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The 2021 edition of AAMAS, the International Conference on Autonomous Agents and Multiagent Systems, took place from the 3rd to 7th of May 2021 (aamas2021.soton.ac.uk). This year it was organized in the form of a virtual event and attracted over 1,000 ...

We introduce a Model AI Assignment (Neller et al., 2021) where students combine various techniques from a deep learning course to build a denoising autoencoder (Shen, Mueller, Barzilay, & Jaakkola, 2020) for news headlines. Students then use this ...

This section is compiled from reports of recent events sponsored or run in cooperation with ACM SIGAI. In general these reports were written and submitted by the conference organisers.

This section features information about upcoming events relevant to the readers of AI Matters, including those supported by SIGAI. We would love to hear from you if you are are organizing an event and would be interested in cooperating with SIGAI.For ...

In recent years, deep learning models have become ubiquitous in industry and academia alike. Modern deep neural networks can solve one of the most complex problems today, but coming with the price of massive compute and storage requirements. This makes ...

The Whittle index policy is a heuristic that has shown remarkable good performance (with guaranted asymptotic optimality) when applied to the class of problems known as multi-armed restless bandits. In this paper we develop QWI, an algorithm based on Q-...

The workshop aims to revisit the development and the application of reinforcement learning techniques in the various application areas covered by the SIGMETRICS conference. Topics include but are not limited to queueing networks (scheduling, resource ...

The SIGEVO Best Dissertation Award was created in 2019 to recognize excellent thesis research by doctoral candidates in the field of evolutionary computing. Doctoral dissertation awards are also given by other Special Interest Groups of ACM, such as ...

Graph Neural Networks (GNNs), a generalization of deep neural networks on graph data have been widely used in various domains, ranging from drug discovery to recommender systems. However, GNNs on such applications are limited when there are few ...

Electric power substations are experiencing an accelerated pace of digital transformation including the deployment of LAN-based IEC 61850 communication protocols that facilitate accessibility to substation data while also increasing remote access points ...

Introduction. We have seen significant advances in the state of the art in natural language processing (NLP) over the past few years [20]. These advances have been driven by new neural network architectures, in particular the Transformer model [19], as ...

In this paper we present C_oR_oNN_a a deep sequential framework for epidemic prediction that leverages a flexible combination of sequential and convolutional components to analyse the transmission of COVID-19 and, perhaps, other undiscovered viruses. ...

This section features information about upcoming events relevant to the readers of AI Matters, including those supported by SIGAI. We would love to hear from you if you are are organizing an event and would be interested in cooperating with SIGAI. For ...

This article summarizes our recent journal paper entitled "Search trajectory networks: A tool for analysing and visualising the behaviour of metaheuristics", where we propose a graph-based, data-driven modeling tool (STNs) to visualize and analyze the ...

In this paper, we provide a fine-grain machine learning-based method, PerfNetV2, which improves the accuracy of our previous work for modeling the neural network performance on a variety of GPU accelerators. Given an application, the proposed method can ...

Semantic classification of scientific literature using machine learning approaches is challenging due to the difficulties in labeling data and the length of the texts [2, 7]. Most of the work has been done for keyword-based categorization tasks, which ...

Amyotrophic Lateral Sclerosis (ALS) is a rare neurodegenerative disease that causes a rapid decline in motor functions and has a fatal trajectory. ALS is currently incurable, so the aim of the treatment is mostly to alleviate symptoms and improve ...

I am fascinated by how rich and flexible human intelligence is. From a quick glance at the scenes in Figure 1A, we effortlessly recognize the 3D geometry and texture of the objects within, reason about how they support each other, and when they move, ...

Supervised machine learning methods that use neural networks ("deep learning") have yielded substantial improvements to a multitude of Natural Language Processing (NLP) tasks in the past decade. Improvements to Information Retrieval (IR) tasks, such as ...

When experiencing an information need, users want to engage with a domain expert, but often turn to an information retrieval system, such as a search engine, instead. Classical information retrieval systems do not answer information needs directly, but ...