·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Ahead of its IPO, Anthropic’s Daniela Amodei shrugs off doubts about AI’s returns23m◆Airbnb’s Brian Chesky plans to launch a new AI lab37m◆Defense tech, AI, and fundraising take center stage at StrictlyVC Los Angeles on June 181h◆Meta steals a tactic from Tesla and builds data centers in tents3h◆Apple approves Poke as the first AI agent on its Messages for Business platform3h◆Nemotron 3.5 Content Safety: Customizable Multimodal Safety for Global Enterprise AI4h◆Kevin O’Leary agrees to downsize massive Utah data center4h◆Meta rolls out a new AI creator assistant on Facebook6h◆What to expect from WWDC 2026: Siri’s highly anticipated revamp and Apple Intelligence updates6h◆Is Silicon Valley ready to put robots in people’s homes? Hello Robot is.8h◆TSMC struggles to keep up with AI demand: ‘We can only support so much’8h◆Apple touts $1.4 trillion in App Store billings and sales, 90% without a commission9h◆Elon Musk is steamrolling Wall Street to become a trillionaire9h◆How to Fine-Tune Nemotron 3.5 ASR for Your Language, Domain, or Accent10h◆Let us filter AI slop, you cowards10h◆EVA-Bench Data 2.0: 3 Domains, 121 Tools, 213 Scenarios10h◆AI leaders call for tougher protections against AI-aided bioweapons10h◆How Endava is redesigning software delivery around AI agents11h◆Task-Seeded Synthetic Q&A Generation for Nemotron Pretraining11h◆How courts are coping with a flood of AI-generated lawsuits12h◆Ahead of its IPO, Anthropic’s Daniela Amodei shrugs off doubts about AI’s returns23m◆Airbnb’s Brian Chesky plans to launch a new AI lab37m◆Defense tech, AI, and fundraising take center stage at StrictlyVC Los Angeles on June 181h◆Meta steals a tactic from Tesla and builds data centers in tents3h◆Apple approves Poke as the first AI agent on its Messages for Business platform3h◆Nemotron 3.5 Content Safety: Customizable Multimodal Safety for Global Enterprise AI4h◆Kevin O’Leary agrees to downsize massive Utah data center4h◆Meta rolls out a new AI creator assistant on Facebook6h◆What to expect from WWDC 2026: Siri’s highly anticipated revamp and Apple Intelligence updates6h◆Is Silicon Valley ready to put robots in people’s homes? Hello Robot is.8h◆TSMC struggles to keep up with AI demand: ‘We can only support so much’8h◆Apple touts $1.4 trillion in App Store billings and sales, 90% without a commission9h◆Elon Musk is steamrolling Wall Street to become a trillionaire9h◆How to Fine-Tune Nemotron 3.5 ASR for Your Language, Domain, or Accent10h◆Let us filter AI slop, you cowards10h◆EVA-Bench Data 2.0: 3 Domains, 121 Tools, 213 Scenarios10h◆AI leaders call for tougher protections against AI-aided bioweapons10h◆How Endava is redesigning software delivery around AI agents11h◆Task-Seeded Synthetic Q&A Generation for Nemotron Pretraining11h◆How courts are coping with a flood of AI-generated lawsuits12h◆
News/Promoting Simple Agents: Ensemble Methods for Event-Log Prediction
arxiv
PublishedApril 24, 2026 at 4:00 AM
—neutral

Promoting Simple Agents: Ensemble Methods for Event-Log Prediction

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2604.21629v1 Announce Type: cross Abstract: We compare lightweight automata-based models (n-grams) with neural architectures (LSTM, Transformer) for next-activity prediction in streaming event logs. Experiments on synthetic patterns and five real-world process mining datasets show that n-grams

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

// no spam · unsubscribe one-click · free forever

Discussion
Mentioned models
03
  • 01
    n-grams
  • 02
    LSTM
  • 03
    Transformer
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#machine learning#ensemble methods#process mining#neural architectures

No replies yet. Be first.

Mentioned models
03
  • 01
    n-grams
  • 02
    LSTM
  • 03
    Transformer
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#machine learning#ensemble methods#process mining#neural architectures
The Bubble Brief
WEEKLY

Read machine learning insights every Tuesday — top movers, new releases, story of the week.

// no spam · unsubscribe one-click · free forever

Originally published on arxiv ↗
HomeModelsNews