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Supervising Unsupervised Learning
v1v2 (latest)

Supervising Unsupervised Learning

14 September 2017
Vikas Garg
Adam Kalai
    SSLFedML
ArXiv (abs)PDFHTML

Papers citing "Supervising Unsupervised Learning"

14 / 14 papers shown
Title
From Latent to Engine Manifolds: Analyzing ImageBind's Multimodal
  Embedding Space
From Latent to Engine Manifolds: Analyzing ImageBind's Multimodal Embedding Space
Andrew Hamara
Pablo Rivas
179
1
0
30 Aug 2024
When to Use What: An In-Depth Comparative Empirical Analysis of OpenIE
  Systems for Downstream Applications
When to Use What: An In-Depth Comparative Empirical Analysis of OpenIE Systems for Downstream ApplicationsAnnual Meeting of the Association for Computational Linguistics (ACL), 2022
Kevin Pei
Ishan Jindal
Kevin Chen-Chuan Chang
Chengxiang Zhai
Yunyao Li
107
7
0
15 Nov 2022
Structural Analysis of Branch-and-Cut and the Learnability of Gomory
  Mixed Integer Cuts
Structural Analysis of Branch-and-Cut and the Learnability of Gomory Mixed Integer CutsNeural Information Processing Systems (NeurIPS), 2022
Maria-Florina Balcan
Siddharth Prasad
Tuomas Sandholm
Ellen Vitercik
118
25
0
15 Apr 2022
How to Train Your MAML to Excel in Few-Shot Classification
How to Train Your MAML to Excel in Few-Shot ClassificationInternational Conference on Learning Representations (ICLR), 2021
Han-Jia Ye
Wei-Lun Chao
194
57
0
30 Jun 2021
Generalization in portfolio-based algorithm selection
Generalization in portfolio-based algorithm selectionAAAI Conference on Artificial Intelligence (AAAI), 2020
Maria-Florina Balcan
Tuomas Sandholm
Ellen Vitercik
135
13
0
24 Dec 2020
Discovering and Interpreting Biased Concepts in Online Communities
Discovering and Interpreting Biased Concepts in Online CommunitiesIEEE Transactions on Knowledge and Data Engineering (TKDE), 2020
Xavier Ferrer-Aran
Tom van Nuenen
Natalia Criado
Jose Such
179
3
0
27 Oct 2020
LiDAM: Semi-Supervised Learning with Localized Domain Adaptation and
  Iterative Matching
LiDAM: Semi-Supervised Learning with Localized Domain Adaptation and Iterative Matching
Qun Liu
Matthew Shreve
R. Bala
153
0
0
13 Oct 2020
A Comprehensive Overview and Survey of Recent Advances in Meta-Learning
A Comprehensive Overview and Survey of Recent Advances in Meta-Learning
Huimin Peng
VLMOffRL
363
39
0
17 Apr 2020
Meta-Learning in Neural Networks: A Survey
Meta-Learning in Neural Networks: A SurveyIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
Timothy M. Hospedales
Antreas Antoniou
P. Micaelli
Amos Storkey
OOD
677
2,352
0
11 Apr 2020
Revisiting Meta-Learning as Supervised Learning
Revisiting Meta-Learning as Supervised Learning
Wei-Lun Chao
Han-Jia Ye
De-Chuan Zhan
M. Campbell
Kilian Q. Weinberger
OODFedML
150
24
0
03 Feb 2020
Meta-Learning to Cluster
Meta-Learning to Cluster
Yibo Jiang
Nakul Verma
FedML
106
7
0
30 Oct 2019
Private Selection from Private Candidates
Private Selection from Private CandidatesSymposium on the Theory of Computing (STOC), 2018
Jingcheng Liu
Kunal Talwar
179
145
0
19 Nov 2018
Unsupervised Learning via Meta-Learning
Unsupervised Learning via Meta-Learning
Kyle Hsu
Sergey Levine
Chelsea Finn
SSLOffRL
381
244
0
04 Oct 2018
Meta-Learning Update Rules for Unsupervised Representation Learning
Meta-Learning Update Rules for Unsupervised Representation Learning
Luke Metz
Niru Maheswaranathan
Brian Cheung
Jascha Narain Sohl-Dickstein
SSLOOD
237
127
0
31 Mar 2018
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