Amir Globerson

According to our database1, Amir Globerson authored at least 79 papers between 2001 and 2019.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

Homepages:

On csauthors.net:

Bibliography

2019
Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot 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 Non-experts.
Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

Learning Rules-First Classifiers.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Mapping Images to Scene Graphs with Permutation-Invariant 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 Over-parameterized Networks that Provably Generalize on Linearly Separable Data.
Proceedings of the 6th International Conference on Learning Representations, 2018

Semi-Supervised 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 Thirty-Third 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 Multi-Focal 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 Max-Margin 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 k-Locality.
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 Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Learning Max-Margin Tree Predictors.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

The Pairwise Piecewise-Linear Embedding for Efficient Non-Linear 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 Constituency-Based 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 3-6, 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 Inter-Sentence 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 8-14, 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 pseudo-max 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 6-9 December 2010, 2010

Learning Efficiently with Approximate Inference via Dual Losses.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

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 M-best 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 7-10 December 2009, 2009

2008
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks.
Journal of Machine Learning Research, 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

Euclidean Embedding of Co-occurrence Data.
Journal of Machine Learning Research, 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 Max-Product: Convergent Message Passing Algorithms for MAP LP-Relaxations.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Exponentiated gradient algorithms for log-linear structured prediction.
Proceedings of the Machine Learning, 2007

Structured Prediction Models via the Matrix-Tree Theorem.
Proceedings of the EMNLP-CoNLL 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
Information Bottleneck for Gaussian Variables.
Journal of Machine Learning Research, 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 Co-occurrences.
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 Co-Occurrence Data.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2003
Sufficient Dimensionality Reduction.
Journal of Machine Learning Research, 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


  Loading...