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MetaPerturb: Transferable Regularizer for Heterogeneous Tasks and
  Architectures

MetaPerturb: Transferable Regularizer for Heterogeneous Tasks and Architectures

13 June 2020
Jeongun Ryu
Jaewoong Shin
Haebeom Lee
Sung Ju Hwang
    AAML
    OOD
ArXivPDFHTML

Papers citing "MetaPerturb: Transferable Regularizer for Heterogeneous Tasks and Architectures"

5 / 5 papers shown
Title
Latent Paraphrasing: Perturbation on Layers Improves Knowledge Injection
  in Language Models
Latent Paraphrasing: Perturbation on Layers Improves Knowledge Injection in Language Models
Minki Kang
Sung Ju Hwang
Gibbeum Lee
Jaewoong Cho
KELM
32
0
0
01 Nov 2024
Learning Cross-Image Object Semantic Relation in Transformer for
  Few-Shot Fine-Grained Image Classification
Learning Cross-Image Object Semantic Relation in Transformer for Few-Shot Fine-Grained Image Classification
Bo-Wen Zhang
Jiakang Yuan
Baopu Li
Tao Chen
Jiayuan Fan
Botian Shi
ViT
13
31
0
02 Jul 2022
On the Importance of Distractors for Few-Shot Classification
On the Importance of Distractors for Few-Shot Classification
Rajshekhar Das
Yu-xiong Wang
José M. F. Moura
13
28
0
20 Sep 2021
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
278
11,677
0
09 Mar 2017
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
273
2,886
0
15 Sep 2016
1