Ofer Meshi
Ofer Meshi
Research Scientist at Google
Email verificata su google.com - Home page
Citata da
Citata da
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
Joint European conference on machine learning and knowledge discovery in…, 2011
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
Smooth and strong: MAP inference with linear convergence
O Meshi, M Mahdavi, A Schwing
Advances in Neural Information Processing Systems, 298-306, 2015
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
Convergence rate analysis of MAP coordinate minimization algorithms
O Meshi, A Globerson, TS Jaakkola
Advances in Neural Information Processing Systems, 3014-3022, 2012
Linear-memory and decomposition-invariant linearly convergent conditional gradient algorithm for structured polytopes
D Garber, O Meshi
Advances in neural information processing systems, 1001-1009, 2016
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
Efficient training of structured svms via soft constraints
O Meshi, N Srebro, T Hazan
Artificial Intelligence and Statistics, 699-707, 2015
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), 1, 2007
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
FastInf: An efficient approximate inference library
A Jaimovich, O Meshi, I McGraw, G Elidan
The Journal of Machine Learning Research 11, 1733-1736, 2010
Deep structured prediction with nonlinear output transformations
C Graber, O Meshi, A Schwing
Advances in Neural Information Processing Systems, 6320-6331, 2018
Learning Max-Margin Tree Predictors
O Meshi, E Eban, G Elidan, A Globerson
Uncertainty in Artificial Intelligence (UAI), 2013
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
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
Asynchronous parallel coordinate minimization for map inference
O Meshi, A Schwing
Advances in Neural Information Processing Systems, 5734-5744, 2017
Fast and scalable structural SVM with slack rescaling
H Choi, O Meshi, N Srebro
Artificial Intelligence and Statistics, 667-675, 2016
On the tightness of lp relaxations for structured prediction
O Meshi, M Mahdavi, D Sontag
arXiv preprint arXiv:1511.01419 1 (2), 3.1, 2015
Il sistema al momento non pu eseguire l'operazione. Riprova pi tardi.
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