Sort by
Refine Your Search
-
software frameworks, algorithms, robust testing and validation methods, and/or empirically validated solutions that contribute directly to social good, promoting trust, fairness, transparency, and
-
. With the widespread adoption of ML algorithms for data analysis and decision-making, preserving the privacy of individuals' data has become a paramount concern. The project focuses on exploring
-
The relationship between the information-theoretic Bayesian minimum message length (MML) principle and the notion of Solomonoff-Kolmogorov complexity from algorithmic information theory (Wallace and
-
. Wallace (1996). MML estimation of the parameters of the spherical Fisher Distribution. In S. Arikawa and A. K. Sharma (eds.) , Proc. 7th International Workshop on Algorithmic Learning Theory (ALT'96
-
the given non-classical logic. The proof of the claim contains an algorithm for deciding whether an arbitrary formula is true or else false! This proof can then be exported automatically to produce a formally
-
group of experts to predict (probabilistically) whether these occupations will be automated, augmented or unaffected by emerging technologies. Using this data, a classification algorithm is then trained
-
This project aims to employ advanced machine learning techniques to analyse text, audio, images, and videos for signs of harmful behaviour. Natural language processing algorithms are utilized
-
monthly stipends. This research direction will involve close collaborations with Prof Lin Chen of China. The supervisor is currently engaged in a joint research project with Prof Lin Chen that will fund
-
" (with Prof Kris Helmerson) "High-bandwidth continuous magnetic sensing of an ensemble of electric spins" (with Prof Kris Helmerson) "Developing a spatially sensitive optical magnetometer catheter probe
-
with leading researchers in glass science/engineering and diffraction physics/crystallography in Australia and around the world. "Local structure and symmetry in metallic glasses" (with Assoc Prof Scott