PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

EPrints submitted by Amir Globerson

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Number of EPrints submitted by this user: 21

Clusters and Coarse Partitions in LP Relaxations
David Sontag, Amir Globerson and Tommi Jaakkola
Advances in Nerual Information Processing Systems Volume 22, 2009.

Convexifying the Bethe Free Energy
Ofer Meshi, Ariel Jaimovich, Amir Globerson and Nir Friedman
Proceedings of Uncertainty in Artificial Intelligence (UAI) 2009.

Convergent message passing algorithms - a unifying view
Talya Meltzer, Amir Globerson and Yair Weiss
Proceedings of Uncertainty in Artificial Intelligence (UAI) 2009.

The Minimum Information Principle and its Application to Neural Code Analysis
Amir Globerson, Eran Stark, Eilon Vaadia and Naftali Tishby
Proceedings of the National Academy of Sciences Volume 106, Number 9, pp. 3490-3495, 2009.

Past-future information bottleneck in dynamical systems
Felix Creutzig, Amir Globerson and Naftali Tishby
Physical Review E Volume 79, Number 4, 2009.

An LP View of the M-best MAP problem
Menachem Fromer and Amir Globerson
Advances in Neural Information Processing Systems 22 pp. 567-575, 2009.

Incorporating Expressive Graphical Models in Variational Approximations: Chain-Graphs and Hidden Variables
Tal El-Hay and Nir Friedman
In: UAI 2001, Seatle(2001).

Continuous Time Markov Networks
Tal El-Hay, Nir Friedman, Daphne Koller and Raz Kupferman
In: UAI 2006, Cambridge, MA(2006).

Gibbs Sampling in Factorized Continuous-Time Markov Processes
Tal El-Hay, Nir Friedman and Raz Kupferman
In: UAI 2008, Helsinki(2008).

Mean Field Variational Approximation for Continuous-Time Bayesian Networks
Ido Cohn, Tal El-Hay, Nir Friedman and Raz Kupferman
In: UAI 2009, Montreal(2009).

More data means less inference: A pseudo-max approach to structured learning
Ofer Meshi, David Sontag, Tommi Jaakkola and Amir Globerson
In: Advances in Neural Information Processing Systems (NIPS) 23, Vancouver, Canada(2010).

Learning Efficiently with Approximate Inference via Dual Losses
Ofer Meshi, David Sontag, Tommi Jaakkola and Amir Globerson
In: International Conference on Machine Learning (ICML), Haifa, Israel(2010).

Learning Bayesian Network Structure using LP Relaxations
Tommi Jaakkola, David Sontag, Amir Globerson and Marina Meila
In: The International Workshop on Artificial Intelligence and Statistics (AISTATS), Sardinia, Italy(2010).

Introduction to Dual Decomposition for Inference
David Sontag, Amir Globerson and Tommi Jaakkola
In: Optimization for Machine Learning (2010) MIT Press .

Spectral Clustering on a Budget
Ohad Shamir and Naftali Tishby
Fourteenth International Conference on Artificial Intelligence and Statistics 2011.

What's in a Hashtag? Content based Prediction of the Spread of Ideas in Microblogging Communities
Oren Tsur and Ari Rappoport
Proceedings of the fifth ACM international conference on Web search and data mining (WSDM) 2012.

Trading value and information in MDPs
Jonathan Rubin, Ohad Shamir and Naftali Tishby
In: Decision Making with Imperfect Decision Makers (2011) Springer .

A Simple Geometric Interpretation of SVM using Stochastic Adversaries
Roi Livni and Amir Globerson
In: AISTATS 2012(2013).

Selective Sharing for Multilingual Dependency Parsing
Tahira Naseem, Regina Barzilay and Amir Globerson
In: ACL 2012(2012).

Learning to Map into a Universal POS Tagset
Yuan Zhang, Roi Reichart, Regina Barzilay and Amir Globerson
In: EMNLP 2012(2012).

The Pairwise Piecewise-Linear Embedding for Efficient Non-Linear Classification
Ofir Pele, Ben Taskar, Amir Globerson and Michael Werman
In: ICML 2013(2012).