| Sentiment analysis of a document using deep learning approach and decision trees AS Zharmagambetov, AA Pak 2015 Twelve international conference on electronics computer and computation …, 2015 | 61 | 2015 |
| Ensembles of bagged TAO trees consistently improve over random forests, AdaBoost and gradient boosting MÁ Carreira-Perpiñán, A Zharmagambetov Proceedings of the 2020 ACM-IMS on foundations of data science conference, 35-46, 2020 | 37 | 2020 |
| Smaller, More Accurate Regression Forests Using Tree Alternating Optimization A Zharmagambetov, MA Carreira-Perpinán Proceedings of the 37th International Conference on Machine Learning, 2020 | 32 | 2020 |
| Improved multiclass AdaBoost for image classification: The role of tree optimization A Zharmagambetov, M Gabidolla, MA Carreira-Perpinán 2021 IEEE International Conference on Image Processing (ICIP), 424-428, 2021 | 26 | 2021 |
| Non-greedy algorithms for decision tree optimization: An experimental comparison A Zharmagambetov, SS Hada, M Gabidolla, MA Carreira-Perpinán 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 25 | 2021 |
| On one approach of solving sentiment analysis task for Kazakh and Russian languages using deep learning NS Sakenovich, AS Zharmagambetov Computational Collective Intelligence: 8th International Conference, ICCCI …, 2016 | 18 | 2016 |
| Improved boosted regression forests through non-greedy tree optimization A Zharmagambetov, M Gabidolla, MÊ Carreira-Perpiñán 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 16 | 2021 |
| An experimental comparison of old and new decision tree algorithms A Zharmagambetov, SS Hada, MÁ Carreira-Perpiñán, M Gabidolla arXiv preprint arXiv:1911.03054, 2019 | 16 | 2019 |
| Sparse oblique decision trees: A tool to understand and manipulate neural net features SS Hada, MÁ Carreira-Perpiñán, A Zharmagambetov Data Mining and Knowledge Discovery, 1-40, 2023 | 13 | 2023 |
| Learning a tree of neural nets A Zharmagambetov, MA Carreira-Perpinán ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 13 | 2021 |
| The method of synonyms extraction from unannotated corpus AA Pak, SS Narynov, AS Zharmagambetov, SN Sagyndykova, ... 2015 Third International Conference on Digital Information, Networking, and …, 2015 | 8 | 2015 |
| Improved multiclass AdaBoost using sparse oblique decision trees M Gabidolla, A Zharmagambetov, MÁ Carreira-Perpiñán 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022 | 7 | 2022 |
| Semi-supervised learning with decision trees: Graph laplacian tree alternating optimization A Zharmagambetov, MÁ Carreira-Perpiñán Advances in Neural Information Processing Systems 35, 2392-2405, 2022 | 6 | 2022 |
| Improved representation learning for acoustic event classification using tree-structured ontology A Zharmagambetov, Q Tang, CC Kao, Q Zhang, M Sun, V Rozgic, ... ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 6 | 2022 |
| Softmax Tree: An Accurate, Fast Classifier When the Number of Classes Is Large A Zharmagambetov, M Gabidolla, MÁ Carreira-Perpiñán Conference on Empirical Methods in Natural Language Processing (EMNLP 2021), 2021 | 6 | 2021 |
| Understanding and manipulating neural net features using sparse oblique classification trees SS Hada, MÁ Carreira-Perpiñán, A Zharmagambetov 2021 IEEE International Conference on Image Processing (ICIP), 3707-3711, 2021 | 6 | 2021 |
| Learning Interpretable, Tree-Based Projection Mappings for Nonlinear Embeddings A Zharmagambetov, MA Carreira-Perpinán International Conference on Artificial Intelligence and Statistics 25, 2022 | 4 | 2022 |
| Faster neural net inference via forests of sparse oblique decision trees Y Idelbayev, A Zharmagambetov, M Gabidolla, MÁ Carreira-Perpiñán | 4 | 2021 |
| Landscape surrogate: Learning decision losses for mathematical optimization under partial information A Zharmagambetov, B Amos, A Ferber, T Huang, B Dilkina, Y Tian Advances in Neural Information Processing Systems 36, 2024 | 3 | 2024 |
| Fast Model Compression MA Carreira-Perpinán, A Zharmagambetov Bay Area Machine Learning Symposium (BayLearn 2018), 2018 | 3 | 2018 |
Miguel Á. Carreira-PerpiñánProfessor of Computer Science, University of California, MercedVerified email at ucmerced.edu
