7 papers
Which Directions Matter? Sparse Design for Affine Robust Optimization
Pedro Chumpitaz-Flores, My Duong, Juan S. Borrero +1
Robust machine learning and optimization rely on the uncertainty model choice. We investigate which uncertainty directions a model must cover when defined by a finite dictionary an…
PASS: Certified Subset Repair for Classical and Quantum Pairwise Constrained Clustering
Pedro Chumpitaz-Flores, My Duong, Ying Mao +1
Pairwise-constrained clustering incorporates side information through must-link (ML) and cannot-link (CL) relations between samples. While these constraints can improve cluster qua…
qc-kmeans: A Quantum Compressive K-Means Algorithm for NISQ Devices
Pedro Chumpitaz-Flores, My Duong, Ying Mao +1
Clustering on NISQ hardware is constrained by data loading and limited qubits. We present \textbf{qc-kmeans}, a hybrid compressive -means that summarizes a dataset with a consta…
QIBONN: A Quantum-Inspired Bilevel Optimizer for Neural Networks on Tabular Classification
Pedro Chumpitaz-Flores, My Duong, Ying Mao +1
Hyperparameter optimization (HPO) for neural networks on tabular data is critical to a wide range of applications, yet it remains challenging due to large, non-convex search spaces…
RS-ORT: A Reduced-Space Branch-and-Bound Algorithm for Optimal Regression Trees
Cristobal Heredia, Pedro Chumpitaz-Flores, Kaixun Hua
Mixed-integer programming (MIP) has emerged as a powerful framework for learning optimal decision trees. Yet, existing MIP approaches for regression tasks are either limited to pur…
A Scalable Global Optimization Algorithm For Constrained Clustering
Pedro Chumpitaz-Flores, My Duong, Cristobal Heredia +1
Constrained clustering leverages limited domain knowledge to improve clustering performance and interpretability, but incorporating pairwise must-link and cannot-link constraints i…