Events

Speaker: Tianren Wang
This project will study the explicit form of a latent space to make the learning process more accurate and interpretable.

Speaker: Sharon Yixuan Li (University of Wisconsin-Madison)
I will introduce a new algorithmic framework, which jointly optimizes for both accurate classification of ID samples, and reliable detection of OOD data.

Speaker: Chaoyi (Joey) Li

Speaker: Prof Phoebe Chen (La Trobe University)
There is a large number of possible applications that can benefit from the analysis of multimedia data.

Speaker: Akari Asai (University of Washington)
We study the problem of retrieval with instructions, where users of a retrieval system explicitly describe their intent along with their queries.

This two-day face-to-face course will bring industry professionals together for dialogue and sharing of knowledge to better understand the operation of tap changers, as well as the design, maintenance and testing thereof. This tap changer course will deliver the theoretical background information necessary along with "hands on" practical experience to understand the issues of tap changes faced by modern power systems and their operators. 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 organizations.

Speaker: Sarah Abdulaziz Alhammad (BCompSc, MCompSc)

Speaker: Xin Xia

Speaker: Yunke Qu

Speaker: Xinyi Gao
This comprehensive experimental study demonstrates that SNS consistently outperforms existing methods in different benchmark datasets.

Speaker: Hechuan Wen
Causal inference is increasingly important in guiding decision-making in high-stake domains, such as healthcare, education, e-commerce, etc.

Speaker: Nathaniel du Preez-Wilkinson

Speaker: Peter Bohm

Speaker: Haoyu Ren (Technical University of Munich)

Speaker: Shengyao Zhuang

Speaker: Dr Shoujin Wang (University of Technology Sydney)
In recent years, sequential/session-based recommendations have emerged as a new recommendation paradigm to well model users’ dynamic and short-term preferences for more accurate and timely recommendations.

Speaker: Andrea Parker, Growth ML Engineer (Weights & Biases)
Join us to learn all about experiment tracking at scale with Pachyderm and Weights & Biases.

Speaker: Dr Grace Hui Yang (Georgetown University)
We propose a novel SEgment-based Neural Indexing method, SEINE, which provides a general indexing framework that can flexibly support a variety of interaction-based neural retrieval methods.

Speaker: Prof Stefan Böttcher - Universität Paderborn (Germany)
This talk gives an overview of the key ideas behind grammar-based compression techniques for strings, trees, and graphs.

Speaker: Dr Ziran Wang (Purdue University)
In this talk, a Mobility Digital Twin (MDT) framework is introduced, which is defined as an Artificial Intelligence (AI)-based data-driven cloud-edge-device framework for mobility services.

Speaker: Dr Qiongkai Xu, The University of Melbourne
This seminar will present research towards trustworthy AI systems.

Speaker: Rischan Mafrur

Speaker: Dr Shixun Huang (RMIT University)
In this talk, recent advances under multiple fields (i.e., data mining, viral marketing and urban computing) of graph analytics will be introduced.

Speaker: Zhuoxiao (Ivan) Chen
Our research focuses on optimising the model performance for 3D object detection, especially when the labelling budget is limited.

Speaker: Dr Yiliao Song, RMIT University
Real-time decision-making for streaming data is facing a common but challenging problem, concept drift.