ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2301.06148
  4. Cited By
Computability of Optimizers

Computability of Optimizers

15 January 2023
Yunseok Lee
Holger Boche
Gitta Kutyniok
ArXivPDFHTML

Papers citing "Computability of Optimizers"

5 / 5 papers shown
Title
Bias Detection via Maximum Subgroup Discrepancy
Bias Detection via Maximum Subgroup Discrepancy
Jiří Němeček
Mark Kozdoba
Illia Kryvoviaz
Tomáš Pevný
Jakub Mareˇcek
89
0
0
04 Feb 2025
Computability of Classification and Deep Learning: From Theoretical
  Limits to Practical Feasibility through Quantization
Computability of Classification and Deep Learning: From Theoretical Limits to Practical Feasibility through Quantization
Holger Boche
Vít Fojtík
Adalbert Fono
Gitta Kutyniok
21
0
0
12 Aug 2024
Reliable AI: Does the Next Generation Require Quantum Computing?
Reliable AI: Does the Next Generation Require Quantum Computing?
Aras Bacho
Holger Boche
Gitta Kutyniok
9
2
0
03 Jul 2023
Learning of Linear Dynamical Systems as a Non-Commutative Polynomial
  Optimization Problem
Learning of Linear Dynamical Systems as a Non-Commutative Polynomial Optimization Problem
Quan-Gen Zhou
Jakub Mareˇcek
8
1
0
04 Feb 2020
Improving neural networks by preventing co-adaptation of feature
  detectors
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton
Nitish Srivastava
A. Krizhevsky
Ilya Sutskever
Ruslan Salakhutdinov
VLM
237
7,597
0
03 Jul 2012
1