Events

This presentation investigates the role of modularity in advancing neuroevolution algorithms and proposes novel techniques that exploit this property to evolve efficient neural networks.

This talk will discuss a flexible survival analysis method that simultaneously accommodates dependent censoring and eliminates the requirement for specifying the copula.

We target conveying more complex information into multi-modal dialogue generation with events, knowledge and reasoning.

With the massive development in Information Communication Technology (ICT) in the past decades, people nowadays are used to fast-paced and real-time information exchange and public opinion deliberation.

This PhD research investigates the critical yet under-explored role of metadata in evaluating the quality of repurposed data.

In this research, we explore the under-researched and challenging area of full-body manipulation tasks for robotics.

In this talk, I will introduce a few works that have been done in my group showing the trends from close-set to open-set and to open-world.

In this thesis, we comprehensively investigate the aforementioned challenges and build effective, secure federated online learning to rank methods.

This research addresses the imperative need for informative representation learning through multimodal data fusion techniques.

This seminar introduces several innovations to address challenges of federated GNN-based recommender systems including performance degradation, inflexible architectures, slow convergence, and the demand for substantial local storage resources.

The overall aim of this research is to advance the field of machine unlearning in the aspects of causal insights, efficiency, and effectiveness.

This seminar explores the latest advancements in time series analysis by examining three key aspects: pattern recognition, on-device applications, and complex multivariate time series modelling.

This presentation investigates the potential of large language models (LLMs) for generating personalized online advertisements tailored to specific personality traits and the implications of such technology for political advertising, combining insights from two studies.

This presentation explores best practices for building AI/ML and generative AI (Gen AI) models responsibly on AWS.

Legal case retrieval (LCR) is a specialised and indispensable retrieval task that focuses on retrieving relevant cases given a query case.

In this talk, we first discuss one of the most important aspects of the filter bubble, recommendation diversity, particularly diversified recommendation models and full-stage large-scale online experiments on short-video platforms.

This one-day face-to-face course will bring industry professionals together for dialogue and sharing of knowledge to better understand oils for transformer and tap changer applications and testing thereof. This course will deliver the theoretical background information necessary along with practical experience from industry experts to understand the issues of oils and their application in a modern power system. This course is aimed at procurement, asset strategies, operations and maintenance managers and engineers in generation, transmission and distribution, renewables manufacturing mining industrial and infrastructure organisations.

This study investigates strategies to effectively handle challenges related to data silos.

Continual graph learning (CGL) is purposed to continuously update a graph model with graph data being fed in a streaming manner.

The research findings provide novel insights and understanding of the sensemaking processes in various settings and contribute to modelling practice and the design of supporting tools.

This research introduces a corresponding attack method to uncover the actual vulnerabilities within recommender systems.

Join us at the 2023 Summer of AI (SAI) from 11-15 December, where you'll hear from UQ's two new Professors of AI, as well as some of our leading academics in the field.

This talk will provide an inside view of what AI/ML/DL infrastructure UQ RCC has available right now and an early view of what is coming next.

Join us at the 2023 Summer of AI (SAI) from 11-15 December, where you'll hear from UQ's two new Professors of AI, as well as some of our leading academics in the field.

The talk will give some background on diffusion as a Generative Model for images, and text-based imaging.