On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,341 papers · 148 categories

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9 results for “image-genomics”

Going off the Grid: Iterative Model Selection for Biclustered Matrix Completionstat.CO

New method for matrix completion with row and column similarities.

problem Matrix completion with row and column similarities.

method Iterative model selection with Hutchinson estimator.

result Effective model selection for optimal smoothing parameters.

matrix completion biclustering iterative model selection Hutchinson estimator image-genomics

2016-10-18abs ↗pdf ↗

FDR-Corrected Sparse Canonical Correlation Analysis with Applications to Imaging Genomicsstat.ME

Proposes FDR-corrected sparse CCA for neuroimaging and genomics.

problem High-dimensional datasets in neuroimaging and genomics make false discoveries a concern.

method FDR-corrected sparse canonical correlation analysis (CCA) for high-dimensional settings.

result The proposed method controls the FDR of canonical vectors in high-dimensional settings.

FDR sparse CCA neuroimaging genomics false discovery rate

2017-05-11abs ↗pdf ↗

Challenges and proposed solutions in modeling multimodal data: A systematic reviewcs.LG

Systematic review of multimodal data challenges and solutions.

problem Challenges in integrating diverse data types for improved diagnostics and personalized care.

method Synthesizing findings from 69 studies on technical obstacles and recent methodological advances.

result Promising solutions like transfer learning, generative models, attention mechanisms, and neural architecture search.

multimodal data clinical research diagnostics personalized care transfer learning

2025-05-11abs ↗pdf ↗

Multi-Domain Translation by Learning Uncoupled Autoencoderscs.LG

New framework for multi-domain translation using autoencoders.

problem Learning probabilistic coupling between different domains.

method Learning multiple uncoupled autoencoders under shared latent distribution.

result New autoencoders can be added sequentially without retraining.

multi-domain translation autoencoders shared latent distribution probabilistic coupling image genomics

2019-02-09abs ↗pdf ↗

An Optimal Statistical and Computational Framework for Generalized Tensor Estimationmath.ST

Paper proposes an optimal framework for tensor estimation across various applications.

problem Generalized tensor estimation problems in computational imaging, genomics, and network analysis.

method Unified projected gradient descent approach to find low-rank tensor fits under generalized parametric models.

result Achieves minimax optimal rate of convergence in estimation error for various tensor estimation problems.

Tensor Estimation Low-Rank Tensor Projected Gradient Descent Generalized Parametric Models Optimal Rate of Convergence

2020-02-26abs ↗pdf ↗

Supervised Dimensionality Reduction for Big Datastat.ML

LOL improves data representations for disease classification.

problem Building accurate data-driven inferences from high-dimensional biomedical data.

method Extending principal components analysis with class-conditional moment estimates.

result LOL and its generalizations lead to improved data representations for classification.

dimensionality reduction big data principal components class-conditional brain imaging

2017-09-05abs ↗pdf ↗

DeepHealth: Review and challenges of artificial intelligence in health informaticscs.LG

AI improves healthcare diagnostics and predictions.

problem Data heterogeneity and model limitations in AI for health.

method Review of AI applications in health informatics.

result AI enhances disease diagnosis and prediction.

AI health informatics medical imaging genomics disease prediction

2019-09-01abs ↗pdf ↗

Regularization Parameter Selection for a Bayesian Multi-Level Group Lasso Regression Model with Application to Imaging Genomicsstat.ML

Bayesian multi-level group lasso model tackles neuroimaging and genetic data.

problem Overshrinkage of regression parameter estimates in high-dimensional settings or weak genetic effects.

method Tuning parameter selection through hierarchical Bayes and empirical Bayes, followed by WAIC approximation.

result WAIC provides a better approximation to marginal likelihood and avoids overshrinkage.

Bayesian lasso group lasso neuroimaging genomics tuning parameter

2016-03-27abs ↗pdf ↗

A Bayesian Group Sparse Multi-Task Regression Model for Imaging Geneticsstat.ME

Bayesian model for genetic influence on brain structure.

problem Point estimates of genetic effects on brain structure.

method Bayesian hierarchical modeling with Gibbs sampling.

result Bayesian method provides interval estimates for genetic effects.

Bayesian statistics genetics neuroimaging interval estimation penalized regression

2016-05-07abs ↗pdf ↗