On the adaptive and continuous information problems. - Mark A. Kon; Erich Novak (J. Complex., 1989)

On linearity of spline algorithms. - Mark A. Kon; Roberto Tempo (J. Complex., 1989)

On the Almost Sure Limit of Probabilistic Recovery. - Mark A. Kon (Curves and Surfaces, 1991)

On the average case solvability of III-posed problems. - Mark A. Kon; Klaus Ritter 001; Arthur G. Werschulz (J. Complex., 1991)

Linearity of algorithms and a result of Ando. - Mark A. Kon; Roberto Tempo (J. Complex., 1991)

On the delta->0 Limit in Probabilistic Complexity. - Mark A. Kon (J. Complex., 1994)

Information complexity of neural networks. - Mark A. Kon; Leszek Plaskota (Neural Networks, 2000)

Complexity of Neural Network Approximation with Limited Information: A Worst Case Approach. - Mark A. Kon; Leszek Plaskota (J. Complex., 2001)

Statistical Likelihood Representations of Prior Knowledge in Machine Learning. - Mark A. Kon; Leszek Plaskota; Andrzej W. Przybyszewski (Artificial Intelligence and Applications, 2005)

Machine Learning and Statistical MAP Methods. - Mark A. Kon; Leszek Plaskota; Andrzej W. Przybyszewski (Intelligent Information Systems, 2005)

Information-based nonlinear approximation: an average case setting. - Mark A. Kon; Leszek Plaskota (J. Complex., 2005)

Machine learning methods for transcription data integration. - Dustin T. Holloway; Mark A. Kon; Charles DeLisi (IBM J. Res. Dev., 2006)

SVMotif: A Machine Learning Motif Algorithm. - Mark A. Kon; Yue Fan; Dustin T. Holloway; Charles DeLisi (ICMLA, 2007)

Learning Methods for DNA Binding in Computational Biology. - Mark A. Kon; Dustin T. Holloway; Yue Fan; Chaitanya Sai; Charles DeLisi (IJCNN, 2007)

Ensemble Machine Methods for DNA Binding. - Yue Fan; Mark A. Kon; Charles DeLisi (ICMLA, 2008)

Smoothing Gene Expression Using Biological Networks. - Yue Fan; Mark A. Kon; Shinuk Kim; Charles DeLisi (ICMLA, 2010)

Empirical Normalization for Quadratic Discriminant Analysis and Classifying Cancer Subtypes. - Mark A. Kon; Nikolay Nikolaev (ICMLA (2), 2011)

Top Scoring Pairs for Feature Selection in Machine Learning and Applications to Cancer Outcome Prediction. - Ping Shi; Surajit Ray; Qifu Zhu; Mark A. Kon (BMC Bioinform., 2011)

On Some Integrated Approaches to Inference - Mark A. Kon; Leszek Plaskota (CoRR, 2012)

Computational methods for cancer survival classification using intermediate information. - Shinuk Kim; Taesung Park; Mark A. Kon (IWBBIO, 2013)

Data Mining and Machine Learning on the Basis from Reflexive Eye Movements Can Predict Symptom Development in Individual Parkinson's Patients. - Andrzej W. Przybyszewski; Mark A. Kon; Stanislaw Szlufik; Justyna Dutkiewicz; Piotr Habela; Dariusz M. Koziorowski (MICAI (2), 2014)

Cancer survival classification using integrated data sets and intermediate information. - Shinuk Kim; Taesung Park; Mark A. Kon (Artif. Intell. Medicine, 2014)

Class Discovery via Bimodal Feature Selection in Unsupervised Settings. - Jessica Curtis; Mark A. Kon (ICMLA, 2015)

On Relating Interpolatory Wavelets to Interpolatory Scaling Functions in Multiresolution Analyses. - Zhiguo Zhang 002; Mark A. Kon (Circuits Syst. Signal Process., 2015)

Some comparisons of gene expression classifiers. - Shinuk Kim; Mark A. Kon; Hyowon Lee 003 (BIBM, 2016)

Differentiation and Integration of Machine Learning Feature Vectors. - Xinying Mu; Ana Brândusa Pavel; Mark A. Kon (ICMLA, 2016)

Multimodal Learning and Intelligent Prediction of Symptom Development in Individual Parkinson's Patients. - Andrzej W. Przybyszewski; Mark A. Kon; Stanislaw Szlufik; Artur Szymanski; Piotr Habela; Dariusz M. Koziorowski (Sensors, 2016)

Comparisons of cancer classifiers based on RNA_seq and miRNA_seq. - Shinuk Kim; Hyowon Lee 003; Mark A. Kon (Int. J. Data Min. Bioinform., 2017)

Wavelet sampling and generalization in neural networks. - Zhiguo Zhang 002; Mark A. Kon (Neurocomputing, 2017)

Absorption probabilities of quantum walks. - Parker Kuklinski; Mark A. Kon (Quantum Inf. Process., 2018)

Bifurcation Curves of Two-Dimensional Quantum Walks. - Parker Kuklinski; Mark A. Kon (CoRR, 2019)

Analytic regularity and stochastic collocation of high-dimensional Newton iterates. - Julio Enrique Castrillón-Candás; Mark A. Kon (Adv. Comput. Math., 2020)

Interpolatory filter banks and interpolatory wavelet packets. - Zhiguo Zhang 002; Mark A. Kon (J. Comput. Appl. Math., 2020)

General methods and properties to evaluate continuum limits of the 1D discrete time quantum walk. - Michael Manighalam; Mark A. Kon (Quantum Inf. Process., 2020)

Existence of Strong Solution for the Complexified Non-linear Poisson Boltzmann Equation. - Brian Choi; Jie Xu 018; Trevor Norton; Mark A. Kon; Julio Enrique Castrillón-Candás (CoRR, 2021)

Stochastic functional analysis with applications to robust machine learning. - Julio Enrique Castrillón-Candás; Dingning Liu; Mark A. Kon (CoRR, 2021)

Wavelet matrix operations and quantum transforms. - Zhiguo Zhang 002; Mark A. Kon (Appl. Math. Comput., 2022)

Stochastic Functional Analysis and Multilevel Vector Field Anomaly Detection. - Julio Enrique Castrillón-Candás; Mark A. Kon (CoRR, 2022)

Coupled VAE: Improved Accuracy and Robustness of a Variational Autoencoder. - Shichen Cao; Jingjing Li; Kenric P. Nelson; Mark A. Kon (Entropy, 2022)

Anomaly detection: A functional analysis perspective. - Julio Enrique Castrillón-Candás; Mark A. Kon (J. Multivar. Anal., 2022)

Analytic regularity of strong solutions for the complexified stochastic non-linear Poisson Boltzmann Equation. - Brian Choi; Jie Xu 018; Trevor Norton; Mark A. Kon; Julio Enrique Castrillón-Candás (CoRR, 2023)

Uncertainty quantification and complex analyticity of the nonlinear Poisson-Boltzmann equation for the interface problem with random domains. - Trevor Norton; Jie Xu 018; Brian Choi; Mark A. Kon; Julio Enrique Castrillón-Candás (CoRR, 2023)

Feature Network Methods in Machine Learning and Applications. - Xinying Mu; Mark A. Kon (CoRR, 2024)

Multilevel Stochastic Optimization for Imputation in Massive Medical Data Records. - Wenrui Li; Xiaoyu Wang; Yuetian Sun; Snezana Milanovic; Mark A. Kon; Julio Enrique Castrillón-Candás (IEEE Trans. Big Data, 2024)

deFOREST: Fusing Optical and Radar satellite data for Enhanced Sensing of Tree-loss. - Julio Enrique Castrillón-Candás; Hanfeng Gu; Caleb Meredith; Yulin Li; Xiaojing Tang; Pontus Olofsson; Mark Kon (CoRR, 2025)

FINDER: Feature Inference on Noisy Datasets using Eigenspace Residuals. - Trajan Murphy; Akshunna S. Dogra; Hanfeng Gu; Caleb Meredith; Mark Kon; Julio Enrique Castrillion-Candas (CoRR, 2025)