Journal articles on the topic 'Benign overfitting'
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Bartlett, Peter L., Philip M. Long, Gábor Lugosi, and Alexander Tsigler. "Benign overfitting in linear regression." Proceedings of the National Academy of Sciences 117, no. 48 (April 24, 2020): 30063–70. http://dx.doi.org/10.1073/pnas.1907378117.
Peters, Evan, and Maria Schuld. "Generalization despite overfitting in quantum machine learning models." Quantum 7 (December 20, 2023): 1210. http://dx.doi.org/10.22331/q-2023-12-20-1210.
Bartlett, Peter L., Andrea Montanari, and Alexander Rakhlin. "Deep learning: a statistical viewpoint." Acta Numerica 30 (May 2021): 87–201. http://dx.doi.org/10.1017/s0962492921000027.
Wang, Ke, and Christos Thrampoulidis. "Binary Classification of Gaussian Mixtures: Abundance of Support Vectors, Benign Overfitting, and Regularization." SIAM Journal on Mathematics of Data Science 4, no. 1 (March 2022): 260–84. http://dx.doi.org/10.1137/21m1415121.
Hu, Wei. "Understanding Surprising Generalization Phenomena in Deep Learning." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 20 (March 24, 2024): 22669. http://dx.doi.org/10.1609/aaai.v38i20.30285.
Montaha, Sidratul, Sami Azam, A. K. M. Rakibul Haque Rafid, Sayma Islam, Pronab Ghosh, and Mirjam Jonkman. "A shallow deep learning approach to classify skin cancer using down-scaling method to minimize time and space complexity." PLOS ONE 17, no. 8 (August 4, 2022): e0269826. http://dx.doi.org/10.1371/journal.pone.0269826.
Windisch, Paul, Carole Koechli, Susanne Rogers, Christina Schröder, Robert Förster, Daniel R. Zwahlen, and Stephan Bodis. "Machine Learning for the Detection and Segmentation of Benign Tumors of the Central Nervous System: A Systematic Review." Cancers 14, no. 11 (May 27, 2022): 2676. http://dx.doi.org/10.3390/cancers14112676.
Liang, ShuFen, HuiLin Liu, FangChen Yang, Chuanbo Qin, and Yue Feng. "Classification of Benign and Malignant Pulmonary Nodules Using a Regularized Extreme Learning Machine." Journal of Medical Imaging and Health Informatics 11, no. 8 (August 1, 2021): 2117–23. http://dx.doi.org/10.1166/jmihi.2021.3448.
Liu, Xinwei, Xiaojun Jia, Jindong Gu, Yuan Xun, Siyuan Liang, and Xiaochun Cao. "Does Few-Shot Learning Suffer from Backdoor Attacks?" Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 18 (March 24, 2024): 19893–901. http://dx.doi.org/10.1609/aaai.v38i18.29965.
Doimo, Diego, Aldo Glielmo, Sebastian Goldt, and Alessandro Laio. "Redundant representations help generalization in wide neural networks * , †." Journal of Statistical Mechanics: Theory and Experiment 2023, no. 11 (November 1, 2023): 114011. http://dx.doi.org/10.1088/1742-5468/aceb4f.
Li, Jian, Yong Liu, and Weiping Wang. "High-Dimensional Analysis for Generalized Nonlinear Regression: From Asymptotics to Algorithm." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 12 (March 24, 2024): 13500–13508. http://dx.doi.org/10.1609/aaai.v38i12.29253.
Alkhaleefah, Mohammad, Shang-Chih Ma, Yang-Lang Chang, Bormin Huang, Praveen Kumar Chittem, and Vishnu Priya Achhannagari. "Double-Shot Transfer Learning for Breast Cancer Classification from X-Ray Images." Applied Sciences 10, no. 11 (June 9, 2020): 3999. http://dx.doi.org/10.3390/app10113999.
Istighosah, Maie, Andi Sunyoto, and Tonny Hidayat. "Breast Cancer Detection in Histopathology Images using ResNet101 Architecture." sinkron 8, no. 4 (October 1, 2023): 2138–49. http://dx.doi.org/10.33395/sinkron.v8i4.12948.
Anjum, Sunila, Imran Ahmed, Muhammad Asif, Hanan Aljuaid, Fahad Alturise, Yazeed Yasin Ghadi, and Rashad Elhabob. "Lung Cancer Classification in Histopathology Images Using Multiresolution Efficient Nets." Computational Intelligence and Neuroscience 2023 (October 16, 2023): 1–12. http://dx.doi.org/10.1155/2023/7282944.
Nadkarni, Swati, and Kevin Noronha. "Breast cancer detection using ensemble of convolutional neural networks." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 1 (February 1, 2024): 1041. http://dx.doi.org/10.11591/ijece.v14i1.pp1041-1047.
Ren, Cheng, and Shouming Hou. "A Hybrid Deep Learning Approach for Lung Nodule Classification." Frontiers in Computing and Intelligent Systems 8, no. 1 (May 10, 2024): 6–12. http://dx.doi.org/10.54097/498fxm65.
Zi Wei, Yee, Marina Md-Arshad, Adlina Abdul Samad, and Norafida Ithnin. "Comparing Malware Attack Detection using Machine Learning Techniques in IoT Network Traffic." International Journal of Innovative Computing 13, no. 1 (May 30, 2023): 21–27. http://dx.doi.org/10.11113/ijic.v13n1.384.
Palla, Tarun Ganesh, and Shahab Tayeb. "Intelligent Mirai Malware Detection for IoT Nodes." Electronics 10, no. 11 (May 24, 2021): 1241. http://dx.doi.org/10.3390/electronics10111241.
Alruwaili, Madallah, and Walaa Gouda. "Automated Breast Cancer Detection Models Based on Transfer Learning." Sensors 22, no. 3 (January 24, 2022): 876. http://dx.doi.org/10.3390/s22030876.
Liu, Yaning, Lin Han, Hexiang Wang, and Bo Yin. "Classification of papillary thyroid carcinoma histological images based on deep learning." Journal of Intelligent & Fuzzy Systems 40, no. 6 (June 21, 2021): 12011–21. http://dx.doi.org/10.3233/jifs-210100.
Ullah, Naeem, Ali Javed, Ali Alhazmi, Syed M. Hasnain, Ali Tahir, and Rehan Ashraf. "TumorDetNet: A unified deep learning model for brain tumor detection and classification." PLOS ONE 18, no. 9 (September 27, 2023): e0291200. http://dx.doi.org/10.1371/journal.pone.0291200.
Zawad, Syed, Ahsan Ali, Pin-Yu Chen, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Yuan Tian, and Feng Yan. "Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 12 (May 18, 2021): 10807–14. http://dx.doi.org/10.1609/aaai.v35i12.17291.
Gonzalez-Cuautle, David, Aldo Hernandez-Suarez, Gabriel Sanchez-Perez, Linda Karina Toscano-Medina, Jose Portillo-Portillo, Jesus Olivares-Mercado, Hector Manuel Perez-Meana, and Ana Lucila Sandoval-Orozco. "Synthetic Minority Oversampling Technique for Optimizing Classification Tasks in Botnet and Intrusion-Detection-System Datasets." Applied Sciences 10, no. 3 (January 22, 2020): 794. http://dx.doi.org/10.3390/app10030794.
Salama, Wessam M., Moustafa H. Aly, and Azza M. Elbagoury. "Lung Images Segmentation and Classification Based on Deep Learning: A New Automated CNN Approach." Journal of Physics: Conference Series 2128, no. 1 (December 1, 2021): 012011. http://dx.doi.org/10.1088/1742-6596/2128/1/012011.
Balasubramaniam, Sathiyabhama, Yuvarajan Velmurugan, Dhayanithi Jaganathan, and Seshathiri Dhanasekaran. "A Modified LeNet CNN for Breast Cancer Diagnosis in Ultrasound Images." Diagnostics 13, no. 17 (August 24, 2023): 2746. http://dx.doi.org/10.3390/diagnostics13172746.
Radhi, Eman, and Mohammed Kamil. "An automatic segmentation of breast ultrasound images using U-Net model." Serbian Journal of Electrical Engineering 20, no. 2 (2023): 191–203. http://dx.doi.org/10.2298/sjee2302191r.
Kujdowicz, Monika, Dominika Januś, Anna Taczanowska-Niemczuk, Marek W. Lankosz, and Dariusz Adamek. "Raman Spectroscopy as a Potential Adjunct of Thyroid Nodule Evaluation: A Systematic Review." International Journal of Molecular Sciences 24, no. 20 (October 13, 2023): 15131. http://dx.doi.org/10.3390/ijms242015131.
Alhussainan, Norah Fahd, Belgacem Ben Youssef, and Mohamed Maher Ben Ismail. "A Deep Learning Approach for Brain Tumor Firmness Detection Based on Five Different YOLO Versions: YOLOv3–YOLOv7." Computation 12, no. 3 (March 1, 2024): 44. http://dx.doi.org/10.3390/computation12030044.
Wang, Ruikui, Yuanfang Guo, and Yunhong Wang. "AGS: Affordable and Generalizable Substitute Training for Transferable Adversarial Attack." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 6 (March 24, 2024): 5553–62. http://dx.doi.org/10.1609/aaai.v38i6.28365.
Shah, Rajesh P., Heather M. Selby, Pritam Mukherjee, Shefali Verma, Peiyi Xie, Qinmei Xu, Millie Das, Sachin Malik, Olivier Gevaert, and Sandy Napel. "Machine Learning Radiomics Model for Early Identification of Small-Cell Lung Cancer on Computed Tomography Scans." JCO Clinical Cancer Informatics, no. 5 (June 2021): 746–57. http://dx.doi.org/10.1200/cci.21.00021.
Alzubaidi, Laith, Omran Al-Shamma, Mohammed A. Fadhel, Laith Farhan, Jinglan Zhang, and Ye Duan. "Optimizing the Performance of Breast Cancer Classification by Employing the Same Domain Transfer Learning from Hybrid Deep Convolutional Neural Network Model." Electronics 9, no. 3 (March 6, 2020): 445. http://dx.doi.org/10.3390/electronics9030445.
Wildeboer, Rogier R., Christophe K. Mannaerts, Ruud J. G. van Sloun, Lars Budäus, Derya Tilki, Hessel Wijkstra, Georg Salomon, and Massimo Mischi. "Automated multiparametric localization of prostate cancer based on B-mode, shear-wave elastography, and contrast-enhanced ultrasound radiomics." European Radiology 30, no. 2 (October 10, 2019): 806–15. http://dx.doi.org/10.1007/s00330-019-06436-w.
Atarsaikhan, Gantugs, Isabel Mogollon, Katja Välimäki, Tuomas Mirtti, Teijo Pellinen, and Lassi Paavolainen. "Abstract 892: Pan-cancer tumor microenvironment profiling with multiplexed immunofluorescence microscopy and self-supervised learning." Cancer Research 84, no. 6_Supplement (March 22, 2024): 892. http://dx.doi.org/10.1158/1538-7445.am2024-892.
Feng, Liqi, Yaqin Zhao, Yichao Sun, Wenxuan Zhao, and Jiaxi Tang. "Action Recognition Using a Spatial-Temporal Network for Wild Felines." Animals 11, no. 2 (February 12, 2021): 485. http://dx.doi.org/10.3390/ani11020485.
Tran-Quoc, Kim, Lieu B. Nguyen, Van Hai Luong, and H. Nguyen-Xuan. "Machine learning for predicting mechanical behavior of concrete beams with 3D printed TPMS." Vietnam Journal of Mechanics 44, no. 4 (December 31, 2022): 538–84. http://dx.doi.org/10.15625/0866-7136/17999.
Wang, Ke, Vidya Muthukumar, and Christos Thrampoulidis. "Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation." IEEE Transactions on Information Theory, 2023, 1. http://dx.doi.org/10.1109/tit.2023.3320098.
Zhou, Lijia, Frederic Koehler, Danica J. Sutherland, and Nathan Srebro. "Optimistic Rates: A Unifying Theory for Interpolation Learningand Regularization in Linear Regression." ACM / IMS Journal of Data Science, November 16, 2023. http://dx.doi.org/10.1145/3594234.
Zufry, Hendra, and Agus Arip Munawar. "Near-Infrared Spectroscopy for Distinguishing Malignancy in Thyroid Nodules." Applied Spectroscopy, February 19, 2024. http://dx.doi.org/10.1177/00037028241232440.
To, Tyrell, Tongtong Lu, Julie M. Jorns, Mollie Patton, Taly Gilat Schmidt, Tina Yen, Bing Yu, and Dong Hye Ye. "Deep learning classification of deep ultraviolet fluorescence images toward intra-operative margin assessment in breast cancer." Frontiers in Oncology 13 (June 16, 2023). http://dx.doi.org/10.3389/fonc.2023.1179025.
Kim, Taehyun, Woonyoung Chang, Jeongyoun Ahn, and Sungkyu Jung. "Double data piling: a high-dimensional solution for asymptotically perfect multi-category classification." Journal of the Korean Statistical Society, April 3, 2024. http://dx.doi.org/10.1007/s42952-024-00263-6.
Feliciani, Giacomo, Francesco Serra, Enrico Menghi, Fabio Ferroni, Anna Sarnelli, Carlo Feo, Maria Chiara Zatelli, Maria Rosaria Ambrosio, Melchiore Giganti, and Aldo Carnevale. "Radiomics in the characterization of lipid-poor adrenal adenomas at unenhanced CT: time to look beyond usual density metrics." European Radiology, August 11, 2023. http://dx.doi.org/10.1007/s00330-023-10090-8.
Giraldo‐Roldan, Daniela, Erin Crespo Cordeiro Ribeiro, Anna Luiza Damaceno Araújo, Paulo Victor Mendes Penafort, Viviane Mariano da Silva, Jeconias Câmara, Hélder Antônio Rebelo Pontes, et al. "Deep learning applied to the histopathological diagnosis of ameloblastomas and ameloblastic carcinomas." Journal of Oral Pathology & Medicine, September 15, 2023. http://dx.doi.org/10.1111/jop.13481.
Jiménez-Gaona, Yuliana, María José Rodríguez-Alvarez, Líder Escudero, Carlos Sandoval, and Vasudevan Lakshminarayanan. "Ultrasound breast images denoising using generative adversarial networks (GANs)." Intelligent Data Analysis, January 31, 2024, 1–18. http://dx.doi.org/10.3233/ida-230631.
Yang, Fan, Yujie Li, Xiaolu Li, Xiaoduo Yu, Yanfeng Zhao, Lin Li, Lizhi Xie, and Meng Lin. "The utility of texture analysis based on quantitative synthetic magnetic resonance imaging in nasopharyngeal carcinoma: a preliminary study." BMC Medical Imaging 23, no. 1 (January 25, 2023). http://dx.doi.org/10.1186/s12880-023-00968-w.
Montaha, Sidratul, Sami Azam, Md Rahad Islam Bhuiyan, Sadia Sultana Chowa, Md Saddam Hossain Mukta, and Mirjam Jonkman. "Malignancy pattern analysis of breast ultrasound images using clinical features and a graph convolutional network." DIGITAL HEALTH 10 (January 2024). http://dx.doi.org/10.1177/20552076241251660.
Singhal, Aneesh B., Oguzhan Kursun, Mehmet A. Topcuoglu, Joshua Fok, Bruce Barton, and Susanne Muehlschlegel. "Abstract WP431: Distinguishing RCVS-associated Subarachnoid Hemorrhage From Cryptogenic and Aneurysmal Subarachnoid Hemorrhage." Stroke 44, suppl_1 (February 2013). http://dx.doi.org/10.1161/str.44.suppl_1.awp431.