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 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: A/Prof Ujwal Gadiraju (Delft University of Technology, the Netherlands)
This talk will discuss the intriguing and pertinent role of human input in propelling better AI technology in the quickly evolving age of generative models.
Speaker: Dr Matthias Weidlich (Humboldt-Universität zu Berlin (HU))
In this talk, we present some of our recent results on achieving such distribution with the model of MuSE graphs as well as optimizations that rely on push-pull-communication.
Speaker: Dr Jing Zhang (Australian National University)
In this talk, we will explain the basic idea of score-based diffusion models, and explore its potential in 2D/3D vision tasks.
Speaker: Dr Clément Canonne (University of Sydney)
In this talk, I will survey and discuss seven algorithms for uniformity testing, and explain some of their (dis)advantages.
Speaker: Prof Abraham Bernstein (University of Zurich)
This talk highlights that computer science needs to increasingly engage with both the social and normative challenges of our work, possibly producing a new understanding of our discipline.
Speaker: Professor Shane Culpepper, RMIT University
In this talk, we will discuss a novel multi-task learning approach which can be used to produce more effective neural ranking models.
