Amir Globerson
According to our database^{1},
Amir Globerson
authored at least 79 papers
between 2001 and 2019.
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Bibliography
2019
CrossLingual Alignment of Contextual Word Embeddings, with Applications to Zeroshot Dependency Parsing.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019
Why do Larger Models Generalize Better? A Theoretical Perspective via the XOR Problem.
Proceedings of the 36th International Conference on Machine Learning, 2019
Explaining Queries Over Web Tables to Nonexperts.
Proceedings of the 35th IEEE International Conference on Data Engineering, 2019
Learning RulesFirst Classifiers.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
Coreference Resolution with Entity Equalization.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019
2018
Mapping Images to Scene Graphs with PermutationInvariant Structured Prediction.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Learning to Optimize Combinatorial Functions.
Proceedings of the 35th International Conference on Machine Learning, 2018
Predict and Constrain: Modeling Cardinality in Deep Structured Prediction.
Proceedings of the 35th International Conference on Machine Learning, 2018
SGD Learns Overparameterized Networks that Provably Generalize on Linearly Separable Data.
Proceedings of the 6th International Conference on Learning Representations, 2018
SemiSupervised Learning with Competitive Infection Models.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
Weakly Supervised Semantic Parsing with Abstract Examples.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018
2017
Learning and Inference with Expectations.
Proceedings of the ThirtyThird Conference on Uncertainty in Artificial Intelligence, 2017
Robust Conditional Probabilities.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Learning Infinite Layer Networks Without the Kernel Trick.
Proceedings of the 34th International Conference on Machine Learning, 2017
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs.
Proceedings of the 34th International Conference on Machine Learning, 2017
Effective Semisupervised Learning on Manifolds.
Proceedings of the 30th Conference on Learning Theory, 2017
2016
Discriminative Learning of Infection Models.
Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 2016
Optimal Tagging with Markov Chain Optimization.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Improper Deep Kernels.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016
Collective Entity Resolution with MultiFocal Attention.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016
2015
Erratum: "Exploring Compositional Architectures and Word Vector Representations for Prepositional Phrase Attachment".
TACL, 2015
Template Kernels for Dependency Parsing.
Proceedings of the NAACL HLT 2015, The 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, USA, May 31, 2015
How Hard is Inference for Structured Prediction?
Proceedings of the 32nd International Conference on Machine Learning, 2015
2014
Exploring Compositional Architectures and Word Vector Representations for Prepositional Phrase Attachment.
TACL, 2014
Tightness Results for Local Consistency Relaxations in Continuous MRFs.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014
Lifted Message Passing as Reparametrization of Graphical Models.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014
Spectral Regularization for MaxMargin Sequence Tagging.
Proceedings of the 31th International Conference on Machine Learning, 2014
Inferning with High Girth Graphical Models.
Proceedings of the 31th International Conference on Machine Learning, 2014
Discrete Chebyshev Classifiers.
Proceedings of the 31th International Conference on Machine Learning, 2014
Learning Structured Models with the AUC Loss and Its Generalizations.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014
Efficient Lifting of MAP LP Relaxations Using kLocality.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014
Steps to Excellence: Simple Inference with Refined Scoring of Dependency Trees.
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics, 2014
2013
Time Varying Autoregressive Moving Average Models for Covariance Estimation.
IEEE Trans. Signal Processing, 2013
Tighter Linear Program Relaxations for High Order Graphical Models.
Proceedings of the TwentyNinth Conference on Uncertainty in Artificial Intelligence, 2013
Learning MaxMargin Tree Predictors.
Proceedings of the TwentyNinth Conference on Uncertainty in Artificial Intelligence, 2013
The Pairwise PiecewiseLinear Embedding for Efficient NonLinear Classification.
Proceedings of the 30th International Conference on Machine Learning, 2013
Vanishing Component Analysis.
Proceedings of the 30th International Conference on Machine Learning, 2013
Higher Order Matching for Consistent Multiple Target Tracking.
Proceedings of the IEEE International Conference on Computer Vision, 2013
Transfer Learning for ConstituencyBased Grammars.
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, 2013
2012
A Simple Geometric Interpretation of SVM using Stochastic Adversaries.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012
Convergence Rate Analysis of MAP Coordinate Minimization Algorithms.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 36, 2012
Covariance estimation in time varying ARMA processes.
Proceedings of the IEEE 7th Sensor Array and Multichannel Signal Processing Workshop, 2012
Learning the Experts for Online Sequence Prediction.
Proceedings of the 29th International Conference on Machine Learning, 2012
Learning to Map into a Universal POS Tagset.
Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, 2012
Improved Parsing and POS Tagging Using InterSentence Consistency Constraints.
Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, 2012
Selective Sharing for Multilingual Dependency Parsing.
Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference, July 814, 2012, Jeju Island, Korea, 2012
2011
What Cannot be Learned with Bethe Approximations.
Proceedings of the UAI 2011, 2011
An Alternating Direction Method for Dual MAP LP Relaxation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011
2010
Learning Bayesian Network Structure using LP Relaxations.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010
More data means less inference: A pseudomax approach to structured learning.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 69 December 2010, 2010
Learning Efficiently with Approximate Inference via Dual Losses.
Proceedings of the 27th International Conference on Machine Learning (ICML10), 2010
2009
The minimum information principle and its application to neural code analysis.
Proc. Natl. Acad. Sci. U.S.A., 2009
Convexifying the Bethe Free Energy.
Proceedings of the UAI 2009, 2009
Convergent message passing algorithms  a unifying view.
Proceedings of the UAI 2009, 2009
An LP View of the Mbest MAP problem.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 710 December 2009, 2009
2008
Exponentiated Gradient Algorithms for Conditional Random Fields and MaxMargin Markov Networks.
J. Mach. Learn. Res., 2008
Tightening LP Relaxations for MAP using Message Passing.
Proceedings of the UAI 2008, 2008
Clusters and Coarse Partitions in LP Relaxations.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
2007
Visualizing pairwise similarity via semidefinite programming.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007
Approximate inference using conditional entropy decompositions.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007
Convergent Propagation Algorithms via Oriented Trees.
Proceedings of the UAI 2007, 2007
Convex Learning with Invariances.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007
Fixing MaxProduct: Convergent Message Passing Algorithms for MAP LPRelaxations.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007
Exponentiated gradient algorithms for loglinear structured prediction.
Proceedings of the Machine Learning, 2007
Structured Prediction Models via the MatrixTree Theorem.
Proceedings of the EMNLPCoNLL 2007, 2007
2006
Discriminative Learning via Semidefinite Probabilistic Models.
Proceedings of the UAI '06, 2006
Approximate inference using planar graph decomposition.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006
Nightmare at test time: robust learning by feature deletion.
Proceedings of the Machine Learning, 2006
Embedding Heterogeneous Data Using Statistical Models.
Proceedings of the Proceedings, 2006
2005
Metric Learning by Collapsing Classes.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005
Distributed Latent Variable Models of Lexical Cooccurrences.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005
2004
The Minimum Information Principle for Discriminative Learning.
Proceedings of the UAI '04, 2004
Euclidean Embedding of CoOccurrence Data.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004
2003
Sufficient Dimensionality Reduction.
J. Mach. Learn. Res., 2003
Sufficient Dimensionality Reduction with Irrelevance Statistics.
Proceedings of the UAI '03, 2003
Information Bottleneck for Gaussian Variables.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003
2002
Sufficient Dimensionality Reduction  A novel Analysis Method.
Proceedings of the Machine Learning, 2002
Most Informative Dimension Reduction.
Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002
2001
Group Redundancy Measures Reveal Redundancy Reduction in the Auditory Pathway.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001