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Exponential Family Graph Matching and Ranking
v1v2 (latest)

Exponential Family Graph Matching and Ranking

Neural Information Processing Systems (NeurIPS), 2009
17 April 2009
James Petterson
T. Caetano
Julian McAuley
Jin Yu
ArXiv (abs)PDFHTML

Papers citing "Exponential Family Graph Matching and Ranking"

13 / 13 papers shown
M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning
  of Mixture Graph Matching and Clustering
M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning of Mixture Graph Matching and ClusteringInternational Conference on Learning Representations (ICLR), 2023
Jiaxin Lu
Zetian Jiang
Tianzhe Wang
Junchi Yan
309
3
0
27 Oct 2023
On the Consistency of Max-Margin Losses
On the Consistency of Max-Margin LossesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Alex W. Nowak
Alessandro Rudi
Francis R. Bach
199
5
0
31 May 2021
Consistent Structured Prediction with Max-Min Margin Markov Networks
Consistent Structured Prediction with Max-Min Margin Markov Networks
Alex Nowak-Vila
Francis R. Bach
Alessandro Rudi
319
16
0
02 Jul 2020
Structured Prediction with Projection Oracles
Structured Prediction with Projection OraclesNeural Information Processing Systems (NeurIPS), 2019
Mathieu Blondel
435
36
0
24 Oct 2019
Solving Partial Assignment Problems using Random Clique Complexes
Solving Partial Assignment Problems using Random Clique ComplexesInternational Conference on Machine Learning (ICML), 2019
Charu Sharma
Deepak Nathani
Manohar Kaul
176
2
0
03 Jul 2019
A General Theory for Structured Prediction with Smooth Convex Surrogates
A General Theory for Structured Prediction with Smooth Convex Surrogates
Alex Nowak-Vila
Francis R. Bach
Alessandro Rudi
362
24
0
05 Feb 2019
Unsupervised Object Matching for Relational Data
Unsupervised Object Matching for Relational Data
Tomoharu Iwata
N. Ueda
239
2
0
09 Oct 2018
Learning Latent Permutations with Gumbel-Sinkhorn Networks
Learning Latent Permutations with Gumbel-Sinkhorn Networks
Gonzalo E. Mena
David Belanger
Scott W. Linderman
Jasper Snoek
357
319
0
23 Feb 2018
Initialization and Coordinate Optimization for Multi-way Matching
Initialization and Coordinate Optimization for Multi-way Matching
Da Tang
Tony Jebara
303
9
0
02 Nov 2016
Bethe Learning of Conditional Random Fields via MAP Decoding
Bethe Learning of Conditional Random Fields via MAP Decoding
K. Tang
Nicholas Ruozzi
David Belanger
Tony Jebara
TPM
389
5
0
04 Mar 2015
A Framework for Optimizing Paper Matching
A Framework for Optimizing Paper MatchingConference on Uncertainty in Artificial Intelligence (UAI), 2011
Laurent Charlin
R. Zemel
Craig Boutilier
231
67
0
14 Feb 2012
Loss-sensitive Training of Probabilistic Conditional Random Fields
Loss-sensitive Training of Probabilistic Conditional Random Fields
Anthony L. Caterini
Hugo Larochelle
R. Zemel
193
14
0
09 Jul 2011
Uncovering the Riffled Independence Structure of Rankings
Uncovering the Riffled Independence Structure of Rankings
Jonathan Huang
Carlos Guestrin
221
4
0
07 Jun 2010
1
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