Title
Topic
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‘Disentangling Node Attributes From Graph Topology for Improved Generalizability in Link Prediction’
“Link prediction is a crucial task in graph machine learning with diverse applications. We explore the interplay between node attributes and graph topology and demonstrate that incorporating pre-trained node attributes improves the generalization power of link prediction models. Our proposed method, UPNA (Unsupervised Pre-training of Node Attributes), solves the inductive link prediction problem by learning a function that takes a pair of node attributes and predicts the probability of an edge, as opposed to Graph Neural Networks, … which can be prone to topological shortcuts in graphs with power-law degree distribution.” Find the paper and full list of authors at…
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‘Can Euclidean Symmetry Be Leveraged in Reinforcement Learning and Planning?’
“In robotic tasks, changes in reference frames typically do not influence the underlying physical properties of the system, which has been known as invariance of physical laws.These changes, which preserve distance, encompass isometric transformations such as translations, rotations, and reflections, collectively known as the Euclidean group. In this work, we delve into the design of improved learning algorithms for reinforcement learning and planning tasks that possess Euclidean group symmetry.” Find the paper and full list of authors at ArXiv.
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‘Leveraging Structure for Improved Classification of Grouped Biased Data’
“We consider semi-supervised binary classification for applications in which data points are naturally grouped … and the labeled data is biased. … The groups overlap in the feature space and consequently the input-output patterns are related across the groups. To model the inherent structure in such data, we assume the partition-projected class-conditional invariance across groups. … We demonstrate that under this assumption, the group carries additional information about the class, over the group-agnostic features, with provably improved area under the ROC curve.” Find the paper and full list of authors in the AAAI Conference on Artificial Intelligence proceedings.
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‘Accelerating Neural MCTS Algorithms Using Neural Sub-Net Structures’
“Neural MCTS algorithms are a combination of Deep Neural Networks and Monte Carlo Tree Search (MCTS) and have successfully trained Reinforcement Learning agents in a tabula-rasa way. … However, these algorithms … take a long time to converge, which requires high computational power and electrical energy. It also becomes difficult for researchers without cutting-edge hardware to pursue Neural MCTS research. We propose Step-MCTS, a novel algorithm that uses subnet structures, each of which simulates a tree that provides a lookahead for exploration.” Find the paper and full list of authors in the International Conference on Autonomous Agents and Multiagent Systems…
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‘Sustainable HCI Under Water: Opportunities for Research with Oceans, Coastal Communities and Marine Systems’
“Although the world’s oceans play a critical role in human well-being, they have not been a primary focus of the sustainable HCI (SHCI) community to date. In this paper, we present a scoping review to show how concerns with the oceans are threaded throughout the broader SHCI literature and to find new research opportunities. We identify several themes that could benefit from focused SHCI research, including marine food sources, culture and coastal communities, ocean conservation, and marine climate change impacts and adaptation strategies.” Find the paper and full list of authors at the Conference on Human Factors in Computing Systems.
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‘Rapid Convergence: The Outcomes of Making PPE During a Healthcare Crisis’
“The U.S. National Institute of Health (NIH) 3D Print Exchange is a public, open-source repository for 3D printable medical device designs with contributions from clinicians, expert-amateur makers, and people from industry and academia. In response to the COVID-19 pandemic, the NIH formed a collection to foster submissions of low-cost, locally manufacturable personal protective equipment (PPE). We evaluated the 623 submissions in this collection … [and] found an immediate design convergence to manufacturing-focused remixes of a few initial designs affiliated with NIH partners and major for-profit groups.” Find the paper and full list of authors at ACM Transactions on Computer-Human Interaction.
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‘OPTIMISM: Enabling Collaborative Implementation of Domain Specific Metaheuristic Optimization’
“For non-technical domain experts and designers it can be a substantial challenge to create designs that meet domain specific goals. This presents an opportunity to create specialized tools that produce optimized designs in the domain. However, implementing domain-specific optimization methods requires a rare combination of programming and domain expertise. … We present OPTIMISM, a toolkit which enables programmers and domain experts to collaboratively implement an optimization component of design tools.” Find the paper and full list of authors in the Conference on Human Factors in Computing Systems proceedings.
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Understanding human decision-making during supply chains shortages
“Research conducted by mechanical and industrial engineering associate professor Jacqueline Griffin, professor Ozlem Ergun, and professor Stacy Marsella [in the Khoury College of Computer science, titled] ‘Agent-Based Modeling of Human Decision-Makers Under Uncertain Information During Supply Chain Shortages’ was published in the proceedings from the 2023 International Conference on Autonomous Agents and Multiagent Systems.”
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‘Predictors and Consequences of Pro-Environmental Behavior at Work’
“Increasingly, people are looking for meaning through their jobs, for employers that have a positive impact on the world, and for workplaces that promote mission-driven behavior. One such mission that is a growing priority is addressing climate change, especially for younger cohorts entering the workforce. Addressing the climate crisis will necessitate substantial changes at all levels of society, including organizational change. This paper examines individual, social, and contextual variables that are associated with pro-environmental behavior (PEB).” Find the paper and full list of authors at ResearchGate.
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‘Microbial Chemolithoautotrophs are Abundant in Salt Marsh Sediment Following Long-Term Experimental Nitrate Enrichment’
“Long-term anthropogenic nitrate (NO3−) enrichment is a serious threat to many coastal systems. Nitrate reduction coupled with the oxidation of reduced forms of sulfur is conducted by chemolithoautotrophic microbial populations in a process that decreases nitrogen (N) pollution. However, little is known about the diversity and distribution of microbes capable of carbon fixation within salt marsh sediment and how they respond to long-term NO3− loading. We used genome-resolved metagenomics to characterize the distribution, phylogenetic relationships, and adaptations important to microbial communities within NO3− enriched sediment.” Find the paper and full list of authors at FEMS Microbiology Letters.
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‘Workforce Ecosystems and AI’
“Companies increasingly rely on an extended workforce (e.g., contractors, gig workers … and technologies such as algorithmic management and artificial intelligence) to achieve strategic goals and objectives. When we ask leaders to describe how they define their workforce today, they mention a diverse array of participants, beyond just full- and part-time employees, all contributing in various ways. … Our ongoing research on workforce ecosystems demonstrates that managing work across organizational boundaries with groups of interdependent actors in a variety of employment relationships creates new opportunities and risks for both workers and businesses.” Find the paper and full list of authors…
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‘A Tool for Mutation Analysis in Racket’
“Racket is a functional programming language that is used to teach CS1 at many high schools and colleges. … In order to evaluate [mutation analysis’s] efficacy in our college’s introductory programming courses, we created a prototype mutation analysis tool for Racket. We describe the design and features of the tool and perform a feasibility study using two assignments from an intro CS course where student test suite thoroughness was evaluated by hand by human graders.” Find the paper and full list of authors in the 2023 IEEE International Conference on Software Testing Verification and Validation Workshop.
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‘SliceLens: Guided Exploration of Machine Learning Datasets’
“SliceLens is a tool for exploring labeled, tabular, machine learning datasets. To explore a dataset, the user selects combinations of features in the dataset that they are interested in. The tool splits those features into bins and then visualizes the label distributions for the subsets of data created by the intersections of the bins. SliceLens guides the user in determining which feature combinations to explore. Guidance is based on a user-selected rating metric, which assigns a score to the subsets created by a given combination of features.”
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‘”Everyone is Covered”: Exploring the Role of Online Interactions in Facilitating Connection and Social Support in Black Churches’
“Faith institutions provide social support and community care for many in the United States (U.S.). Notably, churches with predominantly Black populations have served as a site for social change and care provision. … However, the pandemic has emphasised how localising these care networks in physical spaces can limit access to social support. … Through interviews and focus groups with nine church members, we explore how hybrid faith communities that bridge offline and online contexts can enable social support and care provision.” Find the paper and full list of authors in the 2023 CHI Conference on Human Factors in Computing Systems…
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‘Game Level Blending Using a Learned Level Representation’
“Game level blending via machine learning, the process of combining features of game levels to create unique and novel game levels using Procedural Content Generation via Machine Learning (PCGML) techniques, has gained increasing popularity in recent years. However, many existing techniques rely on human-annotated level representations, which limits game level blending to a limited number of annotated games. … In this paper, we present a novel approach to game level blending … that can serve as a level representation for unannotated games and a unified level representation across games without … human annotation.” Find the paper and full list of…
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‘Typed-Untyped Interactions: A Comparative Analysis’
“The literature presents many strategies for enforcing the integrity of types when typed code interacts with untyped code. This article presents a uniform evaluation framework that characterizes the differences among some major existing semantics for typed–untyped interaction. Type system designers can use this framework to analyze the guarantees of their own dynamic semantics.” Find the paper and full list of authors in ACM Transactions on Programming Languages and Systems.
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‘EMShepherd: Detecting Adversarial Samples via Side-channel Leakage’
“Deep Neural Networks (DNN) are vulnerable to adversarial perturbations-small changes crafted deliberately on the input to mislead the model for wrong predictions. Adversarial attacks have disastrous consequences for deep learning-empowered critical applications. … Inspired by the fact that electromagnetic (EM) emanations of a model inference are dependent on both operations and data and may contain footprints of different input classes, we propose a framework, EMShepherd, to capture EM traces of model execution, perform processing on traces and exploit them for adversarial detection.” Find the paper and full list of authors at ArXiv.
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‘Injecting Language Workbench Technology Into Mainstream Languages’
“Eelco Visser envisioned a future where DSLs become a commonplace abstraction in software development. He took strides towards implementing this vision with the Spoofax language workbench. However, his vision is far from the mainstream of programming today. How will the many mainstream programmers encounter and adopt language workbench technology? We propose that the macro systems found in emerging industrial languages open a path towards delivering language workbenches as easy-to-adopt libraries.” Find the paper and full list of authors at the Dagstuhl Research Online Publication Server.