Ofer Meshi - RankMe

44 papers A* 9A 8Journal 19Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	ConvApparel: A Benchmark Dataset and Validation Framework for User Simulators in Conversational Recommenders. EACL (Volume 1: Long Papers) Ofer Meshi, Krisztian Balog, Sally Goldman, Avi Caciularu, Guy Tennenholtz, Jihwan Jeong, Amir Globerson, Craig Boutilier
2026	J	`jnl`	ConvApparel: A Benchmark Dataset and Validation Framework for User Simulators in Conversational Recommenders. CoRR Ofer Meshi, Krisztian Balog, Sally Goldman, Avi Caciularu, Guy Tennenholtz, Jihwan Jeong, Amir Globerson, Craig Boutilier
2025	J	`jnl`	Asking Clarifying Questions for Preference Elicitation With Large Language Models. CoRR Ali Montazeralghaem, Guy Tennenholtz, Craig Boutilier, Ofer Meshi
2024	A*	`conf`	Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval. NeurIPS Haolun Wu, Ofer Meshi, Masrour Zoghi, Fernando Diaz, Xue (Steve) Liu, Craig Boutilier, Maryam Karimzadehgan
2024	A*	`conf`	Minimizing Live Experiments in Recommender Systems: User Simulation to Evaluate Preference Elicitation Policies. SIGIR Chih-Wei Hsu, Martin Mladenov, Ofer Meshi, James Pine, Hubert Pham, Shane Li, Xujian Liang, Anton Polishko, Li Yang, Ben Scheetz, Craig Boutilier
2024	J	`jnl`	Minimizing Live Experiments in Recommender Systems: User Simulation to Evaluate Preference Elicitation Policies. CoRR Chih-Wei Hsu, Martin Mladenov, Ofer Meshi, James Pine, Hubert Pham, Shane Li, Xujian Liang, Anton Polishko, Li Yang, Ben Scheetz, Craig Boutilier
2024	A*	`conf`	Model-Free Preference Elicitation. IJCAI Carlos Martin, Craig Boutilier, Ofer Meshi, Tuomas Sandholm
2023	J	`jnl`	Density-based User Representation through Gaussian Process Regression for Multi-interest Personalized Retrieval. CoRR Haolun Wu, Ofer Meshi, Masrour Zoghi, Fernando Diaz, Xue Liu, Craig Boutilier, Maryam Karimzadehgan
2023	A	`conf`	Overcoming Prior Misspecification in Online Learning to Rank. AISTATS Javad Azizi, Ofer Meshi, Masrour Zoghi, Maryam Karimzadehgan
2023	J	`jnl`	Overcoming Prior Misspecification in Online Learning to Rank. CoRR Javad Azizi, Ofer Meshi, Masrour Zoghi, Maryam Karimzadehgan
2022	A	`conf`	On the Value of Prior in Online Learning to Rank. AISTATS Branislav Kveton, Ofer Meshi, Masrour Zoghi, Zhen Qin
2019	A*	`conf`	Advantage Amplification in Slowly Evolving Latent-State Environments. IJCAI Martin Mladenov, Ofer Meshi, Jayden Ooi, Dale Schuurmans, Craig Boutilier
2019	J	`jnl`	Advantage Amplification in Slowly Evolving Latent-State Environments. CoRR Martin Mladenov, Ofer Meshi, Jayden Ooi, Dale Schuurmans, Craig Boutilier
2019	J	`jnl`	Empirical Bayes Regret Minimization. CoRR Chih-Wei Hsu, Branislav Kveton, Ofer Meshi, Martin Mladenov, Csaba Szepesvári
2019	J	`jnl`	Train and Test Tightness of LP Relaxations in Structured Prediction. J. Mach. Learn. Res. Ofer Meshi, Ben London, Adrian Weller, David A. Sontag
2018	A*	`conf`	Deep Structured Prediction with Nonlinear Output Transformations. NeurIPS Colin Graber, Ofer Meshi, Alexander G. Schwing
2018	J	`jnl`	Deep Structured Prediction with Nonlinear Output Transformations. CoRR Colin Graber, Ofer Meshi, Alexander G. Schwing
2018	A*	`conf`	Planning and Learning with Stochastic Action Sets. IJCAI Craig Boutilier, Alon Cohen, Avinatan Hassidim, Yishay Mansour, Ofer Meshi, Martin Mladenov, Dale Schuurmans
2018	J	`jnl`	Planning and Learning with Stochastic Action Sets. CoRR Craig Boutilier, Alon Cohen, Amit Daniely, Avinatan Hassidim, Yishay Mansour, Ofer Meshi, Martin Mladenov, Dale Schuurmans
2018	J	`jnl`	Seq2Slate: Re-ranking and Slate Optimization with RNNs. CoRR Irwan Bello, Sayali Kulkarni, Sagar Jain, Craig Boutilier, Ed Huai-hsin Chi, Elad Eban, Xiyang Luo, Alan Mackey, Ofer Meshi
2017	—	`conf`	Asynchronous Parallel Coordinate Minimization for MAP Inference. NIPS Ofer Meshi, Alexander G. Schwing
2017	A*	`conf`	Logistic Markov Decision Processes. IJCAI Martin Mladenov, Craig Boutilier, Dale Schuurmans, Ofer Meshi, Gal Elidan, Tyler Lu
2016	A	`conf`	Fast and Scalable Structural SVM with Slack Rescaling. AISTATS Heejin Choi, Ofer Meshi, Nathan Srebro
2016	—	`conf`	Linear-Memory and Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes. NIPS Dan Garber, Ofer Meshi
2016	J	`jnl`	Linear-memory and Decomposition-invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes. CoRR Dan Garber, Ofer Meshi
2016	A*	`conf`	Train and Test Tightness of LP Relaxations in Structured Prediction. ICML Ofer Meshi, Mehrdad Mahdavi, Adrian Weller, David A. Sontag
2015	A	`conf`	Efficient Training of Structured SVMs via Soft Constraints. AISTATS Ofer Meshi, Nathan Srebro, Tamir Hazan
2015	J	`jnl`	Fast and Scalable Structural SVM with Slack Rescaling. CoRR Heejin Choi, Ofer Meshi, Nathan Srebro
2015	J	`jnl`	On the Tightness of LP Relaxations for Structured Prediction. CoRR Ofer Meshi, Mehrdad Mahdavi, David A. Sontag
2015	—	`conf`	Smooth and Strong: MAP Inference with Linear Convergence. NIPS Ofer Meshi, Mehrdad Mahdavi, Alexander G. Schwing
2014	A	`conf`	Learning Structured Models with the AUC Loss and Its Generalizations. AISTATS Nir Rosenfeld, Ofer Meshi, Daniel Tarlow, Amir Globerson
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
2013	A	`conf`	Learning Max-Margin Tree Predictors. UAI Ofer Meshi, Elad Eban, Gal Elidan, Amir Globerson
2013	J	`jnl`	Learning Max-Margin Tree Predictors. CoRR Ofer Meshi, Elad Eban, Gal Elidan, Amir Globerson
2012	—	`conf`	Convergence Rate Analysis of MAP Coordinate Minimization Algorithms. NIPS Ofer Meshi, Tommi S. Jaakkola, Amir Globerson
2012	J	`jnl`	Convexifying the Bethe Free Energy CoRR Ofer Meshi, Ariel Jaimovich, Amir Globerson, Nir Friedman
2012	J	`jnl`	Template Based Inference in Symmetric Relational Markov Random Fields CoRR Ariel Jaimovich, Ofer Meshi, Nir Friedman
2011	—	`conf`	An Alternating Direction Method for Dual MAP LP Relaxation. ECML/PKDD (2) Ofer Meshi, Amir Globerson
2010	J	`jnl`	FastInf: An Efficient Approximate Inference Library. J. Mach. Learn. Res. Ariel Jaimovich, Ofer Meshi, Ian McGraw, Gal Elidan
2010	A*	`conf`	Learning Efficiently with Approximate Inference via Dual Losses. ICML Ofer Meshi, David A. Sontag, Tommi S. Jaakkola, Amir Globerson
2010	—	`conf`	More data means less inference: A pseudo-max approach to structured learning. NIPS David A. Sontag, Ofer Meshi, Tommi S. Jaakkola, Amir Globerson
2009	A	`conf`	Convexifying the Bethe Free Energy. UAI Ofer Meshi, Ariel Jaimovich, Amir Globerson, Nir Friedman
2007	J	`jnl`	Evolutionary conservation and over-representation of functionally enriched network patterns in the yeast regulatory network. BMC Syst. Biol. Ofer Meshi, Tomer Shlomi, Eytan Ruppin
2007	A	`conf`	Template Based Inference in Symmetric Relational Markov Random Fields. UAI Ariel Jaimovich, Ofer Meshi, Nir Friedman