·
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 returns4h◆Airbnb’s Brian Chesky plans to launch a new AI lab4h◆Defense tech, AI, and fundraising take center stage at StrictlyVC Los Angeles on June 185h◆Meta steals a tactic from Tesla and builds data centers in tents7h◆Apple approves Poke as the first AI agent on its Messages for Business platform7h◆Nemotron 3.5 Content Safety: Customizable Multimodal Safety for Global Enterprise AI7h◆Kevin O’Leary agrees to downsize massive Utah data center8h◆Meta rolls out a new AI creator assistant on Facebook10h◆What to expect from WWDC 2026: Siri’s highly anticipated revamp and Apple Intelligence updates10h◆Is Silicon Valley ready to put robots in people’s homes? Hello Robot is.11h◆TSMC struggles to keep up with AI demand: ‘We can only support so much’12h◆Apple touts $1.4 trillion in App Store billings and sales, 90% without a commission12h◆Elon Musk is steamrolling Wall Street to become a trillionaire12h◆How to Fine-Tune Nemotron 3.5 ASR for Your Language, Domain, or Accent13h◆Let us filter AI slop, you cowards14h◆EVA-Bench Data 2.0: 3 Domains, 121 Tools, 213 Scenarios14h◆AI leaders call for tougher protections against AI-aided bioweapons14h◆How Endava is redesigning software delivery around AI agents14h◆Task-Seeded Synthetic Q&A Generation for Nemotron Pretraining15h◆How courts are coping with a flood of AI-generated lawsuits15h◆Ahead of its IPO, Anthropic’s Daniela Amodei shrugs off doubts about AI’s returns4h◆Airbnb’s Brian Chesky plans to launch a new AI lab4h◆Defense tech, AI, and fundraising take center stage at StrictlyVC Los Angeles on June 185h◆Meta steals a tactic from Tesla and builds data centers in tents7h◆Apple approves Poke as the first AI agent on its Messages for Business platform7h◆Nemotron 3.5 Content Safety: Customizable Multimodal Safety for Global Enterprise AI7h◆Kevin O’Leary agrees to downsize massive Utah data center8h◆Meta rolls out a new AI creator assistant on Facebook10h◆What to expect from WWDC 2026: Siri’s highly anticipated revamp and Apple Intelligence updates10h◆Is Silicon Valley ready to put robots in people’s homes? Hello Robot is.11h◆TSMC struggles to keep up with AI demand: ‘We can only support so much’12h◆Apple touts $1.4 trillion in App Store billings and sales, 90% without a commission12h◆Elon Musk is steamrolling Wall Street to become a trillionaire12h◆How to Fine-Tune Nemotron 3.5 ASR for Your Language, Domain, or Accent13h◆Let us filter AI slop, you cowards14h◆EVA-Bench Data 2.0: 3 Domains, 121 Tools, 213 Scenarios14h◆AI leaders call for tougher protections against AI-aided bioweapons14h◆How Endava is redesigning software delivery around AI agents14h◆Task-Seeded Synthetic Q&A Generation for Nemotron Pretraining15h◆How courts are coping with a flood of AI-generated lawsuits15h◆
News/Nonlinear Equilibrium Transitions in a Potential Game Model for Federated Learning
arxiv
PublishedJune 2, 2026 at 4:00 AM
—neutral

Nonlinear Equilibrium Transitions in a Potential Game Model for Federated Learning

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

arXiv:2411.11793v2 Announce Type: replace Abstract: In federated learning (FL), a central server typically allocates training efforts to clients. However, from a market-oriented perspective, clients may independently choose their training efforts based on rational self-interest. To study this settin

Stay posted· Newsletter

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

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

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →
The Bubble Brief
WEEKLY

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

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

Originally published on arxiv ↗
HomeModelsNews