Data Science Institute (Conference Papers)
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An SRAM optimized approach for constant memory consumption and ultra-fast execution of ML classifiers on TinyML hardware
(Institute of Electrical and Electronics Engineers, 2021-11-15)With the introduction of ultra-low-power machine learning (TinyML), IoT devices are becoming smarter as they are driven by Machine Learning (ML) models. However, any increase in the training data results in a linear ... -
CURED4NLG: A dataset for table-to-text generation
(University of Galway, 2023)We introduce CURED4NLG, a dataset for the task of table-to-text generation focusing on the public health domain. The dataset consists of 280 pairs of tables and documents extracted from weekly epidemiological reports ... -
Unsupervised deep language and dialect identification for short texts
(International Committee on Computational Linguistics, 2020-12)Automatic Language Identification (LI) or Dialect Identification (DI) of short texts of closely related languages or dialects, is one of the primary steps in many natural language processing pipelines. Language identification ... -
Cross-lingual sentence embedding using multi-task learning
(Association for Computational Linguistics, 2021-11-07)Multilingual sentence embeddings capture rich semantic information not only for measuring similarity between texts but also for catering to a broad range of downstream cross-lingual NLP tasks. State-of-the-art multilingual ... -
NUIG at TIAD 2021: Cross-lingual word embeddings for translation inference
(2021-09-01)Inducing new translation pairs across dictionaries is an important task that facilitates processing and maintaining lexicographical data. This paper describes our submissions to the Translation Inference Across Dictionaries ... -
Do city dashboards make sense? Conceptualising user experiences and challenges in using city dashboards. A case study
(Association for Computing Machinery (ACM), 2021-06-09)City dashboards present information about a city to a broad audience with some thought given as to how some of these audiences might understand the information. However, little research has looked at how ’citizens’ make ... -
Understanding my city through dashboards. How hard can it be?
(International Federation for Information Processing (IFIP) and eJournal of eDemocracy and Open Government (JeDEM), 2019-09-02)This paper describes research into how current city dashboards support users' sensemaking processes. It uses criteria identified in previous research concerning visualisation and applies these to a number of city dashboards ... -
Traffic prediction framework for OpenStreetMap using deep learning based complex event processing and open traffic cameras
(Dagstuhl Research Online Publication Server (DROPS), 2020-09-25)Displaying near-real-time traffic information is a useful feature of digital navigation maps. However, most commercial providers rely on privacy-compromising measures such as deriving location information from cellphones ... -
RCE-NN: a five-stage pipeline to execute neural networks (CNNs) on resource-constrained IoT edge devices
(Association for Computing Machinery (ACM), 2020-10-06)Microcontroller Units (MCUs) in edge devices are resource constrained due to their limited memory footprint, fewer computation cores, and low clock speeds. These limitations constrain one from deploying and executing machine ... -
Edge2Train: A framework to train machine learning models (SVMs) on resource-constrained IoT edge devices
(Association for Computing Machinery (ACM), 2020-10-06)In recent years, ML (Machine Learning) models that have been trained in data centers can often be deployed for use on edge devices. When the model deployed on these devices encounters unseen data patterns, it will either ... -
Enabling machine learning on the edge using SRAM conserving efficient neural networks execution approach
(National University of Ireland Galway, 2021-09-13)Edge analytics refers to the application of data analytics and Machine Learning (ML) algorithms on IoT devices. The concept of edge analytics is gaining popularity due to its ability to perform AI-based analytics at the ... -
Ultra-fast machine learning classifier execution on IoT devices without SRAM consumption
(Institute of Electrical and Electronics Engineers (IEEE), 2021-05-25)With the introduction of edge analytics, IoT devices are becoming smart and ready for AI applications. A few modern ML frameworks are focusing on the generation of small-size ML models (often in kBs) that can directly be ... -
TinyML benchmark: Executing fully connected neural networks on commodity microcontrollers
(National University of Ireland Galway, 2021-06-20)Recent advancements in the field of ultra-low-power machine learning (TinyML) promises to unlock an entirely new class of edge applications. However, continued progress is restrained by the lack of benchmarking Machine ... -
Uncovering semantic bias in neural network models using a knowledge graph
(ACM, 2020-10-19)While neural networks models have shown impressive performance in many NLP tasks, lack of interpretability is often seen as a disadvantage. Individual relevance scores assigned by post-hoc explanation methods are not ... -
Smart speaker design and implementation with biometric authentication and advanced voice interaction capability
(CEUR-WS.org, 2019-12-05)Advancements in semiconductor technology have reduced dimensions and cost while improving the performance and capacity of chipsets. In addition, advancement in the AI frameworks and libraries brings possibilities to ... -
Unsupervised method to analyze playing styles of EPL teams using ball possession-position data
(IEEE, 2020-03-06)In the English Premier League (EPL) matches, a network of advanced systems gathers sports data in real-time to build a possession-position dataset. In this work, data fields from the sophisticated raw possession-position ... -
NUIG-Panlingua-KMI Hindi-Marathi MT Systems for Similar Language Translation Task @ WMT 2020
(Association for Computational Linguistics, 2020-11-19)NUIG-Panlingua-KMI submission to WMT 2020 seeks to push the state-of-the-art in the Similar language translation task for the Hindi ↔ Marathi language pair. As part of these efforts, we conducted a series of experiments to ... -
Findings of the LoResMT 2020 shared task on zero-shot for low-resource languages
(Association for Computational Linguistics, 2020-12-04)This paper presents the findings of the LoResMT 2020 Shared Task on zero-shot translation for low resource languages. This task was organised as part of the 3rd Workshop on Technologies for MT of Low Resource Languages ... -
Towards automatic linking of lexicographic data: the case of a historical and a modern Danish dictionary
(European Association for Lexicography, 2020)Given the diversity of lexical-semantic resources, particularly dictionaries, integrating such resources by aligning various types of information is an important task, both in e-lexicography and natural language processing. ... -
Enrichment of blockchain transaction management with semantic triples
(National University of Ireland Galway, 2020-11-02)Abstract—Enterprise business transactions have both public and private information; hence blockchain adaptation to an enterprise business application needs current blockchain platforms to support both public and private ...