Arman Zharmagambetov

According to our database, Arman Zharmagambetov authored at least 27 papers between 2016 and 2024.

Collaborative distances:

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

2024

Sparse oblique decision trees: a tool to understand and manipulate neural net features.

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

Data Min. Knowl. Discov., September, 2024

To the Globe (TTG): Towards Language-Driven Guaranteed Travel Planning.

Da JU, Song Jiang, Andrew Cohen, Aaron Foss, Sasha Mitts, Arman Zharmagambetov, Brandon Amos, Xian Li, Justine T. Kao, Maryam Fazel-Zarandi, Yuandong Tian

CoRR, 2024

Aligning LLMs to Be Robust Against Prompt Injection.

Sizhe Chen, Arman Zharmagambetov, Saeed Mahloujifar, Kamalika Chaudhuri, Chuan Guo

CoRR, 2024

MARS: Multi-radio Architecture with Radio Selection using Decision Trees for emerging mesoscale CPS/IoT applications.

Jothi Prasanna Shanmuga Sundaram, Arman Zharmagambetov, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán, Alberto Cerpa

CoRR, 2024

AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs.

Anselm Paulus, Arman Zharmagambetov, Chuan Guo, Brandon Amos, Yuandong Tian

CoRR, 2024

Contrastive Predict-and-Search for Mixed Integer Linear Programs.

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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Beyond the ROC Curve: Classification Trees Using Cost-Optimal Curves, with Application to Imbalanced Datasets.

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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

GenCO: Generating Diverse Designs with Combinatorial Constraints.

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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

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

Learning Tree-Based Models with Manifold Regularization: Alternating Optimization Algorithms

Arman Zharmagambetov

PhD thesis, 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

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