BiomedBench: A benchmark suite of TinyML biomedical applications for low-power wearables

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Background: Compared with conventional unimodal analysis, understanding how brain function and structure relate to one another opens a new biologically relevant assessment of neural mechanisms. However, how function-structure dependencies (FSDs) evolve thr ...

Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

The objective of meta-learning is to exploit knowledge obtained from observed tasks to improve adaptation to unseen tasks. Meta-learners are able to generalize better when they are trained with a larger number of observed tasks and with a larger amount of ...

Model compression techniques have lead to a reduction of size and number of computations of Deep Learning models. However, techniques such as pruning mostly lack of a real co-optimization with hardware platforms. For instance, implementing unstructured pru ...

Stochastic Maximum Likelihood (SML) is a popular direction of arrival (DOA) estimation technique in array signal processing. It is a parametric method that jointly estimates signal and instrument noise by maximum likelihood, achieving excellent statistical ...

In recent years, population aging and the consequent higher incidence of noncommunicable diseases, have increased the need for long-term health monitoring. Moreover, as healthcare cost is projected to grow substantially by 2030 in OECD countries, the deman ...

The articles in this special section focus on graph signal processing. Generically, the networks that sustain our societies can be understood as complex systems formed by multiple nodes, where global network behavior arises from local interactions between ...

Many factors influence learners' performance on an activity beyond the knowledge required. Learners' on-task effort has been acknowledged for strongly relating to their educational outcomes, reflecting how actively they are engaged in that activity. Howeve ...

In a non-uniform memory access machine, the placement of software threads to hardware cores can have a significant effect on the performance of concurrent applications. Detecting the best possible placement for each application is a necessity for thread sc ...

Distributed graph signal processing methods require that the graph nodes communicate by exchanging messages. These messages have a finite precision in a realistic network, which may necessitate to implement quantization. Quantization, in turn, generates er ...

In this paper we describe our approach to teaching applied digital signal processing (DSP) using freely-available software and inexpensive off-the-shelf hardware components. The pedagogical framework is built around simple real-time audio processing algori ...

Photosensing has proven to be highly useful in biomedical research and medical care. Being able to detect and quantify the light emitted by fluorescent or bioluminescent reporters has significantly participated in the development of new cancer treatments a ...

Despite the high costs of acquisition and maintenance of modern data centers, machine resource utilization is often low. Servers running online interactive services are over-provisioned to support peak load (which only occurs for a fraction of the time), d ...

Graph spectral analysis can yield meaningful embeddings of graphs by providing insight into distributed features not directly accessible in nodal domain. Recent efforts in graph signal processing have proposed new decompositions-for example, based on wavel ...

In this work, we present a reproduction of the paper of Bertinetto et al. ”Meta- learning with differentiable closed-form solvers” as part of the ICLR 2019 Reproducibility Challenge. In successfully reproducing the most crucial part of the paper, we reach ...

It has often been found that students appreciate hands-on work, and find that they learn more with courses that include a project than those relying solely on conventional lectures and tests. This type of project driven learning is a key component of “Inqu ...

Data is pervasive in today's world and has actually been for quite some time. With the increasing volume of data to process, there is a need for faster and at least as accurate techniques than what we already have. In particular, the last decade recorded t ...

An emerging way to deal with high-dimensional non-euclidean data is to assume that the underlying structure can be captured by a graph. Recently, ideas have begun to emerge related to the analysis of time-varying graph signals. This work aims to elevate th ...

The recent breakthrough in metamaterial-based optical computing devices (2014 Science 343 160) has inspired a quest for similar systems in acoustics, performing mathematical operations on sound waves. So far, acoustic analog computing has been demonstrated ...

Digital silicon photo-multipliers (SiPMs) have emerged in the recent past as a viable low cost alternative to photomultiplier tubes in positron emission tomography systems, providing multiple timestamps, energy and scintillation coordinates at high spatial ...

BiomedBench: A benchmark suite of TinyML biomedical applications for low-power wearables

Chattez avec Graph Search

Longitudinal Analysis of Brain Function-Structure Dependencies in 22q11.2 Deletion Syndrome and Psychotic Symptoms

EdgeAI-Aware Design of In-Memory Computing Architectures

Dif-MAML: Decentralized Multi-Agent Meta-Learning

Structured and tiled-based pruning of Deep Learning models targeting FPGA implementations

SiML: Sieved Maximum Likelihood for Array Signal Processing

System-level Design of Adaptive Wearable Sensors for Health and Wellness Monitoring

Graph Signal Processing: Foundations and Emerging Directions [From the Guest Editors]

Predicting learners' effortful behaviour in adaptive assessment using multimodal data

Thread-Placement Learning

Optimized Quantization in Distributed Graph Signal Processing

Teaching Practical DSP with Off-the-Shelf Hardware and Free Software

Analysis of photosensor frontends for biomedical applications: a focus on noise

Efficient Workload Colocation in Modern Data Centers

Guided graph spectral embedding: Application to the C. elegans connectome

[Re] Meta learning with differentiable closed-form solvers

Inquiry-Based Learning with RoboGen: An Open-Source Software and Hardware Platform for Robotics and Artificial Intelligence

Robust and Efficient Data Clustering with Signal Processing on Graphs

A Time-Vertex Signal Processing Framework

Performing mathematical operations using high-index acoustic metamaterials

A Sensor Network Architecture for Digital SiPM-Based PET Systems