Events

DH Asia Webinar Series: “A Sandbox for Humanistic Data Scientists” by Dr. Setsuko Yokoyama

ISTD PhD Oral Defense Seminar by Joel Ong – Modern Portfolio Construction with Advanced Deep Learning Models

A key challenge in data-driven decision-making is the presence of estimation errors in the prediction models, which tend to be amplified by the subsequent optimization model — a phenomenon that is often referred to as the Optimizer’s Curse. A contemporary approach to combat such estimation errors is offered by distributionally robust problem formulations that consider all data-generating distributions close to the empirical distribution derived from historical samples, where ‘closeness’ is determined by the Wasserstein distance. While those techniques show significant promise in problems where all input features are continuous, they scale exponentially when categorical features are present. This work demonstrates that such mixed-feature problems can indeed be solved in polynomial time. We present a practically efficient algorithm to solve mixed-feature problems and compare our method against alternative techniques.

ISTD PhD Oral Defense Seminar presented by Perry Lam – Sparsity in Text-to-Speech

DH Asia Webinar Series: “Recreating Chinese Mythical Creatures in the Digital Age” by Dr. Kaby Wing-Sze Kung

The Design Ethics of Autonomous Machines

DH Asia Webinar Series: “The Tale of Genji: Where Traditional Research Meets Digital Technology” by Ayano Takeuchi

Adriel Kuek (DSO National Laboratories) – An Introduction to AI in Defence R&D

ISTD PhD Oral Defense presented by Gong Jia – Towards Data Efficient, Reliable and Flexible 3D Digital Human Modeling

Mark Sin (Apple Inc.) – What in School Helped my Career?