Arman Zharmagambetov

According to our database, Arman Zharmagambetov authored at least 19 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

GenCO: Generating Diverse Solutions to Design Problems with Combinatorial Nature.

Aaron M. Ferber, Arman Zharmagambetov, Taoan Huang, Bistra Dilkina, Yuandong Tian

CoRR, 2023

Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information.

Arman Zharmagambetov, Brandon Amos, Aaron M. Ferber, Taoan Huang, Bistra Dilkina, Yuandong Tian

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Towards Better Decision Forests: Forest Alternating Optimization.

Miguel Á. Carreira-Perpiñán, Magzhan Gabidolla, Arman Zharmagambetov

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Semi-Supervised Learning with Decision Trees: Graph Laplacian Tree Alternating Optimization.

Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Improved Multiclass AdaBoost Using Sparse Oblique Decision Trees.

Magzhan Gabidolla, Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán

Proceedings of the International Joint Conference on Neural Networks, 2022

Improved Representation Learning For Acoustic Event Classification Using Tree-Structured Ontology.

Arman Zharmagambetov, Qingming Tang, Chieh-Chi Kao, Qin Zhang, Ming Sun, Viktor Rozgic, Jasha Droppo, Chao Wang

Proceedings of the IEEE International Conference on Acoustics, 2022

Learning Interpretable, Tree-Based Projection Mappings for Nonlinear Embeddings.

Arman Serikuly Zharmagambetov, Miguel Á. Carreira-Perpiñán

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Sparse Oblique Decision Trees: A Tool to Understand and Manipulate Neural Net Features.

Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov

CoRR, 2021

Non-Greedy Algorithms for Decision Tree Optimization: An Experimental Comparison.

Arman Zharmagambetov, Suryabhan Singh Hada, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán

Proceedings of the International Joint Conference on Neural Networks, 2021

Improved Boosted Regression Forests Through Non-Greedy Tree Optimization.

Arman Zharmagambetov, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán

Proceedings of the International Joint Conference on Neural Networks, 2021

Improved Multiclass Adaboost For Image Classification: The Role Of Tree Optimization.

Arman Zharmagambetov, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

A Simple, Effective Way To Improve Neural Net Classification: Ensembling Unit Activations With A Sparse Oblique Decision Tree.

Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

Understanding And Manipulating Neural Net Features Using Sparse Oblique Classification Trees.

Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

Learning a Tree of Neural Nets.

Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán

Proceedings of the IEEE International Conference on Acoustics, 2021

Softmax Tree: An Accurate, Fast Classifier When the Number of Classes Is Large.

Arman Zharmagambetov, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

Smaller, more accurate regression forests using tree alternating optimization.

Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán

Proceedings of the 37th International Conference on Machine Learning, 2020

Ensembles of Bagged TAO Trees Consistently Improve over Random Forests, AdaBoost and Gradient Boosting.

Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov

Proceedings of the FODS '20: ACM-IMS Foundations of Data Science Conference, 2020

2019

An Experimental Comparison of Old and New Decision Tree Algorithms.

Arman Zharmagambetov, Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán

CoRR, 2019

2016

On One Approach of Solving Sentiment Analysis Task for Kazakh and Russian Languages Using Deep Learning.

Narynov Sergazy Sakenovich, Arman Serikuly Zharmagambetov

Proceedings of the Computational Collective Intelligence - 8th International Conference, 2016