Online Edge Flow Prediction Over Expanding Simplicial Complexes

Simplicial convolutional filters can process signals defined over levels of a simplicial complex such as nodes, edges, triangles, and so on with applications in e.g., flow prediction in transportation or financial networks. However, the underlying topology expands over time in a way that new edges and triangles form. For example, in a...

Online Vector Autoregressive Models Over Expanding Graphs

Current spatiotemporal learning methods for complex data exploit the graph structure as an inductive bias to restrict the function space and improve data and computation efficiency. However, these methods work principally on graphs with a fixed size, whereas in several applications there are expanding graphs where new nodes join the network; e.g...

For What It's Worth: Humans Overwrite Their Economic Self-interest to Avoid Bargaining With AI Systems

As algorithms are increasingly augmenting and substituting human decision-making, understanding how the introduction of computational agents changes the fundamentals of human behavior becomes vital. This pertains to not only users, but also those parties who face the consequences of an algorithmic decision. In a controlled experiment with 480...

Regulations Aware Motion Planning for Autonomous Surface Vessels in Urban Canals

In unstructured urban canals, regulation-aware interactions with other vessels are essential for collision avoidance and social compliance. In this paper, we propose a regulations aware motion planning framework for Autonomous Surface Vessels (ASVs) that accounts for dynamic and static obstacles. Our method builds upon local model predictive...

Learning Expanding Graphs for Signal Interpolation

Performing signal processing over graphs requires knowledge of the underlying fixed topology. However, graphs often grow in size with new nodes appearing over time, whose connectivity is typically unknown; hence, making more challenging the downstream tasks in applications like cold start recommendation. We address such a challenge for signal...

Incremental Nonlinear Dynamic Inversion Control of Long-Stroke Pneumatic Actuators

Pneumatic cylinders provide an environmentfriendly actuation means by minimizing the leakage of any harmful industrial fluids, as occurs for hydraulic actuators. However, pneumatic actuation has not been utilized widely for industrial servo applications due to its highly nonlinear nature. Incremental nonlinear dynamic inversion (INDI) is a form...

Active Semi-Supervised Learning for Diffusions on Graphs

Diffusion-based semi-supervised learning on graphs consists of diffusing labeled information of a few nodes to infer the labels on the remaining ones. The performance of these methods heavily relies on the initial labeled set, which is either generated randomly or using heuristics. The first sometimes leads to unsatisfactory results because...

Collective Data Analytics Capability Building Processes: a Governance Model

Collective data analytics capability building offers opportunities for government organizations to develop capabilities that would be difficult to develop on their own. However, research on that topic is scarce and there is still a limited understanding of how collective data analytics capability building processes contribute to the value...

Activity Dependent Multichannel ADC Architecture using Level Crossing Quantisation for Atrial Electrogram Recording

This paper presents a novel multichannel level-crossing (MLC) ADC architecture aimed at recording atrial electrograms from multiple channels. The proposed architecture combines synchronous sampling with level-crossing (LC) quantisation to achieve activity dependent operation while recording from multiple channels simultaneously. In the...

Applications of Computation-In-Memory Architectures based on Memristive Devices

Today's computing architectures and device technologies are unable to meet the increasingly stringent demands on energy and performance posed by emerging applications. Therefore, alternative computing architectures are being explored that leverage novel post-CMOS device technologies. One of these is a Computation-in-Memory architecture based on...