| Support vector machine classification and validation of cancer tissue samples using microarray expression data TS Furey, N Cristianini, N Duffy, DW Bednarski, M Schummer, D Haussler Bioinformatics 16 (10), 906-914, 2000 | 3363 | 2000 |
| Evolving deep neural networks R Miikkulainen, J Liang, E Meyerson, A Rawal, D Fink, O Francon, B Raju, ... Artificial intelligence in the age of neural networks and brain computing …, 2024 | 1320 | 2024 |
| Convolution kernels for natural language M Collins, N Duffy Advances in neural information processing systems 14, 2001 | 1260 | 2001 |
| New ranking algorithms for parsing and tagging: Kernels over discrete structures, and the voted perceptron M Collins, N Duffy Proceedings of the 40th annual meeting of the association for computational …, 2002 | 736 | 2002 |
| Boosting methods for regression N Duffy, D Helmbold Machine Learning 47, 153-200, 2002 | 249 | 2002 |
| Real time context learning by software agents J Funge, R Musick, D Dobson, N Duffy, M McNally, X Tu, I Wright, W Yen, ... US Patent 7,296,007, 2007 | 202 | 2007 |
| Content embedding using deep metric learning algorithms P Tsatsin, PM Long, DGM Legrand, N Duffy US Patent 10,909,459, 2021 | 124 | 2021 |
| Query controlled behavior models as components of intelligent agents J Funge, R Musick, D Dobson, N Duffy, M McNally, X Tu, I Wright, W Yen, ... US Patent 7,636,701, 2009 | 86 | 2009 |
| Non-disruptive embedding of specialized elements J Funge, R Musick, D Dobson, N Duffy, M McNally, X Tu, I Wright, W Yen, ... US Patent 7,263,462, 2007 | 74 | 2007 |
| Artificial intelligence in the age of neural networks and brain computing R Miikkulainen, J Liang, E Meyerson, A Rawal, D Fink, O Francon, B Raju, ... Elsevier, 2019 | 71 | 2019 |
| Non-disruptive embedding of specialized elements J Funge, R Musick, D Dobson, N Duffy, M McNally, X Tu, I Wright, W Yen, ... US Patent 7,558,698, 2009 | 63 | 2009 |
| Potential boosters? N Duffy, D Helmbold Advances in neural information processing systems 12, 1999 | 60 | 1999 |
| Leveraging for Regression. N Duffy, DP Helmbold COLT, 208-219, 2000 | 48 | 2000 |
| Evolving deep neural networks (2017) R Miikkulainen, J Liang, E Meyerson, A Rawal, D Fink, O Francon, B Raju, ... arXiv preprint arXiv:1703.00548, 2017 | 46 | 2017 |
| A geometric approach to leveraging weak learners N Duffy, D Helmbold European conference on computational learning theory, 18-33, 1999 | 43 | 1999 |
| Methods for molecular property modeling using virtual data N Duffy, G Lanza, J Yu, W Mydlowec US Patent App. 11/074,587, 2005 | 36 | 2005 |
| Parsing with a single neuron: Convolution kernels for natural language problems M Collins, N Duffy | 33 | 2001 |
| Identification of new inhibitors of protein kinase R guided by statistical modeling R Bryk, K Wu, BC Raimundo, PE Boardman, P Chao, GL Conn, ... Bioorganic & medicinal chemistry letters 21 (13), 4108-4114, 2011 | 32 | 2011 |
| Connectionist symbol processing: Dead or alive? P Arun Neural Computing Surveys 2, 1-40, 1998 | 31 | 1998 |
| Machine learning based extraction of partition objects from electronic documents DG Tecuci, RKR Palla, HRM Nezhad, V Poon, NP Duffy, J Nipko US Patent 10,614,345, 2020 | 26 | 2020 |
Risto MiikkulainenProfessor of Computer Science, the University of Texas at AustinVerified email at cs.utexas.edu
