Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
increase in data volume, it is necessary to adopt parallelism techniques to achieve reasonable query response time. The main focus will be on parallel query processing, which is the main driver for Big Data
-
will commence with, in parallel, the survey for collecting the data and a comparison of machine learning methods on artificial pseudo-randomly generated data. The world will see all too many changes
-
will commence with, in parallel, the survey for collecting the data and a comparison of machine learning methods on artificial pseudo-randomly generated data. The world will see all too many changes
-
NMT models where sufficient parallel corpora are not available (eg [1,2]). This project investigates methods to enable high performing NMT in low-resource scenarios. [1] Neural Machine Translation for
-
NMT models where sufficient parallel corpora are not available (eg [1,2]). This project investigates methods to enable high performing NMT in low-resource scenarios. [1] Neural Machine Translation for
-
[Malaysia Campus- VPSSP] An AI-Informed Planetary Health Framework for Equitable AMR Risk Mitigation
modelling from Project 1, we will conduct focus groups and interviews with communities in high- and low-risk zones to capture local knowledge, behaviours, and risk perceptions related to AMR. In parallel
-
roles in both Australia and Hong Kong. In a parallel sporting career, Chris was also a two-time Olympian in 1976 and 1980 and the Head Coach of the Australian Track and Field Team at the Sydney Olympic
-
Primary supervisor Levin Kuhlmann Co-supervisors Damian Anderson Trang Le Research area Machine Learning This project will develop general cutting edge generative AI and natural language processing
-
Primary supervisor Levin Kuhlmann Co-supervisors Damian Anderson Trang Le Research area Machine Learning This project will develop general cutting edge generative AI and natural language processing
-
(mobile-edge-cloud continuum) federated learning architecture and develop context-aware models and schemes for optimising distribution, storage and processing of tasks and data in each layer. Required