On One Approach of Solving Sentiment Analysis Task for Kazakh and Russian Languages Using Deep Learning. - Narynov Sergazy Sakenovich; Arman Serikuly Zharmagambetov (ICCCI (2), 2016)

An Experimental Comparison of Old and New Decision Tree Algorithms. - Arman Zharmagambetov; Suryabhan Singh Hada; Miguel Á. Carreira-Perpiñán (CoRR, 2019)

Ensembles of Bagged TAO Trees Consistently Improve over Random Forests, AdaBoost and Gradient Boosting. - Miguel Á. Carreira-Perpiñán; Arman Zharmagambetov (FODS, 2020)

Smaller, more accurate regression forests using tree alternating optimization. - Arman Zharmagambetov; Miguel Á. Carreira-Perpiñán (ICML, 2020)

Softmax Tree: An Accurate, Fast Classifier When the Number of Classes Is Large. - Arman Zharmagambetov; Magzhan Gabidolla; Miguel Á. Carreira-Perpiñán (EMNLP (1), 2021)

Learning a Tree of Neural Nets. - Arman Zharmagambetov; Miguel Á. Carreira-Perpiñán (ICASSP, 2021)

Understanding And Manipulating Neural Net Features Using Sparse Oblique Classification Trees. - Suryabhan Singh Hada; Miguel Á. Carreira-Perpiñán; Arman Zharmagambetov (ICIP, 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 (ICIP, 2021)

Improved Multiclass Adaboost For Image Classification: The Role Of Tree Optimization. - Arman Zharmagambetov; Magzhan Gabidolla; Miguel Á. Carreira-Perpiñán (ICIP, 2021)

Improved Boosted Regression Forests Through Non-Greedy Tree Optimization. - Arman Zharmagambetov; Magzhan Gabidolla; Miguel Á. Carreira-Perpiñán (IJCNN, 2021)

Non-Greedy Algorithms for Decision Tree Optimization: An Experimental Comparison. - Arman Zharmagambetov; Suryabhan Singh Hada; Magzhan Gabidolla; Miguel Á. Carreira-Perpiñán (IJCNN, 2021)

Learning Interpretable, Tree-Based Projection Mappings for Nonlinear Embeddings. - Arman Serikuly Zharmagambetov; Miguel Á. Carreira-Perpiñán (AISTATS, 2022)

Improved Representation Learning For Acoustic Event Classification Using Tree-Structured Ontology. - Arman Zharmagambetov; Qingming Tang; Chieh-Chi Kao; Qin Zhang; Ming Sun 007; Viktor Rozgic; Jasha Droppo; Chao Wang 018 (ICASSP, 2022)

Improved Multiclass AdaBoost Using Sparse Oblique Decision Trees. - Magzhan Gabidolla; Arman Zharmagambetov; Miguel Á. Carreira-Perpiñán (IJCNN, 2022)

Semi-Supervised Learning with Decision Trees: Graph Laplacian Tree Alternating Optimization. - Arman Zharmagambetov; Miguel Á. Carreira-Perpiñán (NeurIPS, 2022)

Learning Tree-Based Models with Manifold Regularization: Alternating Optimization Algorithms - Arman Zharmagambetov (2022)

Towards Better Decision Forests: Forest Alternating Optimization. - Miguel Á. Carreira-Perpiñán; Magzhan Gabidolla; Arman Zharmagambetov (CVPR, 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 (NeurIPS, 2023)

GenCO: Generating Diverse Solutions to Design Problems with Combinatorial Nature. - Aaron M. Ferber; Arman Zharmagambetov; Taoan Huang; Bistra Dilkina; Yuandong Tian (CoRR, 2023)

GenCO: Generating Diverse Designs with Combinatorial Constraints. - Aaron M. Ferber; Arman Zharmagambetov; Taoan Huang; Bistra Dilkina; Yuandong Tian (ICML, 2024)

Beyond the ROC Curve: Classification Trees Using Cost-Optimal Curves, with Application to Imbalanced Datasets. - Magzhan Gabidolla; Arman Zharmagambetov; Miguel Á. Carreira-Perpiñán (ICML, 2024)

Contrastive Predict-and-Search for Mixed Integer Linear Programs. - Taoan Huang; Aaron M. Ferber; Arman Zharmagambetov; Yuandong Tian; Bistra Dilkina (ICML, 2024)

AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs. - Anselm Paulus; Arman Zharmagambetov; Chuan Guo 001; Brandon Amos; Yuandong Tian (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)

Aligning LLMs to Be Robust Against Prompt Injection. - Sizhe Chen; Arman Zharmagambetov; Saeed Mahloujifar; Kamalika Chaudhuri; Chuan Guo 001 (CoRR, 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 003; Justine T. Kao; Maryam Fazel-Zarandi; Yuandong Tian (CoRR, 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., 2024)

AgentDAM: Privacy Leakage Evaluation for Autonomous Web Agents. - Arman Zharmagambetov; Chuan Guo 001; Ivan Evtimov; Maya Pavlova; Ruslan Salakhutdinov; Kamalika Chaudhuri (CoRR, 2025)

WASP: Benchmarking Web Agent Security Against Prompt Injection Attacks. - Ivan Evtimov; Arman Zharmagambetov; Aaron Grattafiori; Chuan Guo 001; Kamalika Chaudhuri (CoRR, 2025)

Meta SecAlign: A Secure Foundation LLM Against Prompt Injection Attacks. - Sizhe Chen; Arman Zharmagambetov; David A. Wagner 001; Chuan Guo 001 (CoRR, 2025)

AlgoTune: Can Language Models Speed Up General-Purpose Numerical Programs? - Ori Press; Brandon Amos; Haoyu Zhao; Yikai Wu 001; Samuel K. Ainsworth; Dominik Krupke; Patrick Kidger; Touqir Sajed; Bartolomeo Stellato; Jisun Park 003; Nathanael Bosch; Eli Meril; et al. (CoRR, 2025)