Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T20:33:48.356510Z
Paper Citation Record · LEDGER
As of 16 August 2026, this Paper Citation Record lists 85 of 85 outbound references and 0 inbound Pith citation observations for arXiv:2412.05726.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-11T20:33:48.356510Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
85 of 85 outbound references displayed
External citation measurements
No source-named external measurement is stored.
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Proximal Iteration for Nonlinear Adaptive Lasso Bayesian inference for spatio-temporal spike-and-slab priors
Reference 1
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Proximal Iteration for Nonlinear Adaptive Lasso Gravity with gravitas: A solution to the border puzzle
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Proximal Iteration for Nonlinear Adaptive Lasso Structured sparsity through convex optimization
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Proximal Iteration for Nonlinear Adaptive Lasso Optimization with sparsity-inducing penalties
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Proximal Iteration for Nonlinear Adaptive Lasso Adaptive regression and model selection in data mining problems
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Proximal Iteration for Nonlinear Adaptive Lasso Model-based compressive sensing
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Proximal Iteration for Nonlinear Adaptive Lasso Convex Analysis and Monotone Operator Theory in Hilbert Spaces
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Proximal Iteration for Nonlinear Adaptive Lasso Bayesian shrinkage
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Proximal Iteration for Nonlinear Adaptive Lasso Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information
Reference 12
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Proximal Iteration for Nonlinear Adaptive Lasso Enhancing sparsity by reweighted _1 minimization
Reference 13
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Proximal Iteration for Nonlinear Adaptive Lasso Carvalho, Nicholas G
Reference 14
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Proximal Iteration for Nonlinear Adaptive Lasso Some statistical models for limited dependent variables with application to the demand for durable goods
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Proximal Iteration for Nonlinear Adaptive Lasso TensorFlow Distributions
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Proximal Iteration for Nonlinear Adaptive Lasso Unresolved cited work
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Proximal Iteration for Nonlinear Adaptive Lasso Boltzmann machine and mean-field approximation for structured sparse decompositions
Reference 18
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Proximal Iteration for Nonlinear Adaptive Lasso On the deep active-subspace method
Reference 19
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Proximal Iteration for Nonlinear Adaptive Lasso Least angle regression
Reference 20
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Proximal Iteration for Nonlinear Adaptive Lasso Variable selection via nonconcave penalized likelihood and its oracle properties
Reference 21
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Proximal Iteration for Nonlinear Adaptive Lasso Regularization paths for generalized linear models via coordinate descent
Reference 22
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Proximal Iteration for Nonlinear Adaptive Lasso Regularization paths for generalized linear models via coordinate descent
Reference 23
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Proximal Iteration for Nonlinear Adaptive Lasso Near-optimal sparse fourier representations via sampling
Reference 24
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Proximal Iteration for Nonlinear Adaptive Lasso MLGL : an R package implementing correlated variable selection by hierarchical clustering and group-lasso
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Proximal Iteration for Nonlinear Adaptive Lasso Feature selection based on structured sparsity: A comprehensive study
Reference 26
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Proximal Iteration for Nonlinear Adaptive Lasso Computing proximal points of nonconvex functions
Reference 27
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Proximal Iteration for Nonlinear Adaptive Lasso A Bayesian Lasso based Sparse Learning Model
Reference 28
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Proximal Iteration for Nonlinear Adaptive Lasso Ridge regression: Biased estimation for nonorthogonal problems
Reference 29
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Proximal Iteration for Nonlinear Adaptive Lasso Learning with structured sparsity
Reference 30
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Proximal Iteration for Nonlinear Adaptive Lasso Hunter and Runze Li
Reference 31
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Observation 997509e0-ba64-4472-b043-2788070fc5cc · outbound
Proximal Iteration for Nonlinear Adaptive Lasso Fast sparse group L asso
Reference 32
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Proximal Iteration for Nonlinear Adaptive Lasso Group lasso with overlap and graph lasso
Reference 33
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Proximal Iteration for Nonlinear Adaptive Lasso Structured variable selection with sparsity-inducing norms
Reference 34
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Proximal Iteration for Nonlinear Adaptive Lasso Proximal methods for hierarchical sparse coding
Reference 35
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Proximal Iteration for Nonlinear Adaptive Lasso Accelerating stochastic gradient descent using predictive variance reduction
Reference 36
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Observation 5be62071-da5a-43be-9641-e01efca0e5a8 · outbound
Proximal Iteration for Nonlinear Adaptive Lasso Self-adaptive lasso and its B ayesian estimation
Reference 37
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Proximal Iteration for Nonlinear Adaptive Lasso Tree-guided group lasso for multi-response regression with structured sparsity, with an application to eqtl mapping
Reference 38
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Proximal Iteration for Nonlinear Adaptive Lasso Adam: A Method for Stochastic Optimization
Reference 39
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Proximal Iteration for Nonlinear Adaptive Lasso Bayesian adaptive lasso
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Proximal Iteration for Nonlinear Adaptive Lasso Global convergence of splitting methods for nonconvex composite optimization
Reference 41
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Proximal Iteration for Nonlinear Adaptive Lasso Sliced inverse regression for dimension reduction
Reference 42
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Proximal Iteration for Nonlinear Adaptive Lasso A simple sampler for the horseshoe estimator
Reference 43
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Proximal Iteration for Nonlinear Adaptive Lasso On exact _q denoising
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Proximal Iteration for Nonlinear Adaptive Lasso Notes on cepii’s distances measures: The geodist database
Reference 46
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Proximal Iteration for Nonlinear Adaptive Lasso Relaxed lasso
Reference 47
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Proximal Iteration for Nonlinear Adaptive Lasso Unresolved cited work
Reference 48
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Proximal Iteration for Nonlinear Adaptive Lasso Solving structured sparsity regularization with proximal methods
Reference 49
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Proximal Iteration for Nonlinear Adaptive Lasso Convex Relaxation for Combinatorial Penalties
Reference 50
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Proximal Iteration for Nonlinear Adaptive Lasso Group Lasso with Overlaps: the Latent Group Lasso approach
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Reference 52
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Proximal Iteration for Nonlinear Adaptive Lasso Proximal algorithms
Reference 53
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Proximal Iteration for Nonlinear Adaptive Lasso The B ayesian lasso
Reference 54
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Proximal Iteration for Nonlinear Adaptive Lasso Proximal algorithms in statistics and machine learning
Reference 55
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Proximal Iteration for Nonlinear Adaptive Lasso Generalized approximate message passing for estimation with random linear mixing
Reference 56
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Proximal Iteration for Nonlinear Adaptive Lasso Convergence of Stochastic Proximal Gradient Algorithm
Reference 57
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Proximal Iteration for Nonlinear Adaptive Lasso Nonlinear sparse B ayesian learning for physics-based models
Reference 58
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Proximal Iteration for Nonlinear Adaptive Lasso Turbo reconstruction of structured sparse signals
Reference 59
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Proximal Iteration for Nonlinear Adaptive Lasso Towards closing the gap between the theory and practice of svrg
Reference 61
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Proximal Iteration for Nonlinear Adaptive Lasso Learning the structure for structured sparsity
Reference 62
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Proximal Iteration for Nonlinear Adaptive Lasso The log of gravity
Reference 63
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Proximal Iteration for Nonlinear Adaptive Lasso A sparse-group lasso
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Proximal Iteration for Nonlinear Adaptive Lasso Understanding the rationales and information environments for early, late, and nonadopters of the covid-19 vaccine
Reference 65
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Proximal Iteration for Nonlinear Adaptive Lasso Feature selection guided by structural information
Reference 66
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Proximal Iteration for Nonlinear Adaptive Lasso Deconvolution with the _1 norm
Reference 67
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Proximal Iteration for Nonlinear Adaptive Lasso GPU -accelerated G ibbs sampling: a case study of the horseshoe probit model
Reference 68
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Proximal Iteration for Nonlinear Adaptive Lasso Regression shrinkage and selection via the lasso
Reference 69
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Proximal Iteration for Nonlinear Adaptive Lasso Sparsity and smoothness via the fused lasso
Reference 70
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Proximal Iteration for Nonlinear Adaptive Lasso Strong rules for discarding predictors in lasso-type problems
Reference 71
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Reference 72
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Proximal Iteration for Nonlinear Adaptive Lasso Sparse B ayesian learning and the relevance vector machine
Reference 73
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Proximal Iteration for Nonlinear Adaptive Lasso Deep active subspaces: A scalable method for high-dimensional uncertainty propagation
Reference 74
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Proximal Iteration for Nonlinear Adaptive Lasso Experiments: planning, analysis, and optimization
Reference 75
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Proximal Iteration for Nonlinear Adaptive Lasso A proximal stochastic gradient method with progressive variance reduction
Reference 76
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Proximal Iteration for Nonlinear Adaptive Lasso Efficient methods for overlapping group lasso
Reference 77
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Proximal Iteration for Nonlinear Adaptive Lasso Model selection and estimation in regression with grouped variables
Reference 78
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Proximal Iteration for Nonlinear Adaptive Lasso Nearly unbiased variable selection under minimax concave penalty
Reference 79
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Proximal Iteration for Nonlinear Adaptive Lasso Bayesian group factor analysis with structured sparsity
Reference 80
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Proximal Iteration for Nonlinear Adaptive Lasso Modeling disease progression via fused sparse group lasso
Reference 81
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Proximal Iteration for Nonlinear Adaptive Lasso A generalized framework for learning and recovery of structured sparse signals
Reference 82
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Proximal Iteration for Nonlinear Adaptive Lasso The adaptive lasso and its oracle properties
Reference 83
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Proximal Iteration for Nonlinear Adaptive Lasso One-step sparse estimates in nonconcave penalized likelihood models
Reference 84
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Proximal Iteration for Nonlinear Adaptive Lasso Sparse principal component analysis
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