Amir Globerson
TitleCited byYear
Metric learning by collapsing classes
A Globerson, ST Roweis
Advances in neural information processing systems, 451-458, 2006
Fixing max-product: Convergent message passing algorithms for MAP LP-relaxations
A Globerson, TS Jaakkola
Advances in neural information processing systems, 553-560, 2008
Tightening LP relaxations for MAP using message passing
D Sontag, T Meltzer, A Globerson, TS Jaakkola, Y Weiss
arXiv preprint arXiv:1206.3288, 2012
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
Euclidean embedding of co-occurrence data
A Globerson, G Chechik, F Pereira, N Tishby
Journal of Machine Learning Research 8 (Oct), 2265-2295, 2007
Introduction to dual composition for inference
D Sontag, A Globerson, T Jaakkola
Optimization for Machine Learning, 2011
Learning Bayesian network structure using LP relaxations
T Jaakkola, D Sontag, A Globerson, M Meila
Proceedings of the Thirteenth International Conference on Artificial …, 2010
Exponentiated gradient algorithms for conditional random fields and max-margin markov networks
M Collins, A Globerson, T Koo, X Carreras, PL Bartlett
Journal of Machine Learning Research 9 (Aug), 1775-1822, 2008
Information bottleneck for Gaussian variables
G Chechik, A Globerson, N Tishby, Y Weiss
Journal of machine learning research 6 (Jan), 165-188, 2005
Globally optimal gradient descent for a convnet with gaussian inputs
A Brutzkus, A Globerson
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
Sufficient dimensionality reduction
A Globerson, N Tishby
Journal of Machine Learning Research 3 (Mar), 1307-1331, 2003
Convergent message passing algorithms: a unifying view
T Meltzer, A Globerson, Y Weiss
Proceedings of the twenty-fifth conference on uncertainty in artificial …, 2009
Convex learning with invariances
CH Teo, A Globerson, ST Roweis, AJ Smola
Advances in neural information processing systems, 1489-1496, 2008
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
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
Proceedings of the 50th Annual Meeting of the Association for Computational …, 2012
An LP View of the M-best MAP problem
M Fromer, A Globerson
Advances in Neural Information Processing Systems, 567-575, 2009
Learning efficiently with approximate inference via dual losses
O Meshi, D Sontag, T Jaakkola, A Globerson
International Machine Learning Society, 2010
An alternating direction method for dual MAP LP relaxation
O Meshi, A Globerson
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011
Approximate inference using planar graph decomposition
A Globerson, TS Jaakkola
Advances in Neural Information Processing Systems, 473-480, 2007
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