Research
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.

168,657 papers · 148 categories

Trend · papers per month

count% of corpus
1122 · Jun 202219922001200920172026
7 results for “Sparsity-Recovery”
Asymptotic Behavior of Adversarial Training Estimator under ℓ∞\ell_\infty-Perturbationmath.ST

The paper studies the asymptotic behavior of adversarial training under ℓ∞\ell_\infty-perturbation.

problem Theoretical guarantees for sparsity-recovery in adversarial training.
method Investigation of the asymptotic distribution of the adversarial training estimator in generalized linear models.
result The asymptotic distribution of the adversarial training estimator under ℓ∞\ell_\infty-perturbation could have a positive probability mass at 0 when the true parameter is 0.
Adversarial TrainingAsymptotic BehaviorSparsity-RecoveryEll Infinity PerturbationGeneralized Linear Model
2024-01-27abs ↗pdf ↗
Provable Guarantees for Sparsity Recovery with Deterministic Missing Data Patternscs.LG

Paper proposes efficient algorithm for recovering sparsity pattern from deterministic missing data.

problem Recovering sparsity pattern from datasets with deterministic missing structure.
method Proposes an efficient algorithm for missing value imputation using topological property of censorship filter.
result Consistently recovers the sparsity pattern with high probability in polynomial time and logarithmic sample complexity.
sparsity recoverydeterministic missing datalassotopological propertyimputation
2022-06-10abs ↗pdf ↗
Learning the Structure of Large Networked Systems Obeying Conservation Lawsstat.ML

Estimates network structure from node potentials and edge flows under Gaussian injection statistics.

problem Estimating network structure from node potentials and edge flows under Gaussian injection statistics.
method Proposes an ℓ1\ell_{1}-regularized maximum likelihood estimator for high-dimensional network structure estimation.
result Establishes sufficient conditions for exact sparsity recovery of network structure with high probability.
network structureconservation lawsmaximum likelihoodsparsity recoveryGaussian distribution
2022-06-14abs ↗pdf ↗
Entropy-Regularized Probabilistic Gates for Sparse Model Discovery in Scarce-Data Federated Learningcs.LG

Entropy regularization improves sparse model discovery in federated learning.

problem Sparse model discovery in federated learning with limited data.
method Entropy regularization of gate distributions for probabilistic sparse model exploration.
result Entropy regularization leads to better sparse model recovery and performance.
federated learningsparse modelsentropy regularizationgate distributionsuncertainty exploration
2026-06-30abs ↗pdf ↗