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. 2410.05942
  4. Cited By
Single Point-Based Distributed Zeroth-Order Optimization with a
  Non-Convex Stochastic Objective Function

Single Point-Based Distributed Zeroth-Order Optimization with a Non-Convex Stochastic Objective Function

8 October 2024
Elissa Mhanna
Mohamad Assaad
ArXivPDFHTML

Papers citing "Single Point-Based Distributed Zeroth-Order Optimization with a Non-Convex Stochastic Objective Function"

3 / 3 papers shown
Title
How to Boost Any Loss Function
How to Boost Any Loss Function
Richard Nock
Yishay Mansour
39
0
0
02 Jul 2024
Rendering Wireless Environments Useful for Gradient Estimators: A Zero-Order Stochastic Federated Learning Method
Rendering Wireless Environments Useful for Gradient Estimators: A Zero-Order Stochastic Federated Learning Method
Elissa Mhanna
Mohamad Assaad
49
1
0
30 Jan 2024
Kernel-based methods for bandit convex optimization
Kernel-based methods for bandit convex optimization
Sébastien Bubeck
Ronen Eldan
Y. Lee
84
164
0
11 Jul 2016
1