Ofer Meshi
Ofer Meshi
Research Scientist at Google
Verified email at - Homepage
Cited by
Cited by
Learning efficiently with approximate inference via dual losses
O Meshi, D Sontag, T Jaakkola, A Globerson
International Machine Learning Society, 2010
An alternating direction method for dual MAP LP relaxation
O Meshi, A Globerson
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2011
Seq2Slate: Re-ranking and slate optimization with RNNs
I Bello, S Kulkarni, S Jain, C Boutilier, E Chi, E Eban, X Luo, A Mackey, ...
arXiv preprint arXiv:1810.02019, 2018
Convexifying the Bethe free energy
O Meshi, A Jaimovich, A Globerson, N Friedman
arXiv preprint arXiv:1205.2624, 2012
Template based inference in symmetric relational Markov random fields
A Jaimovich, O Meshi, N Friedman
arXiv preprint arXiv:1206.5276, 2012
Linear-memory and decomposition-invariant linearly convergent conditional gradient algorithm for structured polytopes
D Garber, O Meshi
Advances in neural information processing systems 29, 2016
Smooth and strong: Map inference with linear convergence
O Meshi, M Mahdavi, A Schwing
Advances in Neural Information Processing Systems 28, 2015
Convergence rate analysis of MAP coordinate minimization algorithms
O Meshi, A Globerson, T Jaakkola
Advances in Neural Information Processing Systems 25, 2012
More data means less inference: A pseudo-max approach to structured learning
D Sontag, O Meshi, T Jaakkola, A Globerson
Neural Information Processing Systems Foundation, 2010
Planning and learning with stochastic action sets
C Boutilier, A Cohen, A Daniely, A Hassidim, Y Mansour, O Meshi, ...
arXiv preprint arXiv:1805.02363, 2018
Learning structured models with the AUC loss and its generalizations
N Rosenfeld, O Meshi, D Tarlow, A Globerson
Artificial Intelligence and Statistics, 841-849, 2014
Deep structured prediction with nonlinear output transformations
C Graber, O Meshi, A Schwing
Advances in Neural Information Processing Systems 31, 2018
Train and Test Tightness of LP Relaxations in Structured Prediction
O Meshi, M Mahdavi, A Weller, D Sontag
International Conference on Machine Learning (ICML), 2016
Evolutionary conservation and over-representation of functionally enriched network patterns in the yeast regulatory network
O Meshi, T Shlomi, E Ruppin
BMC systems biology 1, 1-7, 2007
Empirical Bayes regret minimization
CW Hsu, B Kveton, O Meshi, M Mladenov, C Szepesvari
arXiv preprint arXiv:1904.02664, 2019
Efficient training of structured svms via soft constraints
O Meshi, N Srebro, T Hazan
Artificial Intelligence and Statistics, 699-707, 2015
FastInf: An efficient approximate inference library
A Jaimovich, O Meshi, I McGraw, G Elidan
The Journal of Machine Learning Research 11, 1733-1736, 2010
On the value of prior in online learning to rank
B Kveton, O Meshi, M Zoghi, Z Qin
International Conference on Artificial Intelligence and Statistics, 6880-6892, 2022
Asynchronous parallel coordinate minimization for map inference
O Meshi, A Schwing
Advances in Neural Information Processing Systems 30, 2017
Approximate linear programming for logistic Markov decision processes
M Mladenov, C Boutilier, D Schuurmans, G Elidan, O Meshi, T Lu
Proceedings of the Twenty-sixth International Joint Conference on Artificial …, 2017
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