57 citations · 167 across the 18 of their papers we have counts for
9 papers · 1 filter
An Information-Theoretic Framework for Unifying Active Learning Problems
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
This paper presents an information-theoretic framework for unifying active learning problems: level set estimation (LSE), Bayesian optimization (BO), and their generalized variant.…
Top- Ranking Bayesian Optimization
Quoc Phong Nguyen, Sebastian Tay, Bryan Kian Hsiang Low +1
This paper presents a novel approach to top- ranking Bayesian optimization (top- ranking BO) which is a practical and significant generalization of preferential BO to handle…
Variational Bayesian Unlearning
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
This paper studies the problem of approximately unlearning a Bayesian model from a small subset of the training data to be erased. We frame this problem as one of minimizing the Ku…
Federated Bayesian Optimization via Thompson Sampling
Zhongxiang Dai, Kian Hsiang Low, Patrick Jaillet
Bayesian optimization (BO) is a prominent approach to optimizing expensive-to-evaluate black-box functions. The massive computational capability of edge devices such as mobile phon…
Competitive Ratios for Online Multi-capacity Ridesharing
Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
In multi-capacity ridesharing, multiple requests (e.g., customers, food items, parcels) with different origin and destination pairs travel in one resource. In recent years, online…
Zone pAth Construction (ZAC) based Approaches for Effective Real-Time Ridesharing
Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Real-time ridesharing systems such as UberPool, Lyft Line, GrabShare have become hugely popular as they reduce the costs for customers, improve per trip revenue for drivers and red…