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Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot
  Meta-Learning

Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning

28 May 2021
Nan Ding
Xi Chen
Tomer Levinboim
Sebastian Goodman
Radu Soricut
ArXivPDFHTML

Papers citing "Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning"

10 / 10 papers shown
Title
Bayes meets Bernstein at the Meta Level: an Analysis of Fast Rates in
  Meta-Learning with PAC-Bayes
Bayes meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes
Charles Riou
Pierre Alquier
Badr-Eddine Chérief-Abdellatif
43
8
0
23 Feb 2023
Improving Robust Generalization by Direct PAC-Bayesian Bound
  Minimization
Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization
Zifa Wang
Nan Ding
Tomer Levinboim
Xi Chen
Radu Soricut
AAML
35
5
0
22 Nov 2022
Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior:
  From Theory to Practice
Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice
Jonas Rothfuss
Martin Josifoski
Vincent Fortuin
Andreas Krause
40
7
0
14 Nov 2022
Hardness-guided domain adaptation to recognise biomedical named entities
  under low-resource scenarios
Hardness-guided domain adaptation to recognise biomedical named entities under low-resource scenarios
Ngoc Dang Nguyen
Lan Du
Wray L. Buntine
Changyou Chen
Richard Beare
23
7
0
11 Nov 2022
Learning New Tasks from a Few Examples with Soft-Label Prototypes
Learning New Tasks from a Few Examples with Soft-Label Prototypes
Avyav Kumar Singh
Ekaterina Shutova
H. Yannakoudakis
VLM
27
0
0
31 Oct 2022
PACTran: PAC-Bayesian Metrics for Estimating the Transferability of
  Pretrained Models to Classification Tasks
PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks
Nan Ding
Xi Chen
Tomer Levinboim
Soravit Changpinyo
Radu Soricut
22
26
0
10 Mar 2022
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
177
639
0
19 Sep 2019
Bayesian Model-Agnostic Meta-Learning
Bayesian Model-Agnostic Meta-Learning
Taesup Kim
Jaesik Yoon
Ousmane Amadou Dia
Sungwoong Kim
Yoshua Bengio
Sungjin Ahn
UQCV
BDL
202
498
0
11 Jun 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language
  Understanding
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Jinpeng Wang
Amanpreet Singh
Julian Michael
Felix Hill
Omer Levy
Samuel R. Bowman
ELM
297
6,959
0
20 Apr 2018
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
338
11,684
0
09 Mar 2017
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