Fetching the paper…
Reading the bibliography…
The log-linear model has received a significant amount of theoretical attention in previous decades and remains the fundamental tool used for learning probability distributions over discrete variables.
Two new properties of mathematical likelihood
R. A. Fisher · 1934
Earlier work this paper cites.
A mathematical theory of communication
C. E. Shannon · 1948
Earlier work this paper cites.
Multivariate information transmission
W. McGill · 1954
Earlier work this paper cites.
Covariance selection
A. P. Dempster · 1972
Earlier work this paper cites.
Multiple mutual informations and multiple interactions in frequency data
Te Sun Han · 1980
Earlier work this paper cites.
Differential geometry of smooth families of probability distributions
Hiroshi Nagaoka and Shun-ichi Amari · 1982
Earlier work this paper cites.
Stochastic relaxation, gibbs distributions, and the bayesian restoration of images
Stuart Geman and Donald Geman · 1984
Earlier work this paper cites.
A learning algorithm for boltzmann machines
David H. Ackley, Geoffrey E. Hinton, and Terrence J. Sejnowski · 1985
Earlier work this paper cites.
Higher-order Boltzmann machines
Terrence J. Sejnowski · 1986
Earlier work this paper cites.
Hierarchical variable selection in polynomial regression models
Julio L. Peixoto · 1987
Earlier work this paper cites.
Information and the Accuracy Attainable in the Estimation of Statistical Parameters , pp. 235–247
C. Radhakrishna Rao · 1992
Earlier work this paper cites.
On the existence of maximum likelihood estimators for graphical gaussian models
Søren L. Buhl · 1993
Earlier work this paper cites.
Constrained differentiation
G. Schay · 1995
Earlier work this paper cites.
Regression shrinkage and selection via the lasso
Robert Tibshirani · 1996
Earlier work this paper cites.
Methods of Information Geometry
S. Amari and H. Nagaoka · 2000
Earlier work this paper cites.
Gibbs sampling
Alan E. Gelfand · 2000
Earlier work this paper cites.
Information geometry on hierarchy of probability distributions
S.-I. Amari · 2001
Earlier work this paper cites.
Annealed importance sampling
Radford M. Neal · 2001
Cited alongside, same era.
Information-geometric measure for neural spikes
Hiroyuki Nakahara and Shun-Ichi Amari · 2002
Cited alongside, same era.
Statistical inference in context specific interaction models for contingency tables
Søren Højsgaard · 2004
Cited alongside, same era.
Reducing the dimensionality of data with neural networks
G. E. Hinton and R. R. Salakhutdinov · 2006
Cited alongside, same era.
Efficient structure learning of markov networks using l_1-regularization
Su-in Lee, Varun Ganapathi, and Daphne Koller · 2006
Cited alongside, same era.
High-dimensional graphical model selection using ℓ 1 \ell_{1} -regularized logistic regression
Martin J Wainwright, John Lafferty, and Pradeep Ravikumar · 2006
Cited alongside, same era.
Stratified Graphical Models - Context-Specific Independence in Graphical Models
Henrik Nyman, Johan Pensar, Timo Koski, and Jukka Corander · 2014
Later among the works it cites.
Feature selection using joint mutual information maximisation
Mohamed Bennasar, Yulia Hicks, and Rossitza Setchi · 2015
Later among the works it cites.
Feature selection with redundancy-complementariness dispersion
Zhijun Chen, Chaozhong Wu, Yishi Zhang, Zhen Huang, Bin Ran, Ming Zhong, and Nengchao Lyu · 2015
Later among the works it cites.
A novel feature selection method considering feature interaction
Zilin Zeng, Hongjun Zhang, Rui Zhang, and Chengxiang Yin · 2015
Later among the works it cites.
Information Geometry and Its Applications
Shun-Ichi Amari · 2016
Later among the works it cites.
Low-rank approximation and completion of positive tensors
Anil Aswani · 2016
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
A conjugate prior for discrete hierarchical log-linear models
Hélène Massam, Jinnan Liu, and Adrian Dobra · 2009
Cited alongside, same era.
Deep boltzmann machines
Ruslan Salakhutdinov and Geoffrey Hinton · 2009
Cited alongside, same era.
Learning markov network structure with decision trees
Daniel Lowd and Jesse Davis · 2010
Cited alongside, same era.
Convex structure learning in log-linear models: Beyond pairwise potentials
Mark Schmidt and Kevin Murphy · 2010
Cited alongside, same era.
Sparse low-order interaction network underlies a highly correlated and learnable neural population code
Elad Ganmor, Ronen Segev, and Elad Schneidman · 2011
Cited alongside, same era.
Markov network structure learning: A randomized feature generation approach
Jan Van Haaren and Jesse Davis · 2012
Cited alongside, same era.
Later among the works it cites.
Interaction pursuit with feature screening and selection, 2016
Yingying Fan, Yinfei Kong, Daoji Li, and Jinchi Lv · 2016
Later among the works it cites.
Computational Information Geometry
Frank Nielsen, Frank Critchley, and Christopher T. J. Dodson · 2017
Later among the works it cites.
High-dimensional hybrid feature selection using interaction information-guided search
Songyot Nakariyakul · 2018
Later among the works it cites.
Legendre decomposition for tensors
Mahito Sugiyama, Hiroyuki Nakahara, and Koji Tsuda · 2018
Later among the works it cites.
Pytorch: an imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Yang, Zach DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
Later among the works it cites.
Finding statistically significant interactions between continuous features
Mahito Sugiyama and Karsten Borgwardt · 2019
Later among the works it cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Later among the works it cites.
Sparse interaction additive networks via feature interaction detection and sparse selection
James Enouen and Yan Liu · 2022
Later among the works it cites.
Many-body approximation for non-negative tensors
Kazu Ghalamkari, Mahito Sugiyama, and Yoshinobu Kawahara · 2023
Later among the works it cites.
Towards hybrid-grained feature interaction selection for deep sparse network
Fuyuan Lyu, Xing Tang, Dugang Liu, Chen Ma, Weihong Luo, Liang Chen, xiuqiang He, and Xue (Steve) Liu · 2023
Later among the works it cites.