#computational efficiency
6 resultsAn Algorithm for Graph-Fused Lasso Based on Graph Decomposition
Feng Yu, Yi Yang, Teng Zhang
The paper introduces a new ADMM-based algorithm for the graph-fused lasso that decomposes the objective into two parts to reduce per-iteration cost and achieve faster convergence.
Acceleration of rank-constrained spatial covariance matrix estimation for blind speech extraction
Yuki Kubo, Norihiro Takamune, Daichi Kitamura +1
The paper introduces faster update rules for estimating rank-constrained spatial covariance matrices used in blind speech extraction, eliminating costly matrix inversions and multi…
Risk-Limiting Bayesian Polling Audits for Two Candidate Elections
Poorvi L. Vora
The paper presents a unified framework for risk‑limiting and Bayesian polling audits in two‑candidate plurality elections, derives a general Bayesian audit without restricting the…
On variational iterative methods for semilinear problems
Prosper Torsu
The paper proposes an iterative technique that transforms semilinear problems into linear systems, allowing fast Poisson solvers to efficiently compute accurate solutions.
Adaptive Conditional Bias-Penalized Kalman Filter for Improved Estimation of Extremes and its Approximation for Reduced Computation
Haojing Shen, Haksu Lee, Dong-Jun Seo
The paper proposes an adaptive, variance‑inflated version of the conditional bias‑penalized Kalman filter that improves estimation of extreme states while reducing computational co…
Framelet Pooling Aided Deep Learning Network : The Method to Process High Dimensional Medical Data
Chang Min Hyun, Kang Cheol Kim, Hyun Cheol Cho +2
The paper proposes a framelet‑pooling based deep learning approach that reduces high‑dimensional medical image data into lower‑dimensional components using filter banks, thereby de…