Deniz Erdogmus
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Information theoretic learning: Renyi's entropy and kernel perspectives
JC Principe
Springer Science & Business Media, 2010
Tversky loss function for image segmentation using 3D fully convolutional deep networks
SSM Salehi, D Erdogmus, A Gholipour
International workshop on machine learning in medical imaging, 379-387, 2017
Automated diagnosis of plus disease in retinopathy of prematurity using deep convolutional neural networks
JM Brown, JP Campbell, A Beers, K Chang, S Ostmo, RVP Chan, J Dy, ...
JAMA ophthalmology 136 (7), 803-810, 2018
The future of human-in-the-loop cyber-physical systems
G Schirner, D Erdogmus, K Chowdhury, T Padir
Computer 46 (1), 36-45, 2013
An error-entropy minimization algorithm for supervised training of nonlinear adaptive systems
D Erdogmus, JC Principe
IEEE Transactions on Signal Processing 50 (7), 1780-1786, 2002
Generalized information potential criterion for adaptive system training
D Erdogmus, JC Principe
IEEE Transactions on Neural Networks 13 (5), 1035-1044, 2002
Locally defined principal curves and surfaces
U Ozertem, D Erdogmus
The Journal of Machine Learning Research 12, 1249-1286, 2011
Optimizing the P300-based brain–computer interface: current status, limitations and future directions
JN Mak, Y Arbel, JW Minett, LM McCane, B Yuksel, D Ryan, D Thompson, ...
Journal of neural engineering 8 (2), 025003, 2011
Auto-context convolutional neural network (auto-net) for brain extraction in magnetic resonance imaging
SSM Salehi, D Erdogmus, A Gholipour
IEEE transactions on medical imaging 36 (11), 2319-2330, 2017
Blind source separation using Renyi's mutual information
KE Hild, D Erdogmus, J Príncipe
IEEE Signal Processing Letters 8 (6), 174-176, 2001
Feature extraction using information-theoretic learning
KE Hild, D Erdogmus, K Torkkola, JC Principe
IEEE Transactions on Pattern Analysis and Machine Intelligence 28 (9), 1385-1392, 2006
Asymmetric loss functions and deep densely-connected networks for highly-imbalanced medical image segmentation: Application to multiple sclerosis lesion detection
SR Hashemi, SSM Salehi, D Erdogmus, SP Prabhu, SK Warfield, ...
IEEE Access 7, 1721-1735, 2018
Structured adversarial attack: Towards general implementation and better interpretability
K Xu, S Liu, P Zhao, PY Chen, H Zhang, Q Fan, D Erdogmus, Y Wang, ...
arXiv preprint arXiv:1808.01664, 2018
Quantitative change of EEG and respiration signals during mindfulness meditation
A Ahani, H Wahbeh, H Nezamfar, M Miller, D Erdogmus, B Oken
Journal of neuroengineering and rehabilitation 11, 1-11, 2014
A comparison of optimal MIMO linear and nonlinear models for brain–machine interfaces
SP Kim, JC Sanchez, YN Rao, D Erdogmus, JM Carmena, MA Lebedev, ...
Journal of neural engineering 3 (2), 145, 2006
Evaluation of a deep learning image assessment system for detecting severe retinopathy of prematurity
TK Redd, JP Campbell, JM Brown, SJ Kim, S Ostmo, RVP Chan, J Dy, ...
British Journal of Ophthalmology 103 (5), 580-584, 2019
The Cauchy–Schwarz divergence and Parzen windowing: Connections to graph theory and Mercer kernels
R Jenssen, JC Principe, D Erdogmus, T Eltoft
Journal of the Franklin Institute 343 (6), 614-629, 2006
A novel LMS algorithm applied to adaptive noise cancellation
JM Górriz, J Ramírez, S Cruces-Alvarez, CG Puntonet, EW Lang, ...
IEEE Signal Processing Letters 16 (1), 34-37, 2008
Clustering using Renyi's entropy
R Jenssen, KE Hild, D Erdogmus, JC Principe, T Eltoft
Proceedings of the International Joint Conference on Neural Networks, 2003 …, 2003
SNR-optimality of sum-of-squares reconstruction for phased-array magnetic resonance imaging
EG Larsson, D Erdogmus, R Yan, JC Principe, JR Fitzsimmons
Journal of Magnetic Resonance 163 (1), 121-123, 2003
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