Recent machine learning techniques such as deep learning and reinforcement learning were built on specific assumptions of the underlying data generation process.  Financial time series frequently do not satisfy these assumptions.  In this talk, we discuss the possible problems if these techniques are applied blindly.  The solutions to these problems are in general problem specific.  However, some of the pain can be alleviated by combining recent machine learning techniques with more classical statistical and econometrics insights.  We will discuss these probable solutions with examples.

9 Dec 2021
2pm - 3:30pm
Where
Room 2502 (Lifts 25/26)
Speakers/Performers
Prof. Jack CK WONG
Professor of Science Practice, HKUST
Organizer(S)
Department of Mathematics
Contact/Enquiries
Payment Details
Audience
Alumni, Faculty and staff, PG students, UG students
Language(s)
English
Other Events
24 May 2024
Seminar, Lecture, Talk
IAS / School of Science Joint Lecture - Confinement Controlled Electrochemistry: Nanopore beyond Sequencing
Abstract Nanopore electrochemistry refers to the promising measurement science based on elaborate pore structures, which offers a well-defined geometric confined space to adopt and characterize sin...
9 May 2024
Seminar, Lecture, Talk
IAS / School of Science Joint Lecture – Deconstructive Homologation of Ethers and Amides
Abstract Preparation of diverse homologs from lead compounds has been a common and important practice in medicinal chemistry. However, homologation of many functional groups, such as ethers an...