2 citations · 2 across the 5 of their papers we have counts for
6 papers
CloudIR-Bench: A Benchmark for Root Cause Analysis and Mitigation of Cloud Incidents
Hoang Tran, Huong Ha, Tri Dang +2
Root cause analysis (RCA) and mitigation prediction are essential for incident management, enabling the identification of underlying causes of failures and ensuring the reliability…
An Empirical Study on Ensemble-Based Transfer Learning Bayesian Optimisation with Mixed Variable Types
Natasha Trinkle, Huong Ha, Jeffrey Chan
Bayesian optimisation is a sample efficient method for finding a global optimum of expensive black-box objective functions. Historic datasets from related problems can be exploited…
MOBO-OSD: Batch Multi-Objective Bayesian Optimization via Orthogonal Search Directions
Lam Ngo, Huong Ha, Jeffrey Chan +1
Bayesian Optimization (BO) is a powerful tool for optimizing expensive black-box objective functions. While extensive research has been conducted on the single-objective optimizati…
MOCA-HESP: Meta High-dimensional Bayesian Optimization for Combinatorial and Mixed Spaces via Hyper-ellipsoid Partitioning
Lam Ngo, Huong Ha, Jeffrey Chan +1
High-dimensional Bayesian Optimization (BO) has attracted significant attention in recent research. However, existing methods have mainly focused on optimizing in continuous domain…
BOIDS: High-dimensional Bayesian Optimization via Incumbent-guided Direction Lines and Subspace Embeddings
Lam Ngo, Huong Ha, Jeffrey Chan +1
When it comes to expensive black-box optimization problems, Bayesian Optimization (BO) is a well-known and powerful solution. Many real-world applications involve a large number of…
High-dimensional Bayesian Optimization via Covariance Matrix Adaptation Strategy
Lam Ngo, Huong Ha, Jeffrey Chan +2
Bayesian Optimization (BO) is an effective method for finding the global optimum of expensive black-box functions. However, it is well known that applying BO to high-dimensional op…