Articoli di riviste sul tema "Model-agnostic methods"
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Su, Houcheng, Weihao Luo, Daixian Liu, Mengzhu Wang, Jing Tang, Junyang Chen, Cong Wang e Zhenghan Chen. "Sharpness-Aware Model-Agnostic Long-Tailed Domain Generalization". Proceedings of the AAAI Conference on Artificial Intelligence 38, n. 13 (24 marzo 2024): 15091–99. http://dx.doi.org/10.1609/aaai.v38i13.29431.
Testo completoPugnana, Andrea, e Salvatore Ruggieri. "A Model-Agnostic Heuristics for Selective Classification". Proceedings of the AAAI Conference on Artificial Intelligence 37, n. 8 (26 giugno 2023): 9461–69. http://dx.doi.org/10.1609/aaai.v37i8.26133.
Testo completoSatrya, Wahyu Fadli, e Ji-Hoon Yun. "Combining Model-Agnostic Meta-Learning and Transfer Learning for Regression". Sensors 23, n. 2 (4 gennaio 2023): 583. http://dx.doi.org/10.3390/s23020583.
Testo completoAtallah, Rasha Ragheb, Amirrudin Kamsin, Maizatul Akmar Ismail e Ahmad Sami Al-Shamayleh. "NEURAL NETWORK WITH AGNOSTIC META-LEARNING MODEL FOR FACE-AGING RECOGNITION". Malaysian Journal of Computer Science 35, n. 1 (31 gennaio 2022): 56–69. http://dx.doi.org/10.22452/mjcs.vol35no1.4.
Testo completoZafar, Muhammad Rehman, e Naimul Khan. "Deterministic Local Interpretable Model-Agnostic Explanations for Stable Explainability". Machine Learning and Knowledge Extraction 3, n. 3 (30 giugno 2021): 525–41. http://dx.doi.org/10.3390/make3030027.
Testo completoTak, Jae-Ho, e Byung-Woo Hong. "Enhancing Model Agnostic Meta-Learning via Gradient Similarity Loss". Electronics 13, n. 3 (29 gennaio 2024): 535. http://dx.doi.org/10.3390/electronics13030535.
Testo completoHou, Xiaoyu, Jihui Xu, Jinming Wu e Huaiyu Xu. "Cross Domain Adaptation of Crowd Counting with Model-Agnostic Meta-Learning". Applied Sciences 11, n. 24 (17 dicembre 2021): 12037. http://dx.doi.org/10.3390/app112412037.
Testo completoChen, Zhouyuan, Zhichao Lian e Zhe Xu. "Interpretable Model-Agnostic Explanations Based on Feature Relationships for High-Performance Computing". Axioms 12, n. 10 (23 ottobre 2023): 997. http://dx.doi.org/10.3390/axioms12100997.
Testo completoHu, Cong, Kai Xu, Zhengqiu Zhu, Long Qin e Quanjun Yin. "Multi-Agent Chronological Planning with Model-Agnostic Meta Reinforcement Learning". Applied Sciences 13, n. 16 (11 agosto 2023): 9174. http://dx.doi.org/10.3390/app13169174.
Testo completoXue, Tianfang, e Haibin Yu. "Unbiased Model-Agnostic Metalearning Algorithm for Learning Target-Driven Visual Navigation Policy". Computational Intelligence and Neuroscience 2021 (8 dicembre 2021): 1–12. http://dx.doi.org/10.1155/2021/5620751.
Testo completoMoskalenko, V. V. "MODEL-AGNOSTIC META-LEARNING FOR RESILIENCE OPTIMIZATION OF ARTIFICIAL INTELLIGENCE SYSTEM". Radio Electronics, Computer Science, Control, n. 2 (30 giugno 2023): 79. http://dx.doi.org/10.15588/1607-3274-2023-2-9.
Testo completoSchmidt, Henri, Palash Sashittal e Benjamin J. Raphael. "A zero-agnostic model for copy number evolution in cancer". PLOS Computational Biology 19, n. 11 (9 novembre 2023): e1011590. http://dx.doi.org/10.1371/journal.pcbi.1011590.
Testo completoHasan, Md Mahmudul. "Understanding Model Predictions: A Comparative Analysis of SHAP and LIME on Various ML Algorithms". Journal of Scientific and Technological Research 5, n. 1 (2024): 17–26. http://dx.doi.org/10.59738/jstr.v5i1.23(17-26).eaqr5800.
Testo completoLabaien Soto, Jokin, Ekhi Zugasti Uriguen e Xabier De Carlos Garcia. "Real-Time, Model-Agnostic and User-Driven Counterfactual Explanations Using Autoencoders". Applied Sciences 13, n. 5 (24 febbraio 2023): 2912. http://dx.doi.org/10.3390/app13052912.
Testo completoSun, Yifei, Cheng Song, Feng Lu, Wei Li, Hai Jin e Albert Y. Zomaya. "ES-Mask: Evolutionary Strip Mask for Explaining Time Series Prediction (Student Abstract)". Proceedings of the AAAI Conference on Artificial Intelligence 37, n. 13 (26 giugno 2023): 16342–43. http://dx.doi.org/10.1609/aaai.v37i13.27031.
Testo completoWu, Gang, Junjun Jiang, Kui Jiang e Xianming Liu. "Learning from History: Task-agnostic Model Contrastive Learning for Image Restoration". Proceedings of the AAAI Conference on Artificial Intelligence 38, n. 6 (24 marzo 2024): 5976–84. http://dx.doi.org/10.1609/aaai.v38i6.28412.
Testo completoLi, Ding, Yan Liu e Jun Huang. "Assessment of Software Vulnerability Contributing Factors by Model-Agnostic Explainable AI". Machine Learning and Knowledge Extraction 6, n. 2 (16 maggio 2024): 1087–113. http://dx.doi.org/10.3390/make6020050.
Testo completoChen, Mingyang, Wen Zhang, Zhen Yao, Yushan Zhu, Yang Gao, Jeff Z. Pan e Huajun Chen. "Entity-Agnostic Representation Learning for Parameter-Efficient Knowledge Graph Embedding". Proceedings of the AAAI Conference on Artificial Intelligence 37, n. 4 (26 giugno 2023): 4182–90. http://dx.doi.org/10.1609/aaai.v37i4.25535.
Testo completoShozu, Kanto, Masaaki Komatsu, Akira Sakai, Reina Komatsu, Ai Dozen, Hidenori Machino, Suguru Yasutomi et al. "Model-Agnostic Method for Thoracic Wall Segmentation in Fetal Ultrasound Videos". Biomolecules 10, n. 12 (17 dicembre 2020): 1691. http://dx.doi.org/10.3390/biom10121691.
Testo completoAlinia, Parastoo, Asiful Arefeen, Zhila Esna Ashari, Seyed Iman Mirzadeh e Hassan Ghasemzadeh. "Model-Agnostic Structural Transfer Learning for Cross-Domain Autonomous Activity Recognition". Sensors 23, n. 14 (12 luglio 2023): 6337. http://dx.doi.org/10.3390/s23146337.
Testo completoApicella, A., F. Isgrò, R. Prevete e G. Tamburrini. "Middle-Level Features for the Explanation of Classification Systems by Sparse Dictionary Methods". International Journal of Neural Systems 30, n. 08 (14 luglio 2020): 2050040. http://dx.doi.org/10.1142/s0129065720500409.
Testo completoDiprose, William K., Nicholas Buist, Ning Hua, Quentin Thurier, George Shand e Reece Robinson. "Physician understanding, explainability, and trust in a hypothetical machine learning risk calculator". Journal of the American Medical Informatics Association 27, n. 4 (27 febbraio 2020): 592–600. http://dx.doi.org/10.1093/jamia/ocz229.
Testo completoLiu, Jiakang, e Hua Huo. "DFENet: Double Feature Enhanced Class Agnostic Counting Methods". Frontiers in Computing and Intelligent Systems 6, n. 1 (1 dicembre 2023): 70–76. http://dx.doi.org/10.54097/fcis.v6i1.14.
Testo completoMoon, Jae-pil, Jin-Guk Kim, Choong-Heon Yang e Su-Bin Park. "A Case Study on the Application of Model-agnostic Methods for the Post hoc Interpretation of A Machine Learning Model :". International Journal of Highway Engineering 24, n. 3 (30 giugno 2022): 83–95. http://dx.doi.org/10.7855/ijhe.2022.24.3.083.
Testo completoLi, Jolen, Christoforos Galazis, Larion Popov, Lev Ovchinnikov, Tatyana Kharybina, Sergey Vesnin, Alexander Losev e Igor Goryanin. "Dynamic Weight Agnostic Neural Networks and Medical Microwave Radiometry (MWR) for Breast Cancer Diagnostics". Diagnostics 12, n. 9 (23 agosto 2022): 2037. http://dx.doi.org/10.3390/diagnostics12092037.
Testo completoR, Jain. "Transparency in AI Decision Making: A Survey of Explainable AI Methods and Applications". Advances in Robotic Technology 2, n. 1 (19 gennaio 2024): 1–10. http://dx.doi.org/10.23880/art-16000110.
Testo completoTOPCU, Deniz. "How to explain a machine learning model: HbA1c classification example". Journal of Medicine and Palliative Care 4, n. 2 (27 marzo 2023): 117–25. http://dx.doi.org/10.47582/jompac.1259507.
Testo completoVieira, Carla Piazzon Ramos, e Luciano Antonio Digiampietri. "A study about Explainable Articial Intelligence: using decision tree to explain SVM". Revista Brasileira de Computação Aplicada 12, n. 1 (8 gennaio 2020): 113–21. http://dx.doi.org/10.5335/rbca.v12i1.10247.
Testo completoNoviandy, Teuku Rizky, Ghalieb Mutig Idroes, Irsan Hardi, Mohd Afjal e Samrat Ray. "A Model-Agnostic Interpretability Approach to Predicting Customer Churn in the Telecommunications Industry". Infolitika Journal of Data Science 2, n. 1 (27 maggio 2024): 34–44. http://dx.doi.org/10.60084/ijds.v2i1.199.
Testo completoThakur, Siddhesh, Jimit Doshi, Sung Min Ha, Gaurav Shukla, Aikaterini Kotrotsou, Sanjay Talbar, Uday Kulkarni et al. "NIMG-40. ROBUST MODALITY-AGNOSTIC SKULL-STRIPPING IN PRESENCE OF DIFFUSE GLIOMA: A MULTI-INSTITUTIONAL STUDY". Neuro-Oncology 21, Supplement_6 (novembre 2019): vi170. http://dx.doi.org/10.1093/neuonc/noz175.710.
Testo completoGunel, Kadir, e Mehmet Fatih Amasyali. "Boosting Lightweight Sentence Embeddings with Knowledge Transfer from Advanced Models: A Model-Agnostic Approach". Applied Sciences 13, n. 23 (22 novembre 2023): 12586. http://dx.doi.org/10.3390/app132312586.
Testo completoKedar, Ms Mayuri Manish. "Exploring the Effectiveness of SHAP over other Explainable AI Methods". INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, n. 06 (6 giugno 2024): 1–5. http://dx.doi.org/10.55041/ijsrem35556.
Testo completoGilo, Daniel, e Shaul Markovitch. "A General Search-Based Framework for Generating Textual Counterfactual Explanations". Proceedings of the AAAI Conference on Artificial Intelligence 38, n. 16 (24 marzo 2024): 18073–81. http://dx.doi.org/10.1609/aaai.v38i16.29764.
Testo completoSong, Rui, Fausto Giunchiglia, Yingji Li, Mingjie Tian e Hao Xu. "TACIT: A Target-Agnostic Feature Disentanglement Framework for Cross-Domain Text Classification". Proceedings of the AAAI Conference on Artificial Intelligence 38, n. 17 (24 marzo 2024): 18999–9007. http://dx.doi.org/10.1609/aaai.v38i17.29866.
Testo completoWang, Kewei, Yizheng Wu, Zhiyu Pan, Xingyi Li, Ke Xian, Zhe Wang, Zhiguo Cao e Guosheng Lin. "Semi-supervised Class-Agnostic Motion Prediction with Pseudo Label Regeneration and BEVMix". Proceedings of the AAAI Conference on Artificial Intelligence 38, n. 6 (24 marzo 2024): 5490–98. http://dx.doi.org/10.1609/aaai.v38i6.28358.
Testo completoLin, Weiping, Zhenfeng Zhuang, Lequan Yu e Liansheng Wang. "Boosting Multiple Instance Learning Models for Whole Slide Image Classification: A Model-Agnostic Framework Based on Counterfactual Inference". Proceedings of the AAAI Conference on Artificial Intelligence 38, n. 4 (24 marzo 2024): 3477–85. http://dx.doi.org/10.1609/aaai.v38i4.28135.
Testo completoRonchetti, Franco, Facundo Quiroga, Ulises Jeremias Cornejo Fandos, Gastón Gustavo Rios, Pedro Dal Bianco, Waldo Hasperué e Laura Lanzarini. "comparison of small sample methods for Handshape Recognition". Journal of Computer Science and Technology 23, n. 1 (3 aprile 2023): e03. http://dx.doi.org/10.24215/16666038.23.e03.
Testo completoDemertzis, Konstantinos, e Lazaros Iliadis. "GeoAI: A Model-Agnostic Meta-Ensemble Zero-Shot Learning Method for Hyperspectral Image Analysis and Classification". Algorithms 13, n. 3 (7 marzo 2020): 61. http://dx.doi.org/10.3390/a13030061.
Testo completoFan, Xinchen, Lancheng Zou, Ziwu Liu, Yanru He, Lian Zou e Ruan Chi. "CSAC-Net: Fast Adaptive sEMG Recognition through Attention Convolution Network and Model-Agnostic Meta-Learning". Sensors 22, n. 10 (11 maggio 2022): 3661. http://dx.doi.org/10.3390/s22103661.
Testo completoSaarela, Mirka, e Lilia Geogieva. "Robustness, Stability, and Fidelity of Explanations for a Deep Skin Cancer Classification Model". Applied Sciences 12, n. 19 (23 settembre 2022): 9545. http://dx.doi.org/10.3390/app12199545.
Testo completoWinder, Isabelle, e Nick Winder. "An agnostic approach to ancient landscapes". Journal of Archaeology and Ancient History, n. 9 (13 febbraio 2023): 1–30. http://dx.doi.org/10.33063/jaah.vi9.130.
Testo completoAkhtar, Naveed, e Mohammad Amir Asim Khan Jalwana. "Rethinking Interpretation: Input-Agnostic Saliency Mapping of Deep Visual Classifiers". Proceedings of the AAAI Conference on Artificial Intelligence 37, n. 1 (26 giugno 2023): 178–86. http://dx.doi.org/10.1609/aaai.v37i1.25089.
Testo completoPruthi, Danish, Rachit Bansal, Bhuwan Dhingra, Livio Baldini Soares, Michael Collins, Zachary C. Lipton, Graham Neubig e William W. Cohen. "Evaluating Explanations: How Much Do Explanations from the Teacher Aid Students?" Transactions of the Association for Computational Linguistics 10 (2022): 359–75. http://dx.doi.org/10.1162/tacl_a_00465.
Testo completoMentias, Amgad, Eric D. Peterson, Neil Keshvani, Dharam J. Kumbhani, Clyde W. Yancy, Alanna A. Morris, Larry A. Allen et al. "Achieving Equity in Hospital Performance Assessments Using Composite Race-Specific Measures of Risk-Standardized Readmission and Mortality Rates for Heart Failure". Circulation 147, n. 15 (11 aprile 2023): 1121–33. http://dx.doi.org/10.1161/circulationaha.122.061995.
Testo completoYarlagadda, Sri Kalyan, Daniel Mas Montserrat, David Güera, Carol J. Boushey, Deborah A. Kerr e Fengqing Zhu. "Saliency-Aware Class-Agnostic Food Image Segmentation". ACM Transactions on Computing for Healthcare 2, n. 3 (luglio 2021): 1–17. http://dx.doi.org/10.1145/3440274.
Testo completoSun, Chenyu, Hangwei Qian e Chunyan Miao. "CUDC: A Curiosity-Driven Unsupervised Data Collection Method with Adaptive Temporal Distances for Offline Reinforcement Learning". Proceedings of the AAAI Conference on Artificial Intelligence 38, n. 13 (24 marzo 2024): 15145–53. http://dx.doi.org/10.1609/aaai.v38i13.29437.
Testo completoPetrescu, Livia, Cătălin Petrescu, Ana Oprea, Oana Mitruț, Gabriela Moise, Alin Moldoveanu e Florica Moldoveanu. "Machine Learning Methods for Fear Classification Based on Physiological Features". Sensors 21, n. 13 (1 luglio 2021): 4519. http://dx.doi.org/10.3390/s21134519.
Testo completoRangwala, Murtaza, Jun Liu, Kulbir Singh Ahluwalia, Shayan Ghajar, Harnaik Singh Dhami, Benjamin F. Tracy, Pratap Tokekar e Ryan K. Williams. "DeepPaSTL: Spatio-Temporal Deep Learning Methods for Predicting Long-Term Pasture Terrains Using Synthetic Datasets". Agronomy 11, n. 11 (5 novembre 2021): 2245. http://dx.doi.org/10.3390/agronomy11112245.
Testo completoChristensen, Cade, Torrey Wagner e Brent Langhals. "Year-Independent Prediction of Food Insecurity Using Classical and Neural Network Machine Learning Methods". AI 2, n. 2 (23 maggio 2021): 244–60. http://dx.doi.org/10.3390/ai2020015.
Testo completoYamazawa, Erika, Satoshi Takahashi, Shota Tanaka, Wataru Takahashi, Takahiro Nakamoto, Shunsaku Takayanagi, Yosuke Kitagawa et al. "RARE-16. A NOVEL RADIOMICS MODEL DIFFERENTIATING CHORDOMA AND CHONDROSARCOMA". Neuro-Oncology 21, Supplement_6 (novembre 2019): vi224—vi225. http://dx.doi.org/10.1093/neuonc/noz175.939.
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