Tensor recovery in high-dimensional Ising models
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Publication:6596178
DOI10.1016/j.jmva.2024.105335MaRDI QIDQ6596178
Somabha Mukherjee, Tianyu Liu, Rahul Biswas
Publication date: 2 September 2024
Published in: Journal of Multivariate Analysis (Search for Journal in Brave)
Lattice systems (Ising, dimer, Potts, etc.) and systems on graphs arising in equilibrium statistical mechanics (82B20) Multivariate analysis (62Hxx) Probabilistic graphical models (62H22)
Cites Work
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- High-dimensional structure estimation in Ising models: local separation criterion
- Evolutionary trees and the Ising model on the Bethe lattice: A proof of Steel's conjecture
- High-dimensional Ising model selection using \(\ell _{1}\)-regularized logistic regression
- Asymptotics of maximum likelihood estimators for the Curie-Weiss model
- Fluctuations of the free energy in the REM and the \(p\)-spin SK models
- The minimax learning rates of normal and Ising undirected graphical models
- Learning a tree-structured Ising model in order to make predictions
- Joint estimation of parameters in Ising model
- Hypergraph with sampling for image retrieval
- Property testing in high-dimensional Ising models
- Inference in Ising models
- Estimation in spin glasses: a first step
- Efficiently Learning Ising Models on Arbitrary Graphs
- Ising models for neural activity inferred via selective cluster expansion: structural and coding properties
- Notes on ferromagneticp-spin and REM
- Landscape statistics of thep-spin Ising model
- Hidden Markov Models and Disease Mapping
- Hypergraphs for predicting essential genes using multiprotein complex data
- Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)
- High-temperature structure detection in ferromagnets
- Beitrag zur Theorie des Ferromagnetismus
- Information-Theoretic Limits of Selecting Binary Graphical Models in High Dimensions
- Neural networks and physical systems with emergent collective computational abilities.
- Approximating discrete probability distributions with dependence trees
- Estimation in tensor Ising models
- Consistent causal inference from time series with PC algorithm and its time-aware extension
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