John H. Kalivas

发表

Adaption of simulated annealing to chemical optimization problems

John H. Kalivas, J. Kalivas, 1995 .

Introduction to special issue on penalty methods

John H. Kalivas, 2017 .

Selecting Factors for Partial Least Squares

John H. Kalivas, Nickey J. Messick, Patrick Lang, 1997 .

The use of chemical and physical properties for characterization of strontium distribution coefficients at the Idaho National Engineering and Environmental Laboratory, Idaho

John H. Kalivas, J. J. Rosentreter, Reinaldo G. Nieves, 1999 .

Multivariate Calibration Domain Adaptation with Unlabeled Data

John H. Kalivas, Robert C. Spiers, 2020 .

Sample and feature augmentation strategies for calibration updating

Erik Andries, John H. Kalivas, Anit Gurung, 2018, Journal of Chemometrics.

Harnessing Model Diversity and Prediction Similarity for Selecting Multivariate Calibration Tuning Parameters

John H. Kalivas, Robert C. Spiers, 2019 .

Graphical diagnostics for regression model determinations with consideration of the bias/variance trade-off

John H. Kalivas, Robert L. Green, J. Kalivas, 2002 .

Fundamentals of Calibration Transfer through Procrustes Analysis

John H. Kalivas, Chad E. Anderson, J. Kalivas, 1999 .

Data Fusion of Nonoptimized Models

John H. Kalivas, J. Kalivas, 2019, Data Handling in Science and Technology.

Chemometrics with undergraduates

John H. Kalivas, J. Kalivas, 1992 .

Regularization Adaption Processes for Multivariate Calibration Maintenance

Erik Andries, John H. Kalivas, Anit Gurung, 2017 .

Fine Tuning Model Updating for Multivariate Calibration Maintenance

Erik Andries, John H. Kalivas, Anit Gurung, 2017 .

Overview of two‐norm (L2) and one‐norm (L1) Tikhonov regularization variants for full wavelength or sparse spectral multivariate calibration models or maintenance

John H. Kalivas, J. Kalivas, John H. Kalivas, 2012 .

Progression of chemometrics in research supportive curricula : Preparing for the demands of society

John H. Kalivas, 2007 .

Examination of Criteria for Local Model Principal Component Regression

John H. Kalivas, Gregory A. Bakken, Dixie R. Long, 1997 .

Multivariate Calibration and Maintenance Using Principle Component Selection

John H. Kalivas, Trevor O'Loughlin, Parviz Shahbazikah, 2012 .

Comparison of extreme learning machine models for gasoline octane number forecasting by near-infrared spectra analysis

Xiaoyu Wang, Kan Yang, John H. Kalivas, 2020 .

Impact of standardization sample design on Tikhonov regularization variants for spectroscopic calibration maintenance and transfer

Erik Andries, John H. Kalivas, Joshua Ottaway, 2010 .

QSAR modeling based on the bias/variance compromise: a harmonious

John H. Kalivas, Joel B. Forrester, Heather A. Seipel, 2004, J. Comput. Aided Mol. Des..

Automatic food and beverage authentication and adulteration detection by classification hybrid fusion

John H. Kalivas, Tony Lemos, J. Kalivas, 2021, Journal of Chemometrics.

Author response for "Automatic food and beverage authentication and adulteration detection by classification hybrid fusion"

John H. Kalivas, Tony Lemos, 2021 .

Reliable Model Selection without Reference Values by Utilizing Model Diversity with Prediction Similarity

John H. Kalivas, Robert C. Spiers, 2021, J. Chem. Inf. Model..

Simulated‐annealing‐based optimization algorithms: Fundamentals and wavelength selection applications

John H. Kalivas, Uwe Hörchner, J. Kalivas, 1995 .

Tikhonov regularization in standardized and general form for multivariate calibration with application towards removing unwanted spectral artifacts

John H. Kalivas, Forrest Stout, 2006 .

3 Sampling Theory, Distribution Functions, and the Multivariate Normal Distribution

Paul J. Gemperline, John H. Kalivas, J. Kalivas, 2006 .

Leveraging Multiple Linear Regression for Wavelength Selection

John H. Kalivas, Tony Lemos, J. Kalivas, 2017 .

Spectral Multivariate Calibration with Wavelength Selection Using Variants of Tikhonov Regularization

Erik Andries, John H. Kalivas, Joshua Ottaway, 2010, Applied spectroscopy.

Optimization using variations of simulated annealing

John H. Kalivas, 1992 .

Convergence of generalized simulated annealing with variable step size with application towards parameter estimations of linear and nonlinear models

John H. Kalivas, Jon M. Sutter, J. Kalivas, 1991 .

Comparison of Forward Selection, Backward Elimination, and Generalized Simulated Annealing for Variable Selection

John H. Kalivas, J. Kalivas, J. Sutter, 1993 .

Evaluation of the calibration matrix condition number as a criterion for optimal derivative-spectrophotometric multicomponent quantitation

John H. Kalivas, J. Kalivas, L. L. Juhl, 1986 .

A consensus modeling approach to update a spectroscopic calibration

Parviz Shahbazikhah, John H. Kalivas, J. Kalivas, 2013 .

Cyclic Subspace Regression

John H. Kalivas, Reinaldo G. Nieves, J. Kalivas, 1998 .

Effective rank for multivariate calibration methods

John H. Kalivas, Heather A. Seipel, J. Kalivas, 2004 .

Which principal components to utilize for principal component regression

John H. Kalivas, Jon M. Sutter, J. Kalivas, 1992 .

Ridge regression optimization using a harmonious approach

John H. Kalivas, Joel B. Forrester, J. Kalivas, 2004 .

Evaluation of principal component selection methods to form a global prediction model by principal component regression

Yu-Long Xie, John H. Kalivas, J. Kalivas, 1997 .

Variance‐decomposition of pure‐component spectra as a measure of selectivity

John H. Kalivas, J. Kalivas, 1989 .

Quantifying selectivity in spectrophotometric multicomponent analysis

John H. Kalivas, Nicolaas M. Faber, N. M. Faber, 2003 .

Generalized simulated annealing for calibration sample selection from an existing set and orthogonalization of undesigned experiments

John H. Kalivas, J. Kalivas, 1991 .

Fusion strategies for selecting multiple tuning parameters for multivariate calibration and other penalty based processes: A model updating application for pharmaceutical analysis.

John H. Kalivas, Alexander J. White, J. Kalivas, 2016, Analytica chimica acta.

Multivariate Calibration, an Overview

John H. Kalivas, J. Kalivas, 2005 .

Cyclic subspace regression with analysis of wavelength-selection criteria

John H. Kalivas, Tracy P. Houghton, Gregory A. Bakken, 1999 .

Further investigation on a comparative study of simulated annealing and genetic algorithm for wavelength selection

John H. Kalivas, Uwe Hörchner, J. Kalivas, 1995 .

Global optimization by simulated annealing with wavelength selection for ultraviolet-visible spectrophotometry

John H. Kalivas, Jon M. Sutter, J. Kalivas, 1989 .

Interrelationships between sensitivity and selectivity measures for spectroscopic analysis

John H. Kalivas, J. Kalivas, P. Lang, 1996 .

Evaluation of Multivariate Calibration Using a Tikhonov Regularization Approach and the Generalized Pair‐Correlation Method with Nonlinear Data

John H. Kalivas, J. Kalivas, Forrest Stout, 2007 .

Pareto calibration with built-in wavelength selection

John H. Kalivas, J. Kalivas, 2004 .

Impartial graphical comparison of multivariate calibration methods and the harmony/parsimony tradeoff

John H. Kalivas, J. Kalivas, Forrest Stout, 2006 .

Learning from Procrustes analysis to improve multivariate calibration

John H. Kalivas, J. Kalivas, 2008 .

Post-Consumer Plastic Identification Using Raman Spectroscopy

John H. Kalivas, J. Kalivas, R. Rodriguez, 1999 .

Fundamentals of condition index evolving profiles for qualitative analysis of unresolved chromatographic peaks

John H. Kalivas, J. Kalivas, Taura D. Jarvis, 1992 .

Wavelength Selection Characterization for NIR Spectra

John H. Kalivas, Uwe Hörchner, J. Kalivas, 1997 .