Mutual Information for Low-Rank Even-Order Symmetric Tensor Factorization

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We consider the problem of parameter estimation in a Bayesian setting and propose a general lower-bound that includes part of the family of f-Divergences. The results are then applied to specific settings of interest and compared to other notable results i ...

A geometric method of lattice reduction based on cycles of directional and hyperplanar shears is presented. The deviation from cubicity at each step of the reduction is evaluated by a parameter called 'basis rhombicity' which is the sum of the absolute val ...

Inferring protein-protein interactions from sequences is an important task in computational biology. Recent methods based on Direct Coupling Analysis (DCA) or Mutual Information (MI) allow to find interaction partners among paralogs of two protein families ...

Aerosol mass spectrometry (AMS) and mid-infrared spectroscopy (MIR) are two analytical methods for characterizing the chemical composition of OM. While AMS provides high-temporal-resolution bulk measurements, the extensive fragmentation during the electron ...

Machine learning frameworks based on correlations of interatomic positions begin with a discretized description of the density of other atoms in the neighborhood of each atom in the system. Symmetry considerations support the use of spherical harmonics to ...

Recommenders are central in many applications today. The most effective recommendation schemes, such as those based on collaborative filtering (CF), exploit similarities between user profiles to make recommendations, but potentially expose private data. Fe ...

We consider a statistical model for finite-rank symmetric tensor factorization and prove a single-letter variational expression for its asymptotic mutual information when the tensor is of even order. The proof applies the adaptive interpolation method orig ...

Poor decisions and selfish behaviors give rise to seemingly intractable global problems, such as the lack of transparency in democratic processes, the spread of conspiracy theories, and the rise in greenhouse gas emissions. However, people are more predict ...

This thesis focuses on two kinds of statistical inference problems in signal processing and data science. The first problem is the estimation of a structured informative tensor from the observation of a noisy tensor in which it is buried. The structure com ...

Due to conservative approaches in construction design and practice, infrastructure often has hidden reserve capacity. When quantified, this reserve has potential to improve decisions related to asset management. Field measurements, collected through load t ...

Mutual Information for Low-Rank Even-Order Symmetric Tensor Factorization

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Lower-bounds on the Bayesian Risk in Estimation Procedures via f–Divergences

A new method for lattice reduction using directional and hyperplanar shearing

Correlations from structure and phylogeny combine constructively in the inference of protein partners from sequences

Fragment ion-functional group relationships in organic aerosols using aerosol mass spectrometry and mid-infrared spectroscopy

A smooth basis for atomistic machine learning

TEE-based decentralized recommender systems: The raw data sharing redemption

Mutual information for low-rank even-order symmetric tensor estimation

Discrete-Choice Mining of Social Processes

Statistical limits of high-dimensional inference problems

A Comparison of optimal measurement-system design with engineering judgement for bridge load testing