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Publication search results
found 29 matches
- 2024
- Ajay Kumar Dwivedi, Suyash Kumar Singh, Pinku Ranjan, Anand Sharma, Vivek Singh:
Machine learning assisted dual port metasurface loaded MIMO antenna with linearly polarized to circularly polarized conversion features for n257 band of 5G mm-wave applications. Int. J. Commun. Syst. 37(8) (2024) - 2023
- Tong Jin, Shujia Pan, Xue Li, Siguang Chen:
Metadata and Image Features Co-Aware Personalized Federated Learning for Smart Healthcare. IEEE J. Biomed. Health Informatics 27(8): 4110-4119 (2023) - 2022
- Jinting Zhu, Julian Jang-Jaccard, Amardeep Singh, Ian Welch, Harith Al-Sahaf, Seyit Camtepe:
A few-shot meta-learning based siamese neural network using entropy features for ransomware classification. Comput. Secur. 117: 102691 (2022) - Qingyong Wang, Yun Zhou, Zehong Cao, Weiming Zhang:
M2SPL: Generative multiview features with adaptive meta-self-paced sampling for class-imbalance learning. Expert Syst. Appl. 189: 115999 (2022) - Si Chen, Libo Wang, Zhen Wang, Yan Yan, Da-Han Wang, Shunzhi Zhu:
Learning meta-adversarial features via multi-stage adaptation network for robust visual object tracking. Neurocomputing 491: 365-381 (2022) - Adriano Rivolli, Luís Paulo F. Garcia, Carlos Soares, Joaquin Vanschoren, André C. P. L. F. de Carvalho:
Meta-features for meta-learning. Knowl. Based Syst. 240: 108101 (2022) - Florian Lux, Ngoc Thang Vu:
Language-Agnostic Meta-Learning for Low-Resource Text-to-Speech with Articulatory Features. ACL (1) 2022: 6858-6868 - Herilalaina Rakotoarison, Louisot Milijaona, Andry Rasoanaivo, Michèle Sebag, Marc Schoenauer:
Learning meta-features for AutoML. ICLR 2022 - Hilla Shinitzky, Yuval Shahar, Dan Avraham, Yizhak Vaisman, Yakir Tsizer, Yaniv Leedon:
Exploiting Meta-Cognitive Features for a Machine-Learning-Based One-Shot Group-Decision Aggregation. CoRR abs/2201.08247 (2022) - Florian Lux, Ngoc Thang Vu:
Language-Agnostic Meta-Learning for Low-Resource Text-to-Speech with Articulatory Features. CoRR abs/2203.03191 (2022) - 2021
- Milos Kotlar, Marija Punt, Zaharije Radivojevic, Milos Cvetanovic, Veljko Milutinovic:
Novel Meta-Features for Automated Machine Learning Model Selection in Anomaly Detection. IEEE Access 9: 89675-89687 (2021) - Md. Mehedi Hasan, Shaherin Basith, Mst. Shamima Khatun, Gwang Lee, Balachandran Manavalan, Hiroyuki Kurata:
Meta-i6mA: an interspecies predictor for identifying DNA N6-methyladenine sites of plant genomes by exploiting informative features in an integrative machine-learning framework. Briefings Bioinform. 22(3) (2021) - Qingfeng Xu, Zhenguo Nie, Handing Xu, Haosu Zhou, Xinjun Liu:
SuperMeshing: A New Deep Learning Architecture for Increasing the Mesh Density of Metal Forming Stress Field with Attention Mechanism and Perceptual Features. CoRR abs/2104.09276 (2021) - Jinting Zhu, Julian Jang-Jaccard, Amardeep Singh, Ian Welch, Harith Al-Sahaf, Seyit Camtepe:
A Few-Shot Meta-Learning based Siamese Neural Network using Entropy Features for Ransomware Classification. CoRR abs/2112.00668 (2021) - 2020
- Riccardo Fantinel, Angelo Cenedese:
Multistep hybrid learning: CNN driven by spatial-temporal features for faults detection on metallic surfaces. J. Electronic Imaging 29(4): 041005 (2020) - Jincheng Xu, Qingfeng Du:
Learning transferable features in meta-learning for few-shot text classification. Pattern Recognit. Lett. 135: 271-278 (2020) - Augusto Lopez Dantas, Aurora T. R. Pozo:
On the use of fitness landscape features in meta-learning based algorithm selection for the quadratic assignment problem. Theor. Comput. Sci. 805: 62-75 (2020) - Haebeom Lee, Taewook Nam, Eunho Yang, Sung Ju Hwang:
Meta Dropout: Learning to Perturb Latent Features for Generalization. ICLR 2020 - Gwendoline de Bie, Herilalaina Rakotoarison, Gabriel Peyré, Michèle Sebag:
Distribution-Based Invariant Deep Networks for Learning Meta-Features. CoRR abs/2006.13708 (2020) - 2019
- Haebeom Lee, Taewook Nam, Eunho Yang, Sung Ju Hwang:
Meta Dropout: Learning to Perturb Features for Generalization. CoRR abs/1905.12914 (2019) - 2018
- Yasunobu Nohara, Koji Iihara, Naoki Nakashima:
Interpretable Machine Learning Techniques for Causal Inference Using Balancing Scores as Meta-features. EMBC 2018: 4042-4045 - Bruno Almeida Pimentel, André C. P. L. F. de Carvalho:
Statistical versus Distance-Based Meta-Features for Clustering Algorithm recommendation Using Meta-Learning. IJCNN 2018: 1-8 - 2017
- Neeru Narang, Michael Martin, Dimitris N. Metaxas, Thirimachos Bourlai:
Learning Deep Features for Hierarchical Classification of Mobile Phone Face Datasets in Heterogeneous Environments. FG 2017: 186-193 - 2016
- Jorge Y. Kanda, André C. P. L. F. de Carvalho, Eduardo R. Hruschka, Carlos Soares, Pavel Brazdil:
Meta-learning to select the best meta-heuristic for the Traveling Salesman Problem: A comparison of meta-features. Neurocomputing 205: 393-406 (2016) - Oliver Kroemer, Gaurav S. Sukhatme:
Meta-level Priors for Learning Manipulation Skills with Sparse Features. ISER 2016: 211-222 - Oliver Kroemer, Gaurav S. Sukhatme:
Learning Relevant Features for Manipulation Skills using Meta-Level Priors. CoRR abs/1605.04439 (2016) - 2011
- Wlodzislaw Duch, Tomasz Maszczyk, Marek Grochowski:
Optimal Support Features for Meta-Learning. Meta-Learning in Computational Intelligence 2011: 317-358 - 2006
- Nikolaos G. Bourbakis, Anna Esposito, Despina Kavraki:
Analysis of Invariant Meta-features for Learning and Understanding Disable People's Emotional Behavior Related to Their Health Conditions: A Case Study. BIBE 2006: 357-369 - 2005
- Ciro Castiello, Giovanna Castellano, Anna Maria Fanelli:
Meta-data: Characterization of Input Features for Meta-learning. MDAI 2005: 457-468
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