Uday Kamath

发表

Theoretical and Empirical Analysis of a Spatial EA Parallel Boosting Algorithm

Kenneth A. De Jong, Uday Kamath, Carlotta Domeniconi, 2016, Evolutionary Computation.

An analysis of a spatial EA parallel boosting algorithm

Kenneth A. De Jong, Uday Kamath, Carlotta Domeniconi, 2013, GECCO '13.

Selecting predictive features for recognition of hypersensitive sites of regulatory genomic sequences with an evolutionary algorithm

Kenneth A. De Jong, Amarda Shehu, Uday Kamath, 2010, GECCO '10.

Using Quantitative Genetics and Phenotypic Traits in Genetic Programming

Uday Kamath, Kenneth de Jong, Jeffrey K. Bassett, 2012 .

An Evolutionary Algorithm Approach for Feature Generation from Sequence Data and Its Application to DNA Splice Site Prediction

Kenneth A. De Jong, Amarda Shehu, Uday Kamath, 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

A Spatial EA Framework for Parallelizing Machine Learning Methods

Kenneth A. De Jong, Amarda Shehu, Uday Kamath, 2012, PPSN.

Feature and Kernel Evolution for Recognition of Hypersensitive Sites in DNA Sequences

Kenneth A. De Jong, Amarda Shehu, Uday Kamath, 2010, BIONETICS.

Basics of Deep Learning

John Liu, Uday Kamath, James Whitaker, 2019, Deep Learning for NLP and Speech Recognition.

An evolutionary-based approach for feature generation: Eukaryotic promoter recognition

Kenneth A. De Jong, Amarda Shehu, Uday Kamath, 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

Convolutional Neural Networks

John Liu, Uday Kamath, James Whitaker, 2019, Deep Learning for NLP and Speech Recognition.

Text and Speech Basics

Uday Kamath, James Whitaker, John Liu, 2019, Deep Learning for NLP and Speech Recognition.

Improving Recognition of Antimicrobial Peptides and Target Selectivity through Machine Learning and Genetic Programming

Amarda Shehu, Uday Kamath, Daniel Veltri, 2017, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Deep Reinforcement Learning for Text and Speech

Uday Kamath, James Whitaker, John Liu, 2019 .

Self-Learning Expert Systems using Rule Classifier in Detection Engines

Uday Kamath, 2008, Artificial Intelligence and Pattern Recognition.

EML: A Scalable, Transparent Meta-Learning Paradigm for Big Data Applications

Kenneth A. De Jong, Amarda Shehu, Uday Kamath, 2019, Innovations in Big Data Mining and Embedded Knowledge.

Attention and Memory Augmented Networks

Uday Kamath, James Whitaker, John Liu, 2019, Deep Learning for NLP and Speech Recognition.

Using evolutionary computation to improve SVM classification

Kenneth A. De Jong, Amarda Shehu, Uday Kamath, 2010, IEEE Congress on Evolutionary Computation.

Theoretical and Empirical Analysis of a Parallel Boosting Algorithm pdf

Kenneth A. De Jong, Uday Kamath, Carlotta Domeniconi, 2015, ArXiv.

Mastering Java Machine Learning

Uday Kamath, Carlotta Domeniconi, Krishna Choppella, 2017 .

Parallel boosted clustering

Zenglin Xu, Uday Kamath, Carlotta Domeniconi, 2019, Neurocomputing.

Deep learning improves antimicrobial peptide recognition

Amarda Shehu, Uday Kamath, Daniel Veltri, 2018, Bioinform..

Transfer Learning: Scenarios, Self-Taught Learning, and Multitask Learning

Uday Kamath, James Whitaker, John Liu, 2019, Deep Learning for NLP and Speech Recognition.

End-to-End Speech Recognition

John Liu, Uday Kamath, James Whitaker, 2019, Deep Learning for NLP and Speech Recognition.

SAX-EFG: an evolutionary feature generation framework for time series classification

Jessica Lin, Kenneth A. De Jong, Uday Kamath, 2014, GECCO.

A Two-Stage Evolutionary Approach for Effective Classification of hypersensitive DNA Sequences

Kenneth A. De Jong, Amarda Shehu, Uday Kamath, 2011, J. Bioinform. Comput. Biol..

A novel method to improve recognition of antimicrobial peptides through distal sequence-based features

Amarda Shehu, Uday Kamath, Daniel Veltri, 2014, 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Transfer Learning: Domain Adaptation

Uday Kamath, James Whitaker, John Liu, 2019, Deep Learning for NLP and Speech Recognition.

Boosted Mean Shift Clustering

Uday Kamath, Carlotta Domeniconi, Guoji Zhang, 2014, ECML/PKDD.

A new methodology for the GP theory toolbox

Kenneth A. De Jong, Uday Kamath, Jeffrey K. Bassett, 2012, GECCO '12.

Deep Learning for NLP and Speech Recognition

John Liu, Uday Kamath, James Whitaker, 2020, Springer International Publishing.

Quantifying Explainability in NLP and Analyzing Algorithms for Performance-Explainability Tradeoff pdf

Uday Kamath, Christi French, Mitchell Naylor, 2021, ArXiv.

Explainable Artificial Intelligence: An Introduction to Interpretable Machine Learning

Uday Kamath, John Liu, Uday Kamath, 2021 .