Computer Vision

No.24-03 Towards Open-World Object Segmentation and Detection

Segmentation and detection are two fundamental and classical tasks in computer vision. In recent years, significant attention has been devoted to the open-vocabulary object segmentati...

From Monash University, Apr 10, 2024

No.23-04 Multi-Domain Few-Shot Image Classification

Most existing few-shot classification methods only consider generalization on one dataset (i.e., single-domain), failing to transfer across various seen and unseen domains. In this ta...

From Australian National University, Mar 15, 2023

No.23-03 Score based Diffusion Models and Their Applications

Generative models show great potential in generating new samples, which have been extensively investigated in 2D/3D vision tasks. Among them, the adversarial training based models, e....

From Australian National University, Mar 01, 2023

Advancing Machine Perception for Artificial Intelligence Systems

Artificial intelligence (AI) techniques have impacted on our lives profoundly, such as providing more secured and resilient social environments and assisting more accurate medical dia...

From University of Technology Sydney, Oct 05, 2022


LibAUC: A deep learning library for X-risk Optimization

In this talk, I will present our recent research efforts of developing a deep learning library called LibAUC, which is applicable for solving a variety of compositional measures. I w...

From Texas A&M University, Oct 26, 2022

Information Retrieval

No.23-13 Task-aware Retrieval with Instructions

We study the problem of retrieval with instructions, where users of a retrieval system explicitly describe their intent along with their queries. We aim to develop a general-purpose t...

From University of Washington, Aug 02, 2023

No.23-10 SEINE: SEgment-based Indexing for NEural Information Retrieval

Many early neural Information Retrieval (NeurIR) methods are re-rankers that rely on a traditional first-stage retriever due to expensive query time computations. Recently, representa...

From Georgetown University, May 03, 2023

A Non-Factoid Question-Answering Taxonomy

Non-factoid question answering (NFQA) is a challenging and under-researched task that requires constructing long-form answers, such as explanations or opinions, to open-ended non-fact...

From RMIT University, Nov 09, 2022

Information Systems

No.23-22 Process Mining: Opportunities and Challenges

In recent years, significant advances in extended reality (XR) and AI have offered novel, promising ways to visualise and eventually better understand large and complex data. Immersio...

From University of Queensland, Sep 13, 2023

No.23-05 A magic ingredient, a secret spice, a special blend, for it can all be nice!' The Human Quotient for Better AI Systems

The unprecedented rise in the adoption of artificial intelligence techniques and automation in many contexts is concomitant with the shortcomings of such technology concerning robustn...

From Delft University of Technology, Mar 22, 2023

No.23-0301 Efficient Distributed Complex Event Processing

Complex event processing emerged as a computational paradigm to detect patterns in event streams based on the continuous evaluation of event queries. Once such queries are evaluated i...

From Humboldt-Universität zu Berlin (HU), Mar 09, 2023

No.23-01 Escaping the Echo Chamber: The Quest for Normative News Recommender Systems

Recommender systems and social networks are often faulted to be the cause for creating Echo Chambers – environments where people mostly encounter news that match their previous choice...

From University of Zurich, Feb 22, 2023


No.23-02 Seven Algorithms for the Same Task (Testing Uniformity)

Suppose you get a set of (independent) data points in some discrete but huge domain {1,2,…,k}, and want to determine if this data is uniformly distributed. This is a basic and fundame...

From University of Sydney, Mar 08, 2023

Digital Twin

No.23-09 Mobility Digital Twin for Connected and Automated Vehicles

A Digital Twin is a digital replica of a living or nonliving physical entity, and this emerging technology attracted extensive attention from different industries during the past deca...

From Purdue University, Apr 26, 2023


No.23-11 Building Experiment Tracking at Scale with Weights & Biases

Building experiments doesn’t just end once the model is deployed. Teams need to monitor their models in production and use their findings to iterate further. Especially when dealing w...

From Weights & Biases, May 10, 2023


No.24-01 Filter Bubble in Recommender System: Diversity and Beyond

Recommender system has reshaped how we access information in today’s world, make relevant content more accessible to everyone. However, it has also resulted in some negative side-effe...

From Tsinghua University, Mar 07, 2024

No.23-12 An Introduction to Sequential/Session-based Recommendation

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 t...

From University of Technology Sydney, May 17, 2023

Machine Learning

No.23-19 Graph Neural Networks for Large Dynamic Graphs

In real-world applications such as social networks, financial transactions, and recommender systems, graph-structured data is frequently dynamic, with the nodes and edges of the graph...

From DATA61-CSIRO, Sep 13, 2023

No.23-16 Generalized Out-of-distribution Detection: Theory and Algorithm

Out-of-distribution (OOD) detection is vital for ensuring the safety and reliability of artificial intelligence systems. It represents a novel and trending area in machine learning an...

From University of Technology Sydney, Aug 23, 2023

No.23-15 How to Detect Out-of-Distribution Data in the Wild? Challenges, Research Progress and Path Forward

When deploying machine learning models in the open and non-stationary world, their reliability is often challenged by the presence of out-of-distribution (OOD) samples. Since data shi...

From University of Wisconsin-Madison, Aug 16, 2023


No.23-20 Immersive Data Visualisation and Interactive AI

In recent years, significant advances in extended reality (XR) and AI have offered novel, promising ways to visualise and eventually better understand large and complex data. Immersio...

From University of Queensland, Sep 13, 2023


Welcome to UQ Data Science Seminar Series!

This UQ Data Science seminar series aims to bring together students and senior researchers to discuss about their research, intending to have a diverse set of talks and speakers on to...

From Introduction, Jan 01, 2023


No.24-02 Building AI/ML & Gen AI responsibly on AWS

This presentation explores best practices for building AI/ML and generative AI (Gen AI) models responsibly on AWS. We’ll explore real use cases where these technologies are driving va...

From Amazon, Mar 13, 2024


No.24-04 Deep Copula-Based Survival Analysis for Dependent Censoring

Censoring is the central problem in survival analysis where either the time-to-event (for instance, death) or the time-to-censoring (such as loss of follow-up) is observed for each sa...

From University of Newcastle, Apr 24, 2024


No.24-06 Generative Sequential Recommendation

In this talk, we first introduce the Sequential Recommendation problem and draw parallels between language modelling and recommender systems. To set the stage, we also briefly cover s...

From University of Glasgow, May 22, 2024


No.24-05 Efficient and Elastic Large Models

Generative LLMs are transforming multiple industries and have proven to be robust for multitude of use cases across industries and settings. One of the key impediments to their widesp...

From Google Research India, May 17, 2024