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Meta-learning with differentiable closed-form solvers

Meta-learning with differentiable closed-form solvers

21 May 2018
Luca Bertinetto
João F. Henriques
Philip Torr
Andrea Vedaldi
    ODL
ArXivPDFHTML

Papers citing "Meta-learning with differentiable closed-form solvers"

50 / 179 papers shown
Title
Adaptation-Agnostic Meta-Training
Adaptation-Agnostic Meta-Training
Jiaxin Chen
Li-Ming Zhan
Xiao-Ming Wu
K. F. Chung
26
0
0
24 Aug 2021
Relational Embedding for Few-Shot Classification
Relational Embedding for Few-Shot Classification
Dahyun Kang
Heeseung Kwon
Juhong Min
Minsu Cho
34
185
0
22 Aug 2021
Prototype Completion for Few-Shot Learning
Prototype Completion for Few-Shot Learning
Baoquan Zhang
Xutao Li
Yunming Ye
Shanshan Feng
VLM
60
18
0
11 Aug 2021
The Role of Global Labels in Few-Shot Classification and How to Infer
  Them
The Role of Global Labels in Few-Shot Classification and How to Infer Them
Ruohan Wang
Massimiliano Pontil
C. Ciliberto
VLM
34
17
0
09 Aug 2021
Joint Inductive and Transductive Learning for Video Object Segmentation
Joint Inductive and Transductive Learning for Video Object Segmentation
Yunyao Mao
Ning Wang
Wen-gang Zhou
Houqiang Li
VOS
30
98
0
08 Aug 2021
Few-shot Unsupervised Domain Adaptation with Image-to-class Sparse
  Similarity Encoding
Few-shot Unsupervised Domain Adaptation with Image-to-class Sparse Similarity Encoding
Sheng Huang
Wanqi Yang
Lei Wang
Luping Zhou
Ming Yang
30
8
0
06 Aug 2021
Few-Shot and Continual Learning with Attentive Independent Mechanisms
Few-Shot and Continual Learning with Attentive Independent Mechanisms
Eugene Lee
Cheng-Han Huang
Chen-Yi Lee
CLL
23
25
0
29 Jul 2021
Bayesian Embeddings for Few-Shot Open World Recognition
Bayesian Embeddings for Few-Shot Open World Recognition
John Willes
James Harrison
Ali Harakeh
Chelsea Finn
Marco Pavone
Steven Waslander
BDL
OffRL
22
18
0
29 Jul 2021
ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback
ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback
Mike Wu
Noah D. Goodman
Chris Piech
Chelsea Finn
35
19
0
23 Jul 2021
Few-shot Learning with Global Relatedness Decoupled-Distillation
Few-shot Learning with Global Relatedness Decoupled-Distillation
Yuanen Zhou
Yanrong Guo
Shijie Hao
Richang Hong
Zhen junzha
Meng Wang
21
1
0
12 Jul 2021
Representation based meta-learning for few-shot spoken intent
  recognition
Representation based meta-learning for few-shot spoken intent recognition
Ashish R. Mittal
Samarth Bharadwaj
Shreya Khare
Saneem A. Chemmengath
Karthik Sankaranarayanan
Brian Kingsbury
20
12
0
29 Jun 2021
Bridging Multi-Task Learning and Meta-Learning: Towards Efficient
  Training and Effective Adaptation
Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation
Haoxiang Wang
Han Zhao
Bo-wen Li
37
88
0
16 Jun 2021
ECKPN: Explicit Class Knowledge Propagation Network for Transductive
  Few-shot Learning
ECKPN: Explicit Class Knowledge Propagation Network for Transductive Few-shot Learning
Chaofan CHEN
Xiaoshan Yang
Changsheng Xu
Xuhui Huang
Zhe Ma
28
50
0
16 Jun 2021
On the Power of Multitask Representation Learning in Linear MDP
On the Power of Multitask Representation Learning in Linear MDP
Rui Lu
Gao Huang
S. Du
27
28
0
15 Jun 2021
Learning to Affiliate: Mutual Centralized Learning for Few-shot
  Classification
Learning to Affiliate: Mutual Centralized Learning for Few-shot Classification
Yang Liu
Weifeng Zhang
Chao Xiang
Tu Zheng
Deng Cai
Xiaofei He
FedML
17
47
0
10 Jun 2021
Tensor feature hallucination for few-shot learning
Tensor feature hallucination for few-shot learning
Michalis Lazarou
Tania Stathaki
Yannis Avrithis
29
22
0
09 Jun 2021
Provably Faster Algorithms for Bilevel Optimization
Provably Faster Algorithms for Bilevel Optimization
Junjie Yang
Kaiyi Ji
Yingbin Liang
49
132
0
08 Jun 2021
BR-NPA: A Non-Parametric High-Resolution Attention Model to improve the
  Interpretability of Attention
BR-NPA: A Non-Parametric High-Resolution Attention Model to improve the Interpretability of Attention
T. Gomez
Suiyi Ling
Thomas Fréour
Harold Mouchère
12
5
0
04 Jun 2021
Stochastic Whitening Batch Normalization
Stochastic Whitening Batch Normalization
Shengdong Zhang
E. Nezhadarya
H. Fashandi
Jiayi Liu
Darin Graham
Mohak Shah
18
10
0
03 Jun 2021
Few-shot Learning for Topic Modeling
Few-shot Learning for Topic Modeling
Tomoharu Iwata
BDL
27
6
0
19 Apr 2021
Reward Optimization for Neural Machine Translation with Learned Metrics
Reward Optimization for Neural Machine Translation with Learned Metrics
Raphael Shu
Kang Min Yoo
Jung-Woo Ha
32
12
0
15 Apr 2021
Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot
  Classification Benchmark
Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark
Vincent Dumoulin
N. Houlsby
Utku Evci
Xiaohua Zhai
Ross Goroshin
Sylvain Gelly
Hugo Larochelle
27
26
0
06 Apr 2021
Multi-level Metric Learning for Few-shot Image Recognition
Multi-level Metric Learning for Few-shot Image Recognition
Haoxing Chen
Huaxiong Li
Yaohui Li
Chunlin Chen
24
21
0
21 Mar 2021
Adaptive-Control-Oriented Meta-Learning for Nonlinear Systems
Adaptive-Control-Oriented Meta-Learning for Nonlinear Systems
Spencer M. Richards
Navid Azizan
Jean-Jacques E. Slotine
Marco Pavone
37
70
0
07 Mar 2021
Cycle Self-Training for Domain Adaptation
Cycle Self-Training for Domain Adaptation
Hong Liu
Jianmin Wang
Mingsheng Long
36
174
0
05 Mar 2021
Exploring Complementary Strengths of Invariant and Equivariant
  Representations for Few-Shot Learning
Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning
Mamshad Nayeem Rizve
Salman Khan
Fahad Shahbaz Khan
M. Shah
41
108
0
01 Mar 2021
Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution
Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution
Amrith Rajagopal Setlur
Oscar Li
Virginia Smith
35
13
0
23 Feb 2021
On Fast Adversarial Robustness Adaptation in Model-Agnostic
  Meta-Learning
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning
Ren Wang
Kaidi Xu
Sijia Liu
Pin-Yu Chen
Tsui-Wei Weng
Chuang Gan
Meng Wang
AAML
21
46
0
20 Feb 2021
Few-shot Conformal Prediction with Auxiliary Tasks
Few-shot Conformal Prediction with Auxiliary Tasks
Adam Fisch
Tal Schuster
Tommi Jaakkola
Regina Barzilay
184
53
0
17 Feb 2021
Few-Shot Graph Learning for Molecular Property Prediction
Few-Shot Graph Learning for Molecular Property Prediction
Zhichun Guo
Chuxu Zhang
W. Yu
John E. Herr
Olaf Wiest
Meng Jiang
Nitesh V. Chawla
AI4CE
119
170
0
16 Feb 2021
Investigating Bi-Level Optimization for Learning and Vision from a
  Unified Perspective: A Survey and Beyond
Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond
Risheng Liu
Jiaxin Gao
Jin Zhang
Deyu Meng
Zhouchen Lin
AI4CE
59
222
0
27 Jan 2021
Contrastive Prototype Learning with Augmented Embeddings for Few-Shot
  Learning
Contrastive Prototype Learning with Augmented Embeddings for Few-Shot Learning
Yizhao Gao
Nanyi Fei
Guangzhen Liu
Zhiwu Lu
Tao Xiang
Songfang Huang
61
35
0
23 Jan 2021
Shallow Bayesian Meta Learning for Real-World Few-Shot Recognition
Shallow Bayesian Meta Learning for Real-World Few-Shot Recognition
Xueting Zhang
Debin Meng
Henry Gouk
Timothy M. Hospedales
BDL
UQCV
30
68
0
08 Jan 2021
Learning Accurate Dense Correspondences and When to Trust Them
Learning Accurate Dense Correspondences and When to Trust Them
Prune Truong
Martin Danelljan
Luc Van Gool
Radu Timofte
3DH
3DPC
79
128
0
05 Jan 2021
Task-Adaptive Negative Envision for Few-Shot Open-Set Recognition
Task-Adaptive Negative Envision for Few-Shot Open-Set Recognition
Shiyuan Huang
Jiawei Ma
G. Han
Shih-Fu Chang
BDL
33
19
0
24 Dec 2020
On Episodes, Prototypical Networks, and Few-shot Learning
On Episodes, Prototypical Networks, and Few-shot Learning
Steinar Laenen
Luca Bertinetto
20
97
0
17 Dec 2020
Iterative label cleaning for transductive and semi-supervised few-shot
  learning
Iterative label cleaning for transductive and semi-supervised few-shot learning
Michalis Lazarou
Tania Stathaki
Yannis Avrithis
40
61
0
14 Dec 2020
Meta-Generating Deep Attentive Metric for Few-shot Classification
Meta-Generating Deep Attentive Metric for Few-shot Classification
Lei Zhang
Fei Zhou
Wei Wei
Yanning Zhang
VLM
42
28
0
03 Dec 2020
Mixture-based Feature Space Learning for Few-shot Image Classification
Mixture-based Feature Space Learning for Few-shot Image Classification
Arman Afrasiyabi
Jean-François Lalonde
Christian Gagné
VLM
18
70
0
24 Nov 2020
Hybrid Consistency Training with Prototype Adaptation for Few-Shot
  Learning
Hybrid Consistency Training with Prototype Adaptation for Few-Shot Learning
Meng Ye
Xiaoyu Lin
Giedrius Burachas
Ajay Divakaran
Yi Yao
17
2
0
19 Nov 2020
Dataset Meta-Learning from Kernel Ridge-Regression
Dataset Meta-Learning from Kernel Ridge-Regression
Timothy Nguyen
Zhourung Chen
Jaehoon Lee
DD
36
238
0
30 Oct 2020
Learning to Learn Variational Semantic Memory
Learning to Learn Variational Semantic Memory
Xiantong Zhen
Yingjun Du
Huan Xiong
Qiang Qiu
Cees G. M. Snoek
Ling Shao
SSL
BDL
VLM
DRL
15
34
0
20 Oct 2020
Bilevel Optimization: Convergence Analysis and Enhanced Design
Bilevel Optimization: Convergence Analysis and Enhanced Design
Kaiyi Ji
Junjie Yang
Yingbin Liang
28
245
0
15 Oct 2020
Few-shot Learning for Spatial Regression
Few-shot Learning for Spatial Regression
Tomoharu Iwata
Yusuke Tanaka
30
11
0
09 Oct 2020
Improving Few-Shot Learning through Multi-task Representation Learning
  Theory
Improving Few-Shot Learning through Multi-task Representation Learning Theory
Quentin Bouniot
I. Redko
Romaric Audigier
Angélique Loesch
Amaury Habrard
45
10
0
05 Oct 2020
Fast Few-Shot Classification by Few-Iteration Meta-Learning
Fast Few-Shot Classification by Few-Iteration Meta-Learning
A. S. Tripathi
Martin Danelljan
Luc Van Gool
Radu Timofte
31
6
0
01 Oct 2020
GOCor: Bringing Globally Optimized Correspondence Volumes into Your
  Neural Network
GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural Network
Prune Truong
Martin Danelljan
Luc Van Gool
Radu Timofte
24
76
0
16 Sep 2020
SML: Semantic Meta-learning for Few-shot Semantic Segmentation
SML: Semantic Meta-learning for Few-shot Semantic Segmentation
Ayyappa Kumar Pambala
Titir Dutta
Soma Biswas
24
22
0
14 Sep 2020
CrossTransformers: spatially-aware few-shot transfer
CrossTransformers: spatially-aware few-shot transfer
Carl Doersch
Ankush Gupta
Andrew Zisserman
ViT
215
330
0
22 Jul 2020
Adaptive Task Sampling for Meta-Learning
Adaptive Task Sampling for Meta-Learning
Chenghao Liu
Zhihao Wang
Doyen Sahoo
Yuan Fang
Kun Zhang
Guosheng Lin
25
54
0
17 Jul 2020
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