65 citations · 202 across the 26 of their papers we have counts for
26 papers
Learning-enabled multi-modal motion prediction in urban environments
Vinicius Trentin, Chenxu Ma, Jorge Villagra +1
Motion prediction is a key factor towards the full deployment of autonomous vehicles. It is fundamental in order to assure safety while navigating through highly interactive comple…
SaLoBa: Maximizing Data Locality and Workload Balance for Fast Sequence Alignment on GPUs
Seongyeon Park, Hajin Kim, Tanveer Ahmad +5
Sequence alignment forms an important backbone in many sequencing applications. A commonly used strategy for sequence alignment is an approximate string matching with a two-dimensi…
A Toolchain for Streaming Dataflow Accelerator Designs for Big Data Analytics: Defining an IR for Composable Typed Streaming Dataflow Designs
Matthijs A. Reukers
Tydi is an open specification for streaming dataflow designs in digital circuits, allowing designers to express how composite and variable-length data structures are transferred ov…
Tydi-lang: A Language for Typed Streaming Hardware
Yongding Tian, Matthijs A. Reukers, Zaid Al-Ars +4
Transferring composite data structures with variable-length fields often requires designing unique protocols, causing incompatibility issues and decreased collaboration among hardw…
QPack Scores: Quantitative performance metrics for application-oriented quantum computer benchmarking
Huub Donkers, Koen Mesman, Zaid Al-Ars +1
This paper presents the benchmark score definitions of QPack, an application-oriented cross-platform benchmarking suite for quantum computers and simulators, which makes use of sca…
Memory-Disaggregated In-Memory Object Store Framework for Big Data Applications
Robin Abrahamse, Akos Hadnagy, Zaid Al-Ars
The concept of memory disaggregation has recently been gaining traction in research. With memory disaggregation, data center compute nodes can directly access memory on adjacent no…
Benchmarking Apache Arrow Flight -- A wire-speed protocol for data transfer, querying and microservices
Tanveer Ahmad, Zaid Al Ars, H. Peter Hofstee
Moving structured data between different big data frameworks and/or data warehouses/storage systems often cause significant overhead. Most of the time more than 80\% of the total t…
Towards an Automatic Diagnosis of Peripheral and Central Palsy Using Machine Learning on Facial Features
C. V. Vletter, H. L. Burger, H. Alers +2
Central palsy is a form of facial paralysis that requires urgent medical attention and has to be differentiated from other, similar conditions such as peripheral palsy. To aid in f…
QKSA: Quantum Knowledge Seeking Agent -- resource-optimized reinforcement learning using quantum process tomography
Aritra Sarkar, Zaid Al-Ars, Harshitta Gandhi +1
In this research, we extend the universal reinforcement learning (URL) agent models of artificial general intelligence to quantum environments. The utility function of a classical…
DFL: High-Performance Blockchain-Based Federated Learning
Yongding Tian, Zhuoran Guo, Jiaxuan Zhang +1
Many researchers have proposed replacing the aggregation server in federated learning with a blockchain system to improve privacy, robustness, and scalability. In this approach, cl…
An Attention Module for Convolutional Neural Networks
Zhu Baozhou, Peter Hofstee, Jinho Lee +1
Attention mechanism has been regarded as an advanced technique to capture long-range feature interactions and to boost the representation capability for convolutional neural networ…
AutoReCon: Neural Architecture Search-based Reconstruction for Data-free Compression
Baozhou Zhu, Peter Hofstee, Johan Peltenburg +2
Data-free compression raises a new challenge because the original training dataset for a pre-trained model to be compressed is not available due to privacy or transmission issues.…
GPU Acceleration of 3D Agent-Based Biological Simulations
Ahmad Hesam, Lukas Breitwieser, Fons Rademakers +1
Researchers in biology are faced with the tough challenge of developing high-performance computer simulations of their increasingly complex agent-based models. BioDynaMo is an open…
QPack: Quantum Approximate Optimization Algorithms as universal benchmark for quantum computers
Koen Mesman, Zaid Al-Ars, Matthias Möller
In this paper, we present QPack, a universal benchmark for Noisy Intermediate-Scale Quantum (NISQ) computers based on Quantum Approximate Optimization Algorithms (QAOA). Unlike oth…
Fidel: Reconstructing Private Training Samples from Weight Updates in Federated Learning
David Enthoven, Zaid Al-Ars
With the increasing number of data collectors such as smartphones, immense amounts of data are available. Federated learning was developed to allow for distributed learning on a ma…
Privacy-Preserving Object Detection & Localization Using Distributed Machine Learning: A Case Study of Infant Eyeblink Conditioning
Stefan Zwaard, Henk-Jan Boele, Hani Alers +3
Distributed machine learning is becoming a popular model-training method due to privacy, computational scalability, and bandwidth capacities. In this work, we explore scalable dist…
SoFAr: Shortcut-based Fractal Architectures for Binary Convolutional Neural Networks
Zhu Baozhou, Peter Hofstee, Jinho Lee +1
Binary Convolutional Neural Networks (BCNNs) can significantly improve the efficiency of Deep Convolutional Neural Networks (DCNNs) for their deployment on resource-constrained pla…
Towards Lossless Binary Convolutional Neural Networks Using Piecewise Approximation
Baozhou Zhu, Zaid Al-Ars, Wei Pan
Binary Convolutional Neural Networks (CNNs) can significantly reduce the number of arithmetic operations and the size of memory storage, which makes the deployment of CNNs on mobil…
NASB: Neural Architecture Search for Binary Convolutional Neural Networks
Baozhou Zhu, Zaid Al-Ars, Peter Hofstee
Binary Convolutional Neural Networks (CNNs) have significantly reduced the number of arithmetic operations and the size of memory storage needed for CNNs, which makes their deploym…
Real-Time Face and Landmark Localization for Eyeblink Detection
Paul Bakker, Henk-Jan Boele, Zaid Al-Ars +1
Pavlovian eyeblink conditioning is a powerful experiment used in the field of neuroscience to measure multiple aspects of how we learn in our daily life. To track the movement of t…
BioDynaMo: a general platform for scalable agent-based simulation
Lukas Breitwieser, Ahmad Hesam, Jean de Montigny +10
Motivation: Agent-based modeling is an indispensable tool for studying complex biological systems. However, existing simulators do not always take full advantage of modern hardware…
Quantum circuit design for universal distribution using a superposition of classical automata
Aritra Sarkar, Zaid Al-Ars, Koen Bertels
In this research, we present a quantum circuit design and implementation for a parallel universal linear bounded automata. This circuit is able to accelerate the inference of algor…
QuASeR -- Quantum Accelerated De Novo DNA Sequence Reconstruction
Aritra Sarkar, Zaid Al-Ars, Koen Bertels
In this article, we present QuASeR, a reference-free DNA sequence reconstruction implementation via de novo assembly on both gate-based and quantum annealing platforms. Each one of…
An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies
David Enthoven, Zaid Al-Ars
With the increased attention and legislation for data-privacy, collaborative machine learning (ML) algorithms are being developed to ensure the protection of private data used for…