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ORCIDArman Zharmagambetov
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- affiliation: University of California Merced, CA, USA
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2020 – today
- 2024
[j1]Suryabhan Singh Hada
, Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov:
Sparse oblique decision trees: a tool to understand and manipulate neural net features. Data Min. Knowl. Discov. 38(5): 2863-2902 (2024)- [c19]Aaron M. Ferber, Arman Zharmagambetov, Taoan Huang, Bistra Dilkina, Yuandong Tian:
GenCO: Generating Diverse Designs with Combinatorial Constraints. ICML 2024 - [c18]Magzhan Gabidolla, Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán:
Beyond the ROC Curve: Classification Trees Using Cost-Optimal Curves, with Application to Imbalanced Datasets. ICML 2024 - [c17]Taoan Huang, Aaron M. Ferber, Arman Zharmagambetov, Yuandong Tian, Bistra Dilkina:
Contrastive Predict-and-Search for Mixed Integer Linear Programs. ICML 2024 - [i5]Anselm Paulus, Arman Zharmagambetov, Chuan Guo, Brandon Amos, Yuandong Tian:
AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs. CoRR abs/2404.16873 (2024) - 2023
- [c16]Miguel Á. Carreira-Perpiñán, Magzhan Gabidolla, Arman Zharmagambetov:
Towards Better Decision Forests: Forest Alternating Optimization. CVPR 2023: 7589-7598 - [c15]Arman Zharmagambetov, Brandon Amos, Aaron M. Ferber, Taoan Huang, Bistra Dilkina, Yuandong Tian:
Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information. NeurIPS 2023 - [i4]Arman Zharmagambetov, Brandon Amos, Aaron M. Ferber, Taoan Huang, Bistra Dilkina, Yuandong Tian:
Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information. CoRR abs/2307.08964 (2023) - [i3]Aaron M. Ferber, Arman Zharmagambetov, Taoan Huang, Bistra Dilkina, Yuandong Tian:
GenCO: Generating Diverse Solutions to Design Problems with Combinatorial Nature. CoRR abs/2310.02442 (2023) - 2022
- [b1]Arman Zharmagambetov:
Learning Tree-Based Models with Manifold Regularization: Alternating Optimization Algorithms. University of California, Merced, USA, 2022 - [c14]Arman Serikuly Zharmagambetov, Miguel Á. Carreira-Perpiñán:
Learning Interpretable, Tree-Based Projection Mappings for Nonlinear Embeddings. AISTATS 2022: 9550-9570 - [c13]Arman Zharmagambetov, Qingming Tang, Chieh-Chi Kao, Qin Zhang, Ming Sun, Viktor Rozgic, Jasha Droppo, Chao Wang:
Improved Representation Learning For Acoustic Event Classification Using Tree-Structured Ontology. ICASSP 2022: 321-325 - [c12]Magzhan Gabidolla, Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán:
Improved Multiclass AdaBoost Using Sparse Oblique Decision Trees. IJCNN 2022: 1-8 - [c11]Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán:
Semi-Supervised Learning with Decision Trees: Graph Laplacian Tree Alternating Optimization. NeurIPS 2022 - 2021
- [c10]Arman Zharmagambetov, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán:
Softmax Tree: An Accurate, Fast Classifier When the Number of Classes Is Large. EMNLP (1) 2021: 10730-10745 - [c9]Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán:
Learning a Tree of Neural Nets. ICASSP 2021: 3140-3144 - [c8]Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán:
A Simple, Effective Way To Improve Neural Net Classification: Ensembling Unit Activations With A Sparse Oblique Decision Tree. ICIP 2021: 369-373 - [c7]Arman Zharmagambetov, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán:
Improved Multiclass Adaboost For Image Classification: The Role Of Tree Optimization. ICIP 2021: 424-428 - [c6]Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov:
Understanding And Manipulating Neural Net Features Using Sparse Oblique Classification Trees. ICIP 2021: 3707-3711 - [c5]Arman Zharmagambetov, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán:
Improved Boosted Regression Forests Through Non-Greedy Tree Optimization. IJCNN 2021: 1-8 - [c4]Arman Zharmagambetov, Suryabhan Singh Hada, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán:
Non-Greedy Algorithms for Decision Tree Optimization: An Experimental Comparison. IJCNN 2021: 1-8 - [i2]Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov:
Sparse Oblique Decision Trees: A Tool to Understand and Manipulate Neural Net Features. CoRR abs/2104.02922 (2021) - 2020
- [c3]Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov:
Ensembles of Bagged TAO Trees Consistently Improve over Random Forests, AdaBoost and Gradient Boosting. FODS 2020: 35-46 - [c2]Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán:
Smaller, more accurate regression forests using tree alternating optimization. ICML 2020: 11398-11408
2010 – 2019
- 2019
- [i1]Arman Zharmagambetov, Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán:
An Experimental Comparison of Old and New Decision Tree Algorithms. CoRR abs/1911.03054 (2019) - 2016
- [c1]Narynov Sergazy Sakenovich, Arman Serikuly Zharmagambetov:
On One Approach of Solving Sentiment Analysis Task for Kazakh and Russian Languages Using Deep Learning. ICCCI (2) 2016: 537-545
Coauthor Index
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