ], 
  "place": "France", 
  "publish_iso_date": "2013-06-01", 
  "reproducible": "yes", 
  "title": "Collective Mind: cleaning up the research and experimentation mess in computer engineering using crowdsourcing, big data and machine learning", 
  "type": {
    "name": "tech_report", 
    "peer_reviewed": "no", 
    "scope": "international"
  }, 
  "when": "2013", 
  "where": "INRIA technical report HAL-00850880"
}

API desc:
{}

If you notice copyrighted, inappropriate or illegal content that should not be here, please report us as soon as possible and we will try to remove it within 48hours!

Developed by dividiti,
cTuning foundation,
and the community
          
Implemented as a CK workflow
                     
   
   
                      Hosted at