All Talks
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.23-13 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.23-12 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
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.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
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.23-05 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.23-04 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