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. 2308.08354
  4. Cited By
Is Meta-Learning the Right Approach for the Cold-Start Problem in
  Recommender Systems?

Is Meta-Learning the Right Approach for the Cold-Start Problem in Recommender Systems?

16 August 2023
Davide Buffelli
Ashish Gupta
Agnieszka Strzalka
Vassilis Plachouras
    OffRL
    LRM
ArXivPDFHTML

Papers citing "Is Meta-Learning the Right Approach for the Cold-Start Problem in Recommender Systems?"

3 / 3 papers shown
Title
Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning
Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning
Yinbo Chen
Zhuang Liu
Huijuan Xu
Trevor Darrell
Xiaolong Wang
158
339
0
09 Mar 2020
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness
  of MAML
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML
Aniruddh Raghu
M. Raghu
Samy Bengio
Oriol Vinyals
170
634
0
19 Sep 2019
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
243
11,568
0
09 Mar 2017
1