Meshi, Ofer

26 publications

NeurIPS 2024 Density-Based User Representation Using Gaussian Process Regression for Multi-Interest Personalized Retrieval Haolun Wu, Ofer Meshi, Masrour Zoghi, Fernando Diaz, Xue Liu, Craig Boutilier, Maryam Karimzadehgan

IJCAI 2024 Model-Free Preference Elicitation Carlos Martin, Craig Boutilier, Ofer Meshi, Tuomas Sandholm

NeurIPSW 2023 Model-Free Preference Elicitation Carlos Martin, Craig Boutilier, Ofer Meshi

AISTATS 2023 Overcoming Prior Misspecification in Online Learning to Rank Javad Azizi, Ofer Meshi, Masrour Zoghi, Maryam Karimzadehgan

ICMLW 2023 Preference Elicitation for Music Recommendations Ofer Meshi, Jon Feldman, Li Yang, Ben Scheetz, Yanli Cai, Mohammadhossein Bateni, Corbyn Salisbury, Vikram Aggarwal, Craig Boutilier

AISTATS 2022 On the Value of Prior in Online Learning to Rank Branislav Kveton, Ofer Meshi, Masrour Zoghi, Zhen Qin

IJCAI 2019 Advantage Amplification in Slowly Evolving Latent-State Environments Martin Mladenov, Ofer Meshi, Jayden Ooi, Dale Schuurmans, Craig Boutilier

JMLR 2019 Train and Test Tightness of LP Relaxations in Structured Prediction Ofer Meshi, Ben London, Adrian Weller, David Sontag

NeurIPS 2018 Deep Structured Prediction with Nonlinear Output Transformations Colin Graber, Ofer Meshi, Alexander Schwing

IJCAI 2018 Planning and Learning with Stochastic Action Sets Craig Boutilier, Alon Cohen, Avinatan Hassidim, Yishay Mansour, Ofer Meshi, Martin Mladenov, Dale Schuurmans

NeurIPS 2017 Asynchronous Parallel Coordinate Minimization for MAP Inference Ofer Meshi, Alexander Schwing

IJCAI 2017 Logistic Markov Decision Processes Martin Mladenov, Craig Boutilier, Dale Schuurmans, Ofer Meshi, Gal Elidan, Tyler Lu

AISTATS 2016 Fast and Scalable Structural SVM with Slack Rescaling Heejin Choi, Ofer Meshi, Nathan Srebro

NeurIPS 2016 Linear-Memory and Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes Dan Garber, Dan Garber, Ofer Meshi

ICML 2016 Train and Test Tightness of LP Relaxations in Structured Prediction Ofer Meshi, Mehrdad Mahdavi, Adrian Weller, David Sontag

AISTATS 2015 Efficient Training of Structured SVMs via Soft Constraints Ofer Meshi, Nathan Srebro, Tamir Hazan

NeurIPS 2015 Smooth and Strong: MAP Inference with Linear Convergence Ofer Meshi, Mehrdad Mahdavi, Alex Schwing

AISTATS 2014 Learning Structured Models with the AUC Loss and Its Generalizations Nir Rosenfeld, Ofer Meshi, Daniel Tarlow, Amir Globerson

UAI 2013 Learning Max-Margin Tree Predictors Ofer Meshi, Elad Eban, Gal Elidan, Amir Globerson

NeurIPS 2012 Convergence Rate Analysis of MAP Coordinate Minimization Algorithms Ofer Meshi, Amir Globerson, Tommi S. Jaakkola

ECML-PKDD 2011 An Alternating Direction Method for Dual MAP LP Relaxation Ofer Meshi, Amir Globerson

MLOSS 2010 FastInf: An Efficient Approximate Inference Library Ariel Jaimovich, Ofer Meshi, Ian McGraw, Gal Elidan

ICML 2010 Learning Efficiently with Approximate Inference via Dual Losses Ofer Meshi, David A. Sontag, Tommi S. Jaakkola, Amir Globerson

NeurIPS 2010 More Data Means Less Inference: A Pseudo-Max Approach to Structured Learning David Sontag, Ofer Meshi, Amir Globerson, Tommi S. Jaakkola

UAI 2009 Convexifying the Bethe Free Energy Ofer Meshi, Ariel Jaimovich, Amir Globerson, Nir Friedman

UAI 2007 Template Based Inference in Symmetric Relational Markov Random Fields Ariel Jaimovich, Ofer Meshi, Nir Friedman