Large Language Models: A Deep Dive - Bridging Theory and Practice

Uday Kamath Uday Kamath Kevin Keenan Garrett Somers Sarah Sorenson Large Language Models: A Deep Dive - Bridging Theory and Practice Springer 2024 1-472 978-3-031-65646-0 https://doi.org/10.1007/978-3-031-65647-7 Uday Kamath John Liu Explainable Artificial Intelligence: An Introduction to Interpretable Machine Learning, 2 Springer 2021 1-310 978-3-030-83355-8 https://doi.org/10.1007/978-3-030-83356-5 Vedant Vajre Mitchell Naylor Uday Kamath Amarda Shehu PsychBERT: A Mental Health Language Model for Social Media Mental Health Behavioral Analysis. 1077-1082 2021 BIBM https://doi.org/10.1109/BIBM52615.2021.9669469 conf/bibm/2021 db/conf/bibm/bibm2021.html#VajreNKS21

Mitchell Naylor Christi French Samantha Terker Uday Kamath Quantifying Explainability in NLP and Analyzing Algorithms for Performance-Explainability Tradeoff. 2021 abs/2107.05693 CoRR https://arxiv.org/abs/2107.05693 db/journals/corr/corr2107.html#abs-2107-05693

Uday Kamath John Liu James Whitaker Deep Learning for NLP and Speech Recognition Springer 2019 1-621 978-3-030-14595-8 https://doi.org/10.1007/978-3-030-14596-5

Yazhou Ren 0001 Uday Kamath Carlotta Domeniconi Zenglin Xu Parallel boosted clustering. 87-100 2019 351 Neurocomputing https://doi.org/10.1016/j.neucom.2019.04.003 db/journals/ijon/ijon351.html#RenKDX19

Uday Kamath Carlotta Domeniconi Amarda Shehu Kenneth A. De Jong EML: A Scalable, Transparent Meta-Learning Paradigm for Big Data Applications. 35-59 2019 Innovations in Big Data Mining and Embedded Knowledge https://doi.org/10.1007/978-3-030-15939-9_3 series/isrl/159 db/series/isrl/isrl159.html#KamathDSJ19

Daniel Veltri Uday Kamath Amarda Shehu Deep learning improves antimicrobial peptide recognition. 2740-2747 2018 34 Bioinform. 16 https://doi.org/10.1093/bioinformatics/bty179 https://www.wikidata.org/entity/Q52625530 db/journals/bioinformatics/bioinformatics34.html#VeltriKS18

Uday Kamath Carlotta Domeniconi Kenneth A. De Jong Theoretical and Empirical Analysis of a Spatial EA Parallel Boosting Algorithm. 2018 26 Evol. Comput. 1 https://doi.org/10.1162/evco_a_00202 https://www.wikidata.org/entity/Q39095236 db/journals/ec/ec26.html#KamathDJ18

Daniel Veltri Uday Kamath Amarda Shehu Improving Recognition of Antimicrobial Peptides and Target Selectivity through Machine Learning and Genetic Programming. 300-313 2017 14 IEEE ACM Trans. Comput. Biol. Bioinform. 2 https://doi.org/10.1109/TCBB.2015.2462364 https://doi.ieeecomputersociety.org/10.1109/TCBB.2015.2462364 https://dl.acm.org/doi/10.1109/TCBB.2015.2462364 https://www.wikidata.org/entity/Q45947862 db/journals/tcbb/tcbb14.html#VeltriKS17

Uday Kamath Carlotta Domeniconi Kenneth A. De Jong Theoretical and Empirical Analysis of a Parallel Boosting Algorithm. 2015 abs/1508.01549 CoRR http://arxiv.org/abs/1508.01549 db/journals/corr/corr1508.html#KamathDJ15

Daniel Veltri Uday Kamath Amarda Shehu A novel method to improve recognition of antimicrobial peptides through distal sequence-based features. 371-378 2014 BIBM https://doi.org/10.1109/BIBM.2014.6999187 https://doi.ieeecomputersociety.org/10.1109/BIBM.2014.6999187 conf/bibm/2014 db/conf/bibm/bibm2014.html#VeltriKS14 Uday Kamath Jessica Lin 0001 Kenneth A. De Jong SAX-EFG: an evolutionary feature generation framework for time series classification. 533-540 2014 GECCO https://doi.org/10.1145/2576768.2598321 conf/gecco/2014 db/conf/gecco/gecco2014.html#KamathLJ14 Ya-Zhou Ren 0001 Uday Kamath Carlotta Domeniconi Guoji Zhang Boosted Mean Shift Clustering. 646-661 2014 ECML/PKDD (2) https://doi.org/10.1007/978-3-662-44851-9_41 conf/pkdd/2014-2 db/conf/pkdd/pkdd2014-2.html#RenKDZ14 Uday Kamath Carlotta Domeniconi Kenneth A. De Jong An analysis of a spatial EA parallel boosting algorithm. 1053-1060 2013 GECCO https://doi.org/10.1145/2463372.2463503 conf/gecco/2013 db/conf/gecco/gecco2013.html#KamathDJ13

Uday Kamath Jack Compton Rezarta Islamaj Dogan Kenneth A. De Jong Amarda Shehu An Evolutionary Algorithm Approach for Feature Generation from Sequence Data and Its Application to DNA Splice Site Prediction. 1387-1398 2012 9 IEEE ACM Trans. Comput. Biol. Bioinform. 5 https://doi.org/10.1109/TCBB.2012.53 https://doi.ieeecomputersociety.org/10.1109/TCBB.2012.53 https://dl.acm.org/doi/10.1109/TCBB.2012.53 https://www.wikidata.org/entity/Q34234782 db/journals/tcbb/tcbb9.html#KamathCDJS12

Jeffrey K. Bassett Uday Kamath Kenneth A. De Jong A new methodology for the GP theory toolbox. 719-726 2012 GECCO https://doi.org/10.1145/2330163.2330264 conf/gecco/2012 db/conf/gecco/gecco2012.html#BassettKJ12 Uday Kamath Johan Kaers Amarda Shehu Kenneth A. De Jong A Spatial EA Framework for Parallelizing Machine Learning Methods. 206-215 2012 PPSN (1) https://doi.org/10.1007/978-3-642-32937-1_21 conf/ppsn/2012-1 db/conf/ppsn/ppsn2012-1.html#KamathKSJ12

Uday Kamath Amarda Shehu Kenneth A. De Jong A Two-Stage Evolutionary Approach for Effective Classification of hypersensitive DNA Sequences. 399-413 2011 9 J. Bioinform. Comput. Biol. 3 https://doi.org/10.1142/S0219720011005586 https://www.wikidata.org/entity/Q44967267 db/journals/jbcb/jbcb9.html#KamathSJ11

Uday Kamath Kenneth A. De Jong Amarda Shehu An evolutionary-based approach for feature generation: Eukaryotic promoter recognition. 277-284 2011 IEEE Congress on Evolutionary Computation https://doi.org/10.1109/CEC.2011.5949629 https://www.wikidata.org/entity/Q58449218 conf/cec/2011 db/conf/cec/cec2011.html#KamathJS11 Uday Kamath Amarda Shehu Kenneth A. De Jong Feature and Kernel Evolution for Recognition of Hypersensitive Sites in DNA Sequences. 213-228 2010 BIONETICS https://doi.org/10.1007/978-3-642-32615-8_23 http://eudl.eu/doi/10.1007/978-3-642-32615-8_23 https://www.wikidata.org/entity/Q58449174 conf/bionetics/2010 db/conf/bionetics/bionetics2010.html#KamathSJ10 Uday Kamath Amarda Shehu Kenneth A. De Jong Using evolutionary computation to improve SVM classification. 1-8 2010 IEEE Congress on Evolutionary Computation https://doi.org/10.1109/CEC.2010.5586432 https://www.wikidata.org/entity/Q58449272 conf/cec/2010 db/conf/cec/cec2010.html#KamathSJ10 Uday Kamath Kenneth A. De Jong Amarda Shehu Selecting predictive features for recognition of hypersensitive sites of regulatory genomic sequences with an evolutionary algorithm. 179-186 2010 GECCO https://doi.org/10.1145/1830483.1830516 https://www.wikidata.org/entity/Q58449179 conf/gecco/2010 db/conf/gecco/gecco2010.html#KamathJS10 Uday Kamath Self-Learning Expert Systems using Rule Classifier in Detection Engines. 224-227 2008 Artificial Intelligence and Pattern Recognition conf/aiprf/2008 db/conf/aiprf/aipr2008.html#Kamath08 Jeffrey K. Bassett Jack Compton Rezarta Islamaj Dogan Carlotta Domeniconi Christi French Kenneth A. De Jong Johan Kaers Kevin Keenan Jessica Lin 0001 John Liu Mitchell Naylor Yazhou Ren 0001Ya-Zhou Ren 0001 Amarda Shehu Garrett Somers Sarah Sorenson Samantha Terker Vedant Vajre Daniel Veltri James Whitaker Zenglin Xu Guoji Zhang