Amir Globerson
Cited by
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Metric learning by collapsing classes
A Globerson, S Roweis
Advances in neural information processing systems 18, 451-458, 2005
Fixing max-product: Convergent message passing algorithms for MAP LP-relaxations
A Globerson, T Jaakkola
Advances in neural information processing systems 20, 553-560, 2007
Nightmare at test time: robust learning by feature deletion
A Globerson, S Roweis
Proceedings of the 23rd international conference on Machine learning, 353-360, 2006
Tightening LP relaxations for MAP using message passing
D Sontag, T Meltzer, A Globerson, TS Jaakkola, Y Weiss
arXiv preprint arXiv:1206.3288, 2012
Euclidean embedding of co-occurrence data
A Globerson, G Chechik, F Pereira, N Tishby
Globally optimal gradient descent for a convnet with gaussian inputs
A Brutzkus, A Globerson
International conference on machine learning, 605-614, 2017
Learning Bayesian network structure using LP relaxations
T Jaakkola, D Sontag, A Globerson, M Meila
Proceedings of the Thirteenth International Conference on Artificial …, 2010
Information Bottleneck for Gaussian Variables.
G Chechik, A Globerson, N Tishby, Y Weiss, P Dayan
Journal of machine learning research 6 (1), 2005
Introduction to dual composition for inference
D Sontag, A Globerson, T Jaakkola
Optimization for Machine Learning, 2011
Exponentiated gradient algorithms for conditional random fields and max-margin markov networks
M Collins, A Globerson, T Koo, X Carreras Pérez, P Bartlett
Journal of Machine Learning Research 9, 1775-1822, 2008
SGD learns over-parameterized networks that provably generalize on linearly separable data
A Brutzkus, A Globerson, E Malach, S Shalev-Shwartz
arXiv preprint arXiv:1710.10174, 2017
Selective sharing for multilingual dependency parsing
T Naseem, R Barzilay, A Globerson
The Association for Computational Linguistics, 2012
Structured prediction models via the matrix-tree theorem
T Koo, A Globerson, X Carreras Pérez, M Collins
Joint Conference on Empirical Methods in Natural Language Processing and …, 2007
Convergent message passing algorithms-a unifying view
T Meltzer, A Globerson, Y Weiss
arXiv preprint arXiv:1205.2625, 2012
Sufficient dimensionality reduction
A Globerson, N Tishby
Journal of Machine Learning Research 3 (Mar), 1307-1331, 2003
Convex learning with invariances
CH Teo, A Globerson, ST Roweis, AJ Smola
Advances in neural information processing systems, 1489-1496, 2008
Cross-lingual alignment of contextual word embeddings, with applications to zero-shot dependency parsing
T Schuster, O Ram, R Barzilay, A Globerson
arXiv preprint arXiv:1902.09492, 2019
Collective entity resolution with multi-focal attention
A Globerson, N Lazic, S Chakrabarti, A Subramanya, M Ringaard, ...
Learning efficiently with approximate inference via dual losses
O Meshi, D Sontag, T Jaakkola, A Globerson
International Machine Learning Society, 2010
An LP View of the M-best MAP problem
M Fromer, A Globerson
Advances in Neural Information Processing Systems 22, 567-575, 2009
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