G. Wahba

Grace Wahba, G. Wahba, Yi Lin, 1999, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468).

Spatial-Temporal Analysis of Temperature Using Smoothing Spline ANOVA

Grace Wahba, G. Wahba, Zhen Luo, 1998 .

Using smoothing spline anova to examine the relation of risk factors to the incidence and progression of diabetic retinopathy.

G Wahba, G. Wahba, R. Klein, 1997, Statistics in medicine.

Getting better contour plots with S and GCVPACK

G. Wahba, D. Bates, F. M. Reames, 1993 .

Testing the (Parametric) Null Model Hypothesis in (Semiparametric) Partial and Generalized Spline Models

Grace Wahba, Dennis D. Cox, Brian S. Yandell, 1988 .

Inequality-Constrained Multivariate Smoothing Splines with Application to the Estimation of Posterior Probabilities

Grace Wahba, G. Wahba, M. A. Villalobos, 1987 .

THREE TOPICS IN ILL-POSED PROBLEMS

Grace Wahba, G. Wahba, 1987 .

Design Criteria and Eigensequence Plots for Satellite-Computed Tomography

Grace Wahba, G. Wahba, 1985 .

Multivariate thin plate spline estimates for the posterior probabilities in the classification problem

Grace Wahba, G. Wahba, M. A. Villalobos, 1983 .

Vector Splines on the Sphere, with Application to the Estimation of Vorticity and Divergence from Discrete, Noisy Data

Grace Wahba, G. Wahba, 1982 .

On the Minimization of a Quadratic Functional Subject to a Continuous Family of Linear Inequality Constraints

Grace Wahba, G. Wahba, 1973 .

A class of approximate solutions to linear operator equations

Grace Wahba, G. Wahba, 1973 .

The Asymptotic Behavior of the Nonlinear Estimators of the Diffusion Tensor and Tensor-Derived Quantities with Implications for Group Analysis

Andrew L. Alexander, Peter J. Basser, Grace Wahba, 2006 .

Dicussion on the meeting on ‘Statistical approaches to inverse problems’

Simon J. Godsill, Dan Cornford, Eric Moulines, 2004 .

An Averaging Method for the Stiff Highly Oscillatory Problem

G. Wahba, W. Miranker, 1976 .

Discussion: Projection Pursuit

Grace Wahba, G. Wahba, 1985 .

Soft Classiication, A. K. A. Risk Estimation, via Penalized Log Likelihood and Smoothing Spline Analysis of Variance

G. Wahba, Chong Gu, Yuedong Wang, 1993 .

Magnetic Resonance Image Segmentation with Thin Plate Spline Thresholding 1

G. Wahba, M. Chung, Xianhong Xie, 2006 .

Magnetic Resonance Image Segmentation with Thin Plate Spline

G. Wahba, M. Chung, Xianhong Xie, 2006 .

Smoothing Spline ANOVA for Exponential Families , with Application to theWisconsin Epidemiological Study of Diabetic Retinopathy 1 2

G. Wahba, B. Klein, WIYuedong Wang, 1995 .

On the Relation Between the GACV and Joachims’ ξα Method for Tuning Support Vector Machines, With Extensions to the Non-Standard Case

G. Wahba, Yi Lin, Yoonkyung Lee, 2001 .

8. Fredholm Integral Equations of the First Kind

Grace Wahba, G. Wahba, 1990 .

Spline Models for Observational Data

G. Wahba, 1990 .

Adaptive tuning, 4-D Var and representers in RKHS

G. Wahba, 2001 .

Generalized Approximate Cross Validation For Support Vector Machines, Or, Another Way To Look At Mar

Grace Wahba, G. Wahba, Yi Lin, 1999 .

Implications of Heterogeneous Variance of Tensor-Derived Quantities for Group Comparisons

G. Wahba, P. Basser, J. Carew, 2007 .

Approximate Regularized Solutions to Linear Operator Equations When the Data-Vector Is Not in the Range of the Operator.

G. Wahba, M. Nashed, 1973 .

5. Confidence Intervals

G. Wahba, 1990 .

An introduction to smoothing spline ANOVA models in RKHS, with examples in geographical data, medicine, atmospheric sciences and machine learning

G. Wahba, 2003, math/0410419.

Comment on "Support Vector Machines with Applications"

G. Wahba, 2006, math/0612822.

Smoothing Spline ANOVA for Exponential Families , with Application to theWisconsin Epidemiological Study of Diabetic Retinopathy 1 2

G. Wahba, B. Klein, WIYuedong Wang, 1995 .

2 What is an RKHS ?

G. Wahba, Yuedong Wang, 2019 .

Cloud Classification of Satellite Radiance Data by Multicategory Support Vector Machines

Steven A. Ackerman, Grace Wahba, Yoonkyung Lee, 2004, Journal of Atmospheric and Oceanic Technology.

Soft and hard classification by reproducing kernel Hilbert space methods

Grace Wahba, G. Wahba, 2002, Proceedings of the National Academy of Sciences of the United States of America.

On the Estimation of Functions of Several Variables from Aggregated Data.

Nira Dyn, Grace Wahba, G. Wahba, 1982 .

Some Results on Tchebychefian Spline Functions

G. Wahba, G. Kimeldorf, 1971 .

Adaptive tuning of numerical weather prediction models: Part I: randomized GCV and related methods i

Feng Gao, Donald R. Johnson, Grace Wahba, 1995 .

Constrained Regularization for Ill Posed Linear Operator Equations, with Applications in Meteorology and Medicine.

Grace Wahba, G. Wahba, 1982 .

A CORRESPONDENCE BETWEEN BAYESIAN ESTIMATION ON

Grace Wahba, George Kimeldorf, G. Wahba, 2016 .

Learning graph structure with parametric and non-parametric models

Grace Wahba, Shilin Ding, G. Wahba, 2012 .

Emanuel Parzen and a Tale of Two Kernels

G. Wahba, 2017 .

Grace Wahba, G. Wahba, 2011 .

The ( Nonstandard ) Multicategory Suport Vector Machine , with Application to Classification of Satellite-Observed Radiance Profiles

G. Wahba, 2022 .

Some Tests of Independence for Stationary Multivariate Time Series

Grace Wahba, G. Wahba, 1971 .

Optimal spline smoothing of fMRI time series by generalized cross-validation

Xianhong Xie, Grace Wahba, John D. Carew, 2003, NeuroImage.

Soft Classification, a. k. a. Risk Estimation, via Penalized Log Likelihood and Smoothing Spline Ana

Chong Gu, Grace Wahba, Yuedong Wang, 1993 .

Structured Machine Learning for Soft Classification with Smoothing Spline ANOVA and Stacked Tuning, Testing, and Evaluation

Chong Gu, Grace Wahba, Ronald Klein, 1993, NIPS.

Minimizing GCV/GML Scores with Multiple Smoothing Parameters via the Newton Method

Chong Gu, Grace Wahba, G. Wahba, 1991, SIAM J. Sci. Comput..

A cross validated bayesian retrieval algorithm for nonlinear remote sensing experiments

Grace Wahba, Finbarr O'Sullivan, G. Wahba, 1985 .

Partial Spline Models for the Inclusion of Tropopause and Frontal Boundary Information in Otherwise Smooth Two- and Three-Dimensional Objective Analysis

Grace Wahba, G. Wahba, Donald R. Johnson, 1986 .

Histosplines with Knots Which are Order Statistics

Grace Wahba, G. Wahba, 1976 .

Smoothing Splines

Grace Wahba, G. Wahba, 2011, International Encyclopedia of Statistical Science.

Learning Higher-Order Graph Structure with Features by Structure Penalty

Xiaojin Zhu, Grace Wahba, Shilin Ding, 2011, NIPS.

A Polynomial Algorithm for Density Estimation

Grace Wahba, G. Wahba, 1971 .

Parameter estimation in linear dynamic systems

Grace Wahba, G. Wahba, 1980 .

Multicategory Support Vector Machines, Theory, and Application to the Classiﬁcation of Microarray Data and Satellite Radiance Data

G. Wahba, Yi Lin, Yoonkyung Lee, 2002 .

Inaugural Article: Soft and hard classification by reproducing kernel Hilbert space methods

G. Wahba, 2002 .

Discussion: Linear Smoothers and Additive Models

Chong Gu, Grace Wahba, Zehua Chen, 1989 .

Rates of convergence of some estimators for a semiparametric model

G. Wahba, J. Shiau, 1988 .

4. Estimating the Smoothing Parameter

Grace Wahba, G. Wahba, 1990 .

Magnetic Resonance Image Segmentation with Thin Plate Spline Thresholding

Moo K. Chung, Xianhong Xie, Grace Wahba, 2006 .

On the dynamic estimation of relative weights for observation and forecast in numerical weather prediction

G. Wahba, A. Deepak, 1988 .

A New Approach to the Numerical Evaluation of the Inverse Radon Transform with Discrete, Noisy Data

G. Wahba, 1981 .

Estimation of the Coefficients in a Multidimensional Distributed Lag Model

G. Wahba, 1969 .

[A Statistical Perspective on Ill-Posed Inverse Problems]: Comment

G. Wahba, 1986 .

Statistical Decision Theory and Related Topics III

Grace Wahba, G. Wahba, 1982 .

On the optimal choice of nodes in the collocation-projection method for solving linear operator equations

G. Wahba, 1976 .