Results 41 to 50 of about 163,423 (274)

Smoothing ADMM for Sparse-Penalized Quantile Regression With Non-Convex Penalties

IEEE Open Journal of Signal Processing
This paper investigates quantile regression in the presence of non-convex and non-smooth sparse penalties, such as the minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD).
Reza Mirzaeifard, Naveen K. D. Venkategowda, Vinay Chakravarthi Gogineni, Stefan Werner   +3 more
doaj   +1 more source

The Floor‐Ceiling‐Chip, or 2 × 2D = Pseudo‐3D—Approaching 3D Cell Morphology and Organization between Two Opposing 2D Substrates with Cell‐Adhesive Protein Micropatterns

Advanced Healthcare Materials, EarlyView.
Here, we present a novel 3D cell patterning and culture platform. The “Floor‐Ceiling‐Chip” (FC‐Chip) consists of two opposing track‐etched membranes, creating a pseudo‐3D microenvironment for the cells in between. By providing the membranes with micropatterned cell‐adhesive islands of varying geometries and sizes, the FC‐Chip enables control over cell ...
Urandelger Tuvshindorj, Francesca Giacomini, Esra Güben Kaçmaz, Tim ten Brink, Lorenzo Moroni, Zeinab Tahmasebi Birgani, Clemens van Blitterswijk, Pamela Habibović, Stefan Giselbrecht, Jan de Boer, Roman Truckenmüller   +10 more
wiley   +1 more source

Optimal resource allocation: Convex quantile regression approach

European Journal of Operational Research
Optimal allocation of resources across sub-units in the context of centralized decision-making systems such as bank branches or supermarket chains is a classical application of operations research and management science. In this paper, we develop quantile allocation models to examine how much the output and productivity could potentially increase if ...
Sheng Dai, Natalia Kuosmanen, Timo Kuosmanen, Juuso Liesiö   +3 more
openaire   +3 more sources

Consistency of Penalized Convex Regression

International Journal of Statistics and Probability, 2020
We consider the problem of estimating an unknown convex function f_* (0, 1)^d →R from data (X1, Y1), … (X_n; Y_n).A simple approach is finding a convex function that is the closest to the data points by minimizing the sum of squared errors over all convex functions. The convex regression estimator, which is computed this way, su ers
openaire   +2 more sources

Eccentric hyperbola: A new modified cutaneous scar re-excision on convex surfaces

Journal of Dermatology and Dermatologic Surgery, 2018
“Re-excision of scar” is a common procedure following diagnostic or therapeutic excision of skin cancer cutaneous lesions. With the conventional techniques, skin tension on convex surfaces results in deformity and elongated scars.
Georgios Pafitanis, Michalis Hadliandreou, Onur Gilleard, Graeme Moir   +3 more
doaj   +1 more source

Convex Least Angle Regression Based LASSO Feature Selection and Swish Activation Function Model for Startup Survival Rate

Cybernetics and Information Technologies, 2023
A startup is a recently established business venture led by entrepreneurs, to create and offer new products or services. The discovery of promising startups is a challenging task for creditors, policymakers, and investors. Therefore, the startup survival
Allu Ramakrishna, Padmanabhuni Venkata Nageswara Rao   +1 more
doaj   +1 more source

Mapping Nanoscale Protein‐Corona Kinetics of DoE‐Optimized Perfluorocarbon Encapsulated‐PLGA Nanoparticles by In Situ, Time‐Resolved Synchrotron SAXS

Advanced Healthcare Materials, EarlyView.
A two‐phase workflow (OFAT screening followed by central composite design) maps how processing variables tune PFCE‐PLGA nanoparticle size, dispersity, surface charge, loading, and 19F‐MRI signal. In situ, time‐resolved synchrotron SAXS tracks albumin‐corona growth on intact dispersions and reveals PFCE‐dependent adsorption pathways.
Joice Maria Joseph, Maria Rosa Gigliobianco, Cristina Minnelli, Paolo Moretti, Francesco Spinozzi, Giovanna Mobbili, Sara Pistolesi, Cristina Casadidio, Gabriella Teti, Roberta Censi, Stefano Antonio Gattone, Piera Di Martino   +11 more
wiley   +1 more source

Convex relaxation of mixture regression with efficient algorithms [PDF]

, 2009
We develop a convex relaxation of maximum a posteriori estimation of a mixture of regression models. Although our relaxation involves a semidefinite matrix variable, we reformulate the problem to eliminate the need for general semidefinite programming ...
,, Caetano, TS, Lim, J, Quadrianto, N, Schuurmans, D   +4 more
core   +2 more sources

Scaled Sparse Linear Regression

, 2012
Scaled sparse linear regression jointly estimates the regression coefficients and noise level in a linear model. It chooses an equilibrium with a sparse regression method by iteratively estimating the noise level via the mean residual square and scaling ...
Sun, Tingni, Zhang, Cun-Hui
core   +1 more source

Adaptive Sampling for Convex Regression

, 2018
In this paper, we introduce the first principled adaptive-sampling procedure for learning a convex function in the $L_\infty$ norm, a problem that arises often in the behavioral and social sciences. We present a function-specific measure of complexity and use it to prove that, for each convex function $f_{\star}$, our algorithm nearly attains the ...
Simchowitz, Max, Jamieson, Kevin, Suchow, Jordan W., Griffiths, Thomas L.   +3 more
openaire   +2 more sources