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An Information-Geometric Distance on the Space of Tasks
v1v2 (latest)

An Information-Geometric Distance on the Space of Tasks

International Conference on Machine Learning (ICML), 2020
1 November 2020
Yansong Gao
Pratik Chaudhari
ArXiv (abs)PDFHTMLGithub

Papers citing "An Information-Geometric Distance on the Space of Tasks"

15 / 15 papers shown
Features are fate: a theory of transfer learning in high-dimensional regression
Features are fate: a theory of transfer learning in high-dimensional regression
Javan Tahir
Surya Ganguli
Grant M. Rotskoff
539
7
0
10 Oct 2024
CLAMS: A System for Zero-Shot Model Selection for Clustering
CLAMS: A System for Zero-Shot Model Selection for Clustering
Prabhant Singh
Pieter Gijsbers
Murat Onur Yildirim
Elif Ceren Gok
Joaquin Vanschoren
309
0
0
15 Jul 2024
Back to the Basics on Predicting Transfer Performance
Back to the Basics on Predicting Transfer Performance
Levy G. Chaves
Eduardo Valle
Alceu Bissoto
Sandra Avila
MedIm
271
0
0
30 May 2024
Adapting Machine Learning Diagnostic Models to New Populations Using a
  Small Amount of Data: Results from Clinical Neuroscience
Adapting Machine Learning Diagnostic Models to New Populations Using a Small Amount of Data: Results from Clinical Neuroscience
Rongguang Wang
G. Erus
Pratik Chaudhari
Christos Davatzikos
OOD
290
7
0
06 Aug 2023
Fisher-Rao distance and pullback SPD cone distances between multivariate
  normal distributions
Fisher-Rao distance and pullback SPD cone distances between multivariate normal distributions
Frank Nielsen
251
1
0
20 Jul 2023
Generating Synthetic Datasets by Interpolating along Generalized
  Geodesics
Generating Synthetic Datasets by Interpolating along Generalized GeodesicsConference on Uncertainty in Artificial Intelligence (UAI), 2023
JiaoJiao Fan
David Alvarez-Melis
258
11
0
12 Jun 2023
Interpolation for Robust Learning: Data Augmentation on Wasserstein
  Geodesics
Interpolation for Robust Learning: Data Augmentation on Wasserstein GeodesicsInternational Conference on Machine Learning (ICML), 2023
Jiacheng Zhu
Jielin Qiu
Aritra Guha
Zhuolin Yang
X. Nguyen
Yue Liu
Ding Zhao
OOD
671
4
0
04 Feb 2023
Meta-Learning for Unsupervised Outlier Detection with Optimal Transport
Meta-Learning for Unsupervised Outlier Detection with Optimal TransportInternational Joint Conference on Artificial Intelligence (IJCAI), 2022
Prabhant Singh
Joaquin Vanschoren
OOD
318
9
0
01 Nov 2022
A picture of the space of typical learnable tasks
A picture of the space of typical learnable tasksInternational Conference on Machine Learning (ICML), 2022
Rahul Ramesh
Jialin Mao
Itay Griniasty
Rubing Yang
H. Teoh
Mark K. Transtrum
James P. Sethna
Pratik Chaudhari
SSLDRL
487
7
0
31 Oct 2022
Time-Varying Propensity Score to Bridge the Gap between the Past and
  Present
Time-Varying Propensity Score to Bridge the Gap between the Past and PresentInternational Conference on Learning Representations (ICLR), 2022
Rasool Fakoor
Jonas W. Mueller
Zachary Chase Lipton
Pratik Chaudhari
Alexander J. Smola
OODAI4TS
581
4
0
04 Oct 2022
Wasserstein Task Embedding for Measuring Task Similarities
Wasserstein Task Embedding for Measuring Task SimilaritiesNeural Networks (NN), 2022
Hengrong Du
Yikun Bai
Yuzhe Lu
Andrea Soltoggio
Soheil Kolouri
OT
233
43
0
24 Aug 2022
Hierarchical Optimal Transport for Comparing Histopathology Datasets
Hierarchical Optimal Transport for Comparing Histopathology DatasetsInternational Conference on Medical Imaging with Deep Learning (MIDL), 2022
A. Yeaton
Rahul G. Krishnan
Rebecca J. Mieloszyk
David Alvarez-Melis
G. Huynh
OT
225
10
0
18 Apr 2022
Probing transfer learning with a model of synthetic correlated datasets
Probing transfer learning with a model of synthetic correlated datasets
Federica Gerace
Luca Saglietti
Stefano Sarao Mannelli
Andrew M. Saxe
Lenka Zdeborová
OOD
297
41
0
09 Jun 2021
Inducing a hierarchy for multi-class classification problems
Inducing a hierarchy for multi-class classification problems
Hayden S. Helm
Weiwei Yang
Sujeeth Bharadwaj
Kate Lytvynets
Oriana Riva
Christopher M. White
Ali Geisa
Carey E. Priebe
205
7
0
20 Feb 2021
A Free-Energy Principle for Representation Learning
A Free-Energy Principle for Representation LearningInternational Conference on Machine Learning (ICML), 2020
Yansong Gao
Pratik Chaudhari
DRL
241
11
0
27 Feb 2020
1
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