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All publications by Justin Domke
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Maximum Likelihood Learning With Arbitrary Treewidth via Fast-Mixing Parameter Sets
Justin Domke
Advances in Neural Information Processing Systems 28, 2015


Reflection, Refraction, and Hamiltonian Monte Carlo
Hadi M. Afshar and Justin Domke
Advances in Neural Information Processing Systems 28, 2015


Finito: A faster, permutable incremental gradient method for big data problems
Aaron Defazio, Justin Domke and Tiberio Caetano
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Projecting Markov Random Field Parameters for Fast Mixing
Xianghang Liu and Justin Domke
Advances in Neural Information Processing Systems 27, 2014


Projecting Ising Model Parameters for Fast Mixing
Justin Domke and Xianghang Liu
Advances in Neural Information Processing Systems 26, 2013


Structured Learning via Logistic Regression
Justin Domke
Advances in Neural Information Processing Systems 26, 2013


Generic Methods for Optimization-Based Modeling
Justin Domke
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics (AISTATS-12), 2012


Implicit Differentiation by Perturbation
Justin Domke
Advances in Neural Information Processing Systems 23, 2010