Ofer Meshi

According to our database, Ofer Meshi authored at least 31 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Minimizing Live Experiments in Recommender Systems: User Simulation to Evaluate Preference Elicitation Policies.

Chih-Wei Hsu, Martin Mladenov, Ofer Meshi, James Pine, Hubert Pham, Shane Li, Xujian Liang, Anton Polishko, Li Yang, Ben Scheetz, Craig Boutilier

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Model-Free Preference Elicitation.

Carlos Martin, Craig Boutilier, Ofer Meshi, Tuomas Sandholm

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

2023

Density-based User Representation through Gaussian Process Regression for Multi-interest Personalized Retrieval.

Haolun Wu, Ofer Meshi, Masrour Zoghi, Fernando Diaz, Xue Liu, Craig Boutilier, Maryam Karimzadehgan

CoRR, 2023

Overcoming Prior Misspecification in Online Learning to Rank.

Javad Azizi, Ofer Meshi, Masrour Zoghi, Maryam Karimzadehgan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

On the Value of Prior in Online Learning to Rank.

Branislav Kveton, Ofer Meshi, Masrour Zoghi, Zhen Qin

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2019

Train and Test Tightness of LP Relaxations in Structured Prediction.

Ofer Meshi, Ben London, Adrian Weller, David A. Sontag

J. Mach. Learn. Res., 2019

Empirical Bayes Regret Minimization.

Chih-Wei Hsu, Branislav Kveton, Ofer Meshi, Martin Mladenov, Csaba Szepesvári

CoRR, 2019

Advantage Amplification in Slowly Evolving Latent-State Environments.

Martin Mladenov, Ofer Meshi, Jayden Ooi, Dale Schuurmans, Craig Boutilier

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

Seq2Slate: Re-ranking and Slate Optimization with RNNs.

Irwan Bello, Sayali Kulkarni, Sagar Jain, Craig Boutilier, Ed Huai-hsin Chi, Elad Eban, Xiyang Luo, Alan Mackey, Ofer Meshi

CoRR, 2018

Planning and Learning with Stochastic Action Sets.

Craig Boutilier, Alon Cohen, Amit Daniely, Avinatan Hassidim, Yishay Mansour, Ofer Meshi, Martin Mladenov, Dale Schuurmans

CoRR, 2018

Deep Structured Prediction with Nonlinear Output Transformations.

Colin Graber, Ofer Meshi, Alexander G. Schwing

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Planning and Learning with Stochastic Action Sets.

Craig Boutilier, Alon Cohen, Avinatan Hassidim, Yishay Mansour, Ofer Meshi, Martin Mladenov, Dale Schuurmans

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017

Asynchronous Parallel Coordinate Minimization for MAP Inference.

Ofer Meshi, Alexander G. Schwing

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Logistic Markov Decision Processes.

Martin Mladenov, Craig Boutilier, Dale Schuurmans, Ofer Meshi, Gal Elidan, Tyler Lu

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

2016

Linear-Memory and Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes.

Dan Garber, Ofer Meshi

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Train and Test Tightness of LP Relaxations in Structured Prediction.

Ofer Meshi, Mehrdad Mahdavi, Adrian Weller, David A. Sontag

Proceedings of the 33nd International Conference on Machine Learning, 2016

Fast and Scalable Structural SVM with Slack Rescaling.

Heejin Choi, Ofer Meshi, Nathan Srebro

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

On the Tightness of LP Relaxations for Structured Prediction.

Ofer Meshi, Mehrdad Mahdavi, David A. Sontag

CoRR, 2015

Smooth and Strong: MAP Inference with Linear Convergence.

Ofer Meshi, Mehrdad Mahdavi, Alexander G. Schwing

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Efficient Training of Structured SVMs via Soft Constraints.

Ofer Meshi, Nathan Srebro, Tamir Hazan

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Learning Structured Models with the AUC Loss and Its Generalizations.

Nir Rosenfeld, Ofer Meshi, Daniel Tarlow, Amir Globerson

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013

Efficient methods for learning and inference in structured output prediction (עם תקציר בעברית ושער נוסף: שיטות יעילות ללמידה והסקה בבעיות חיזוי מובנה.).

Ofer Meshi

PhD thesis, 2013

Learning Max-Margin Tree Predictors.

Ofer Meshi, Elad Eban, Gal Elidan, Amir Globerson

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

2012

Convergence Rate Analysis of MAP Coordinate Minimization Algorithms.

Ofer Meshi, Tommi S. Jaakkola, Amir Globerson

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

2011

An Alternating Direction Method for Dual MAP LP Relaxation.

Ofer Meshi, Amir Globerson

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

2010

FastInf: An Efficient Approximate Inference Library.

Ariel Jaimovich, Ofer Meshi, Ian McGraw, Gal Elidan

J. Mach. Learn. Res., 2010

More data means less inference: A pseudo-max approach to structured learning.

David A. Sontag, Ofer Meshi, Tommi S. Jaakkola, Amir Globerson

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.

Ofer Meshi, David A. Sontag, Tommi S. Jaakkola, Amir Globerson

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

2009

Convexifying the Bethe Free Energy.

Ofer Meshi, Ariel Jaimovich, Amir Globerson, Nir Friedman

Proceedings of the UAI 2009, 2009

2007

Evolutionary conservation and over-representation of functionally enriched network patterns in the yeast regulatory network.

Ofer Meshi, Tomer Shlomi, Eytan Ruppin

BMC Syst. Biol., 2007

Template Based Inference in Symmetric Relational Markov Random Fields.

Ariel Jaimovich, Ofer Meshi, Nir Friedman

Proceedings of the UAI 2007, 2007