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ORCIDUlisses Braga-Neto
Ulisses M. Braga-Neto – Ulisses de Mendonça Braga Neto
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- affiliation: Texas A&M University, College Station, TX, USA
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2020 – today
- 2024
[j72]Sambandh Bhusan Dhal
, Stavros Kalafatis, Ulisses Braga-Neto, Krishna Chaitanya Gadepally, Jose Luis Landivar-Scott, Lei Zhao, Kevin J. Nowka, Juan Landivar, Pankaj Pal, Mahendra Bhandari:
Testing the Performance of LSTM and ARIMA Models for In-Season Forecasting of Canopy Cover (CC) in Cotton Crops. Remote. Sens. 16(11): 1906 (2024)- [j71]Pappu Kumar Yadav, J. Alex Thomasson, Robert G. Hardin, Stephen W. Searcy, Ulisses Braga-Neto, Sorin C. Popescu, Roberto Rodriguez, Daniel E. Martin, Juan Enciso:
AI-Driven Computer Vision Detection of Cotton in Corn Fields Using UAS Remote Sensing Data and Spot-Spray Application. Remote. Sens. 16(15): 2754 (2024) - [i19]Ming Zhong, Dehao Liu, Raymundo Arróyave, Ulisses Braga-Neto:
Label Propagation Training Schemes for Physics-Informed Neural Networks and Gaussian Processes. CoRR abs/2404.05817 (2024) - [i18]Baoli Hao, Ulisses Braga-Neto, Chun Liu, Lifan Wang, Ming Zhong:
Structure Preserving PINN for Solving Time Dependent PDEs with Periodic Boundary. CoRR abs/2404.16189 (2024) - 2023
- [j70]Pappu Kumar Yadav, J. Alex Thomasson, Robert G. Hardin, Stephen W. Searcy, Ulisses Braga-Neto, Sorin C. Popescu, Daniel E. Martin, Roberto Rodriguez, Karem Meza, Juan Enciso, Jorge Solorzano Diaz, Tianyi Wang:
Detecting volunteer cotton plants in a corn field with deep learning on UAV remote-sensing imagery. Comput. Electron. Agric. 204: 107551 (2023) - [j69]Levi D. McClenny, Ulisses M. Braga-Neto:
Self-adaptive physics-informed neural networks. J. Comput. Phys. 474: 111722 (2023) - [j68]Emilio Jose Rocha Coutinho, Marcelo Dall'Aqua, Levi D. McClenny, Ming Zhong, Ulisses Braga-Neto, Eduardo Gildin:
Physics-informed neural networks with adaptive localized artificial viscosity. J. Comput. Phys. 489: 112265 (2023) - [j67]Rodrigo Capobianco Guido, Tülay Adali, Emil Björnson, Laure Blanc-Féraud, Ulisses Braga-Neto, Behnaz Ghoraani, Christian Jutten, Alle-Jan van der Veen, Hong Vicky Zhao, Xiaoxiang Zhu:
IEEE Signal Processing Society: Celebrating 75 Years of Remarkable Achievements [From the Guest Editors]. IEEE Signal Process. Mag. 40(4): 3-6 (2023) - [j66]Rodrigo Capobianco Guido, Tülay Adali, Emil Björnson, Laure Blanc-Féraud, Ulisses Braga-Neto, Behnaz Ghoraani, Christian Jutten, Alle-Jan van der Veen, Hong Vicky Zhao, Xiaoxiang Zhu:
IEEE Signal Processing Society: Celebrating 75 Years of Remarkable Achievements (Part 2) [From the Guest Editors]. IEEE Signal Process. Mag. 40(5): 8-11 (2023) - [c48]Parisa Ghane, Ulisses Braga-Neto:
Predicting Generalization in Deep Learning Using Data Augmentation and posterior Probability Estimators. MLSP 2023: 1-6 - 2022
- [j65]Parisa Ghane, Ulisses Braga-Neto:
Generalized Resubstitution for Classification Error Estimation. J. Mach. Learn. Res. 23: 280:1-280:30 (2022) - [j64]Sambandh Bhusan Dhal, Kyle Jungbluth, Raymond Lin, Seyed Pouyan Sabahi, Muthukumar Bagavathiannan, Ulisses Braga-Neto, Stavros Kalafatis:
A Machine-Learning-Based IoT System for Optimizing Nutrient Supply in Commercial Aquaponic Operations. Sensors 22(9): 3510 (2022) - [j63]Yukun Tan, Fernando B. Lima Neto, Ulisses M. Braga-Neto:
PALLAS: Penalized mAximum LikeLihood and pArticle Swarms for Inference of Gene Regulatory Networks From Time Series Data. IEEE ACM Trans. Comput. Biol. Bioinform. 19(3): 1807-1816 (2022) - [i17]Caio Davi, Ulisses M. Braga-Neto:
PSO-PINN: Physics-Informed Neural Networks Trained with Particle Swarm Optimization. CoRR abs/2202.01943 (2022) - [i16]Emilio Jose Rocha Coutinho, Marcelo Dall'Aqua, Levi D. McClenny, Ming Zhong, Ulisses Braga-Neto, Eduardo Gildin:
Physics-Informed Neural Networks with Adaptive Localized Artificial Viscosity. CoRR abs/2203.08802 (2022) - [i15]Yicheng Wang, Xiaotian Han, Chia-Yuan Chang, Daochen Zha, Ulisses Braga-Neto, Xia Hu:
Auto-PINN: Understanding and Optimizing Physics-Informed Neural Architecture. CoRR abs/2205.13748 (2022) - [i14]Pappu Kumar Yadav, J. Alex Thomasson, Robert G. Hardin IV, Stephen W. Searcy, Ulisses Braga-Neto, Sorin C. Popescu, Daniel E. Martin, Roberto Rodriguez, Karem Meza, Juan Enciso, Jorge Solorzano Diaz, Tianyi Wang:
Detecting Volunteer Cotton Plants in a Corn Field with Deep Learning on UAV Remote-Sensing Imagery. CoRR abs/2207.06673 (2022) - [i13]Pappu Kumar Yadav, J. Alex Thomasson, Stephen W. Searcy, Robert G. Hardin, Ulisses Braga-Neto, Sorin C. Popescu, Daniel E. Martin, Roberto Rodriguez, Karem Meza, Juan Enciso, Jorge Solorzano Diaz, Tianyi Wang:
Computer Vision for Volunteer Cotton Detection in a Corn Field with UAS Remote Sensing Imagery and Spot Spray Applications. CoRR abs/2207.07334 (2022) - [i12]Pappu Kumar Yadav, J. Alex Thomasson, Stephen W. Searcy, Robert G. Hardin, Ulisses Braga-Neto, Sorin C. Popescu, Daniel E. Martin, Roberto Rodriguez, Karem Meza, Juan Enciso, Jorge Solorzano Diaz, Tianyi Wang:
Assessing The Performance of YOLOv5 Algorithm for Detecting Volunteer Cotton Plants in Corn Fields at Three Different Growth Stages. CoRR abs/2208.00519 (2022) - [i11]Pappu Kumar Yadav, J. Alex Thomasson, Robert G. Hardin, Stephen W. Searcy, Ulisses Braga-Neto, Sorin C. Popescu, Roberto Rodriguez, Daniel E. Martin, Juan Enciso, Karem Meza, Emma L. White:
Plastic Contaminant Detection in Aerial Imagery of Cotton Fields with Deep Learning. CoRR abs/2212.07527 (2022) - [i10]Ulisses Braga-Neto:
Characteristics-Informed Neural Networks for Forward and Inverse Hyperbolic Problems. CoRR abs/2212.14012 (2022) - 2021
- [c47]Levi D. McClenny, Ulisses M. Braga-Neto:
Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism. AAAI Spring Symposium: MLPS 2021 - [c46]Parisa Ghane, Narges Zarnaghinaghsh, Ulisses M. Braga-Neto:
Comparison of Classification Algorithms Towards Subject-Specific and Subject-Independent BCI. BCI 2021: 1-6 - [c45]Caio Davi, Ulisses M. Braga-Neto:
A Semi-Supervised Generative Adversarial Network for Prediction of Genetic Disease Outcomes. MLSP 2021: 1-6 - [i9]Levi D. McClenny, Mulugeta A. Haile, Ulisses M. Braga-Neto:
TensorDiffEq: Scalable Multi-GPU Forward and Inverse Solvers for Physics Informed Neural Networks. CoRR abs/2103.16034 (2021) - [i8]Yukun Tan, Durward Cator III, Martial L. Ndeffo Mbah, Ulisses M. Braga-Neto:
A stochastic metapopulation state-space approach to modeling and estimating Covid-19 spread. CoRR abs/2106.07919 (2021) - [i7]Parisa Ghane, Ulisses M. Braga-Neto:
Generalized Resubstitution for Classification Error Estimation. CoRR abs/2110.12285 (2021) - 2020
- [b1]Ulisses M. Braga-Neto:
Fundamentals of Pattern Recognition and Machine Learning. Springer 2020, ISBN 978-3-030-27655-3, pp. 1-286 - [j62]Mahdi Imani, Edward R. Dougherty, Ulisses M. Braga-Neto:
Boolean Kalman filter and smoother under model uncertainty. Autom. 111 (2020) - [j61]Ulisses M. Braga-Neto, Edward R. Dougherty:
Machine Learning Requires Probability and Statistics [Perspectives]. IEEE Signal Process. Mag. 37(4): 118-122 (2020) - [j60]Arghavan Bahadorinejad, Mahdi Imani, Ulisses M. Braga-Neto:
Adaptive Particle Filtering for Fault Detection in Partially-Observed Boolean Dynamical Systems. IEEE ACM Trans. Comput. Biol. Bioinform. 17(4): 1105-1114 (2020) - [c44]Yukun Tan, Fernando B. Lima Neto, Ulisses M. Braga-Neto:
Inference of Protein-Protein Interaction Networks from Liquid-Chromatography Mass-Spectrometry Data by Approximate Bayesian Computation-Sequential Monte Carlo Sampling. MLSP 2020: 1-6 - [i6]Levi D. McClenny, Mulugeta A. Haile, Vahid Attari, Brian M. Sadler, Ulisses M. Braga-Neto, Raymundo Arróyave:
Deep Multimodal Transfer-Learned Regression in Data-Poor Domains. CoRR abs/2006.09310 (2020) - [i5]Caio Davi, Ulisses M. Braga-Neto:
A Semi-Supervised Generative Adversarial Network for Prediction of Genetic Disease Outcomes. CoRR abs/2007.01200 (2020) - [i4]Levi D. McClenny, Ulisses M. Braga-Neto:
Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism. CoRR abs/2009.04544 (2020) - [i3]Parisa Ghane, Ulisses M. Braga-Neto:
Comparison of Classification Algorithms Towards Subject-Specific and Subject-Independent BCI. CoRR abs/2012.12473 (2020)
2010 – 2019
- 2019
- [j59]Caio Davi, André Pastor, Thiego Oliveira, Fernando Buarque de Lima Neto, Ulisses M. Braga-Neto, Abigail W. Bigham, Michael Bamshad, Ernesto T. A. Marques Jr., Bartolomeu Acioli-Santos:
Severe Dengue Prognosis Using Human Genome Data and Machine Learning. IEEE Trans. Biomed. Eng. 66(10): 2861-2868 (2019) - [j58]Alireza Karbalayghareh, Ulisses M. Braga-Neto, Edward R. Dougherty:
Classification of Single-Cell Gene Expression Trajectories from Incomplete and Noisy Data. IEEE ACM Trans. Comput. Biol. Bioinform. 16(1): 193-207 (2019) - [j57]Mahdi Imani, Ulisses M. Braga-Neto:
Control of Gene Regulatory Networks Using Bayesian Inverse Reinforcement Learning. IEEE ACM Trans. Comput. Biol. Bioinform. 16(4): 1250-1261 (2019) - [j56]Mahdi Imani, Ulisses M. Braga-Neto:
Point-Based Methodology to Monitor and Control Gene Regulatory Networks via Noisy Measurements. IEEE Trans. Control. Syst. Technol. 27(3): 1023-1035 (2019) - [c43]Mahdi Imani, Seyede Fatemeh Ghoreishi, Douglas L. Allaire, Ulisses M. Braga-Neto:
MFBO-SSM: Multi-Fidelity Bayesian Optimization for Fast Inference in State-Space Models. AAAI 2019: 7858-7865 - 2018
- [j55]Mahdi Imani, Ulisses M. Braga-Neto:
Particle filters for partially-observed Boolean dynamical systems. Autom. 87: 238-250 (2018) - [j54]Mahdi Imani, Ulisses M. Braga-Neto:
Finite-horizon LQR controller for partially-observed Boolean dynamical systems. Autom. 95: 172-179 (2018) - [j53]Mahdi Imani, Ulisses M. Braga-Neto:
Gene regulatory network state estimation from arbitrary correlated measurements. EURASIP J. Adv. Signal Process. 2018: 22 (2018) - [j52]Esmaeil Atashpaz-Gargari, Marcelo da Silva Reis, Ulisses M. Braga-Neto, Junior Barrera, Edward R. Dougherty:
A fast Branch-and-Bound algorithm for U-curve feature selection. Pattern Recognit. 73: 172-188 (2018) - [j51]Alireza Karbalayghareh, Ulisses M. Braga-Neto, Jianping Hua, Edward Russell Dougherty:
Classification of State Trajectories in Gene Regulatory Networks. IEEE ACM Trans. Comput. Biol. Bioinform. 15(1): 68-82 (2018) - [j50]Arghavan Bahadorinejad, Ulisses M. Braga-Neto:
Optimal Fault Detection and Diagnosis in Transcriptional Circuits Using Next-Generation Sequencing. IEEE ACM Trans. Comput. Biol. Bioinform. 15(2): 516-525 (2018) - [j49]Mahdi Imani, Ulisses M. Braga-Neto:
Control of Gene Regulatory Networks With Noisy Measurements and Uncertain Inputs. IEEE Trans. Control. Netw. Syst. 5(2): 760-769 (2018) - [c42]Mahdi Imani, Ulisses M. Braga-Neto:
Optimal Control of Gene Regulatory Networks with Unknown Cost Function. ACC 2018: 3939-3944 - [c41]Ehsan Hajiramezanali, Mahdi Imani, Ulisses M. Braga-Neto, Xiaoning Qian, Edward R. Dougherty:
Scalable Optimal Bayesian Classification of Single-Cell Trajectories under Regulatory Model Uncertainty. BCB 2018: 596-597 - [c40]Yukun Tan, Fernando B. Lima Neto, Ulisses M. Braga-Neto:
Inference of gene regulatory Networks by Maximum-likelihood adaptive filtering and discrete fish School Search. MLSP 2018: 1-6 - [c39]Mahdi Imani, Seyede Fatemeh Ghoreishi, Ulisses M. Braga-Neto:
Bayesian Control of Large MDPs with Unknown Dynamics in Data-Poor Environments. NeurIPS 2018: 8157-8167 - [i2]Mahdi Imani, Roozbeh Dehghannasiri, Ulisses M. Braga-Neto, Edward R. Dougherty:
Sequential Experimental Design for Optimal Structural Intervention in Gene Regulatory Networks Based on the Mean Objective Cost of Uncertainty. CoRR abs/1805.12253 (2018) - 2017
- [j48]Levi D. McClenny, Mahdi Imani, Ulisses M. Braga-Neto:
BoolFilter: an R package for estimation and identification of partially-observed Boolean dynamical systems. BMC Bioinform. 18(1): 519:1-519:8 (2017) - [j47]Mahdi Imani, Ulisses M. Braga-Neto:
Maximum-Likelihood Adaptive Filter for Partially Observed Boolean Dynamical Systems. IEEE Trans. Signal Process. 65(2): 359-371 (2017) - [c38]Shuilian Xie, Mahdi Imani, Edward R. Dougherty, Ulisses M. Braga-Neto:
Nonstationary linear discriminant analysis. ACSSC 2017: 161-165 - [c37]Emre Arslan, Ulisses M. Braga-Neto:
Bayesian top scoring pairs for feature selection. ACSSC 2017: 387-391 - [c36]Mahdi Imani, Ulisses M. Braga-Neto:
Optimal finite-horizon sensor selection for Boolean Kalman Filter. ACSSC 2017: 1481-1485 - [c35]Mahdi Imani, Ulisses M. Braga-Neto:
Multiple Model Adaptive controller for Partially-Observed Boolean Dynamical Systems. ACC 2017: 1103-1108 - [c34]Alireza Karbalayghareh, Ulisses M. Braga-Neto, Edward R. Dougherty:
Intrinsically Bayesian Robust Classifier for Single-Cell Gene Expression Time Series in Gene Regulatory Networks. BCB 2017: 766-767 - [c33]Levi D. McClenny, Mahdi Imani, Ulisses M. Braga-Neto:
Boolean Kalman Filter with correlated observation noise. ICASSP 2017: 866-870 - [c32]Emre Arslan, Ulisses M. Braga-Neto:
A Bayesian approach to Top-Scoring Pairs classification. ICASSP 2017: 871-875 - [c31]Alireza Karbalayghareh, Ulisses M. Braga-Neto, Edward R. Dougherty:
Classification of Gaussian trajectories with missing data in Boolean gene regulatory networks. ICASSP 2017: 1078-1082 - [i1]Mahdi Imani, Ulisses M. Braga-Neto:
Control of Gene Regulatory Networks with Noisy Measurements and Uncertain Inputs. CoRR abs/1702.07652 (2017) - 2016
- [j46]Ting Chen, Ulisses M. Braga-Neto:
Bayesian estimation of the discrete coefficient of determination. EURASIP J. Bioinform. Syst. Biol. 2016: 1 (2016) - [c30]Mahdi Imani, Ulisses M. Braga-Neto:
State-feedback control of Partially-Observed Boolean Dynamical Systems using RNA-seq time series data. ACC 2016: 227-232 - [c29]Mahdi Imani, Ulisses M. Braga-Neto:
Point-based value iteration for partially-observed Boolean dynamical systems with finite observation space. CDC 2016: 4208-4213 - 2015
- [j45]Ting Chen, Ulisses M. Braga-Neto:
Statistical Detection of Intrinsically Multivariate Predictive Genes. IEEE ACM Trans. Comput. Biol. Bioinform. 12(4): 951-964 (2015) - [c28]Mahdi Imani, Ulisses M. Braga-Neto:
Optimal gene regulatory network inference using the Boolean Kalman filter and multiple model adaptive estimation. ACSSC 2015: 423-427 - [c27]Mahdi Imani, Ulisses M. Braga-Neto:
Optimal state estimation for boolean dynamical systems using a boolean Kalman smoother. GlobalSIP 2015: 972-976 - 2014
- [j44]Ulisses M. Braga-Neto, Amin Zollanvari, Edward R. Dougherty:
Cross-validation under separate sampling: strong bias and how to correct it. Bioinform. 30(23): 3349-3355 (2014) - [j43]Thang T. Vu, Chao Sima, Ulisses M. Braga-Neto, Edward R. Dougherty:
Unbiased bootstrap error estimation for linear discriminant analysis. EURASIP J. Bioinform. Syst. Biol. 2014: 15 (2014) - [j42]Esmaeil Atashpaz-Gargari, Ulisses M. Braga-Neto, Edward R. Dougherty:
Modeling and systematic analysis of biomarker validation using selected reaction monitoring. EURASIP J. Bioinform. Syst. Biol. 2014: 17 (2014) - [c26]Arghavan Bahadorinejad, Ulisses M. Braga-Neto:
Optimal fault detection in stochastic Boolean regulatory networks. GlobalSIP 2014: 1386-1389 - [c25]Xingde Jiang, Ulisses M. Braga-Neto:
A Naive-Bayes approach to Bolstered error estimation in high-dimensional spaces. GlobalSIP 2014: 1398-1401 - 2013
- [j41]David Correa Martins Jr., Evaldo Araújo de Oliveira, Ulisses M. Braga-Neto, Ronaldo Fumio Hashimoto, Roberto Marcondes Cesar Jr.:
Signal propagation in Bayesian networks and its relationship with intrinsically multivariate predictive variables. Inf. Sci. 225: 18-34 (2013) - [j40]Esmaeil Atashpaz-Gargari, Chao Sima, Ulisses M. Braga-Neto, Edward R. Dougherty:
Relationship between the accuracy of classifier error estimation and complexity of decision boundary. Pattern Recognit. 46(5): 1315-1322 (2013) - [j39]Ting Chen, Ulisses M. Braga-Neto:
Maximum-Likelihood Estimation of the Discrete Coefficient of Determination in Stochastic Boolean Systems. IEEE Trans. Signal Process. 61(15): 3880-3894 (2013) - [c24]Ting Chen, Ulisses M. Braga-Neto:
Optimal Bayesian MMSE estimation of the coefficient of determination for discrete prediction. GENSiPS 2013: 66-69 - [c23]Amin Zollanvari, Ulisses M. Braga-Neto, Edward R. Dougherty:
Effect of mixing probabilities on the bias of cross-validation under separate sampling. GENSiPS 2013: 98-99 - [c22]Esmaeil Atashpaz-Gargari, Ulisses M. Braga-Neto, Edward R. Dougherty:
Improved branch-and-bound algorithm for U-curve optimization. GENSiPS 2013: 100-101 - [c21]Ulisses M. Braga-Neto:
Particle filtering approach to state estimation in Boolean dynamical systems. GlobalSIP 2013: 81-84 - 2012
- [j38]Youting Sun, Jianqiu Zhang, Ulisses M. Braga-Neto, Edward R. Dougherty:
BPDA2d - a 2D global optimization-based Bayesian peptide detection algorithm for liquid chromatograph-mass spectrometry. Bioinform. 28(4): 564-572 (2012) - [j37]Amin Zollanvari, Ulisses M. Braga-Neto, Edward R. Dougherty:
Exact representation of the second-order moments for resubstitution and leave-one-out error estimation for linear discriminant analysis in the univariate heteroskedastic Gaussian model. Pattern Recognit. 45(2): 908-917 (2012) - [c20]Ting Chen, Ulisses M. Braga-Neto:
A statistical test for intrinsically multivariate predictive genes. GENSiPS 2012: 151-154 - [c19]Ulisses M. Braga-Neto:
Joint state and parameter estimation for Boolean dynamical systems. SSP 2012: 704-707 - 2011
- [j36]Chao Sima, Ulisses M. Braga-Neto, Edward R. Dougherty:
High-dimensional bolstered error estimation. Bioinform. 27(21): 3056-3064 (2011) - [j35]Jonathan D. Wren, Doris M. Kupfer, Edward J. Perkins, Susan Bridges, Stephen Winters-Hilt, Mikhail G. Dozmorov, Ulisses M. Braga-Neto:
Proceedings of the 2011 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference. BMC Bioinform. 12(S-10): S1 (2011) - [j34]Ying Wang, Noushin Ghaffari, Charles D. Johnson, Ulisses M. Braga-Neto, Hui Wang, Rui Chen, Huaijun Zhou:
Evaluation of the coverage and depth of transcriptome by RNA-Seq in chickens. BMC Bioinform. 12(S-10): S5 (2011) - [j33]Amin Zollanvari, Ulisses M. Braga-Neto, Edward R. Dougherty:
Analytic Study of Performance of Error Estimators for Linear Discriminant Analysis. IEEE Trans. Signal Process. 59(9): 4238-4255 (2011) - [c18]Ting Chen, Ulisses M. Braga-Neto:
Maximum likelihood estimation of the binary Coefficient of Determination. ACSCC 2011: 1012-1016 - [c17]Ulisses M. Braga-Neto:
Optimal state estimation for Boolean dynamical systems. ACSCC 2011: 1050-1054 - [c16]Ulisses M. Braga-Neto, Antonia Papandreou-Suppappola:
Session TA1b: Biosignal estimation and classification. ACSCC 2011: 1090-1092 - [c15]Zhenghao Zhang, Youting Sun, Ulisses M. Braga-Neto, Edward R. Dougherty, Jianqiu Zhang:
A parallel programming framework with Markovian messaging for LC-MS peptide detection. BIBM Workshops 2011: 1057-1059 - [c14]Esmaeil Atashpaz-Gargari, Ulisses M. Braga-Neto, Edward R. Dougherty:
Multiple reaction monitoring: Modeling and systematic analysis. GENSiPS 2011: 105-107 - [c13]Youting Sun, Ulisses M. Braga-Neto, Edward R. Dougherty:
Modeling and systematic analysis of LC-MS proteomics pipeline. GENSiPS 2011: 112-116 - [c12]Ting Chen, Ulisses M. Braga-Neto:
Sample-based estimators for the instrinsically multivariate prediction score. GENSiPS 2011: 139-142 - [c11]Esmaeil Atashpaz-Gargari, Chao Sima, Ulisses M. Braga-Neto, Edward R. Dougherty:
Relationship between the accuracy of classifier error estimation and distribution complexity. GENSiPS 2011: 147-149 - [c10]Sardar Afra, Ulisses M. Braga-Neto:
Studying the possibility of peaking phenomenon in linear support vector machines with non-separable data. GENSiPS 2011: 218-221 - 2010
- [j32]Youting Sun, Jianqiu Zhang, Ulisses M. Braga-Neto, Edward R. Dougherty:
BPDA - A Bayesian peptide detection algorithm for mass spectrometry. BMC Bioinform. 11: 490 (2010) - [j31]Ting Chen, Ulisses M. Braga-Neto:
Exact Performance of CoD Estimators in Discrete Prediction. EURASIP J. Adv. Signal Process. 2010 (2010) - [j30]Thang T. Vu, Ulisses M. Braga-Neto:
Small-Sample Error Estimation for Bagged Classification Rules. EURASIP J. Adv. Signal Process. 2010 (2010) - [j29]Gerald Jean Francis Banon, Ulisses M. Braga-Neto, Roberto Marcondes Cesar Jr.:
ISMM 2007 Special Issue. Image Vis. Comput. 28(10): 1427-1428 (2010) - [j28]Ulisses M. Braga-Neto, Edward R. Dougherty:
Exact correlation between actual and estimated errors in discrete classification. Pattern Recognit. Lett. 31(5): 407-412 (2010) - [j27]Amin Zollanvari, Ulisses M. Braga-Neto, Edward R. Dougherty:
Joint sampling distribution between actual and estimated classification errors for linear discriminant analysis. IEEE Trans. Inf. Theory 56(2): 784-804 (2010) - [c9]Ting Chen, Ulisses M. Braga-Neto:
Approximate expressions for the variances of non-randomized error estimators and CoD estimators for the discrete histogram rule. GENSiPS 2010: 1-4 - [c8]Amin Zollanvari, Ulisses M. Braga-Neto, Edward R. Dougherty:
RMS bounds and sample size considerations for error estimation in linear discriminant analysis. GENSiPS 2010: 1-4
2000 – 2009
- 2009
- [j26]Jonathan D. Wren, Yuriy Gusev, Raphael D. Isokpehi, Daniel Berleant, Ulisses M. Braga-Neto, Dawn Wilkins, Susan Bridges:
Proceedings of the 2009 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference. BMC Bioinform. 10(S-11): 1 (2009) - [j25]Amin Zollanvari, Mary Jane Cunningham, Ulisses M. Braga-Neto, Edward R. Dougherty:
Analysis and modeling of time-course gene-expression profiles from nanomaterial-exposed primary human epidermal keratinocytes. BMC Bioinform. 10(S-11): 10 (2009) - [j24]Erchin Serpedin, Javier Garcia-Frías, Yufei Huang, Ulisses M. Braga-Neto:
Applications of Signal Processing Techniques to Bioinformatics, Genomics, and Proteomics. EURASIP J. Bioinform. Syst. Biol. 2009 (2009) - [j23]Youting Sun, Ulisses M. Braga-Neto, Edward R. Dougherty:
Impact of Missing Value Imputation on Classification for DNA Microarray Gene Expression Data - A Model-Based Study. EURASIP J. Bioinform. Syst. Biol. 2009 (2009) - [j22]Thang T. Vu, Ulisses M. Braga-Neto:
Is Bagging Effective in the Classification of Small-Sample Genomic and Proteomic Data? EURASIP J. Bioinform. Syst. Biol. 2009 (2009) - [j21]Amin Zollanvari, Ulisses M. Braga-Neto, Edward R. Dougherty:
On the sampling distribution of resubstitution and leave-one-out error estimators for linear classifiers. Pattern Recognit. 42(11): 2705-2723 (2009) - [c7]Chao Sima, Thang T. Vu, Ulisses M. Braga-Neto, Edward R. Dougherty:
Bolstered error estimator with feature selection. GENSiPS 2009: 1-2 - [c6]Thang T. Vu, Ulisses M. Braga-Neto, Edward R. Dougherty:
Bagging degrades the performance of linear discriminant classifiers. GENSiPS 2009: 1-2 - [c5]Amin Zollanvari, Ulisses M. Braga-Neto, Edward R. Dougherty:
Sample size calculation from specified RMS of the resubstitution error for linear classifiers. GENSiPS 2009: 1-2 - 2008
- [j20]