Related papers: Lessons from the Coinseminar
Federated learning is a privacy-focused approach towards machine learning where models are trained on client devices with locally available data and aggregated at a central server. However, the dependence on a single central server is…
Portfolio management is the decision-making process of allocating an amount of fund into different financial investment products. Cryptocurrencies are electronic and decentralized alternatives to government-issued money, with Bitcoin as the…
In this paper we try to organize machine teaching as a coherent set of ideas. Each idea is presented as varying along a dimension. The collection of dimensions then form the problem space of machine teaching, such that existing teaching…
In domains such as health care and finance, shortage of labeled data and computational resources is a critical issue while developing machine learning algorithms. To address the issue of labeled data scarcity in training and deployment of…
Teaching is about constantly innovating strategies, ways and means to engage diverse students in active and meaningful learning. In line with this, SUTD adopts various student-centric teaching and learning teaching methods and approaches.…
Mining is rapidly evolving into an AI driven cyber physical ecosystem where safety and operational reliability depend on robust perception, trustworthy distributed intelligence, and continuous monitoring of miners and equipment. However,…
Blockchain, which is a technology for distributedly managing ledger information over multiple nodes without a centralized system, has elicited increasing attention. Performing experiments on actual blockchains are difficult because a large…
This paper discusses the perspective of the H2020 TEACHING project on the next generation of autonomous applications running in a distributed and highly heterogeneous environment comprising both virtual and physical resources spanning the…
Modern mobile devices have access to a wealth of data suitable for learning models, which in turn can greatly improve the user experience on the device. For example, language models can improve speech recognition and text entry, and image…
Collaborative cybersecurity relies on organizations sharing information to boost security, but trust management is a key concern. Decentralized solutions like distributed ledgers, particularly blockchain, are crucial for eliminating single…
The coin-tap test is a convenient and primary method for non-destructive testing, while its manual on-site operation is tough and costly. With the help of the latest intelligent signal processing method, convolutional neural networks (CNN),…
Hackathons and similar time-bounded events have become a popular form of collaboration. They are commonly organized as in-person events during which teams engage in intense collaboration over a short period of time to complete a project…
The paper presents a course on Combinatorial Algorithms that is based on the drafts of the author that he used while teaching the course in the Department of Informatics and Applied Mathematics of Yerevan State University, Armenia from…
The proliferation of wireless communications networks over the past decades, combined with the scarcity of the wireless spectrum, have motivated a significant effort towards increasing the throughput of wireless networks. One of the major…
In this paper we propose a model to study the appropriation of knowledge of one student in a non-collaborative online class. We formulate a stochastic model based on the quality of the teacher's class and the affinity of the student to…
Quantum computing (QC) is an emerging computing paradigm with potential to revolutionize the field of computing. QC is a field that is quickly developing globally and has high barriers of entry. In this paper we explore both successful…
Designing Knowledge Management Systems (KMSs) for higher education requires addressing complex human-technology interactions, especially where staff turnover and changing roles create ongoing challenges for reusing knowledge. While advances…
Federated Learning is an emerging distributed collaborative learning paradigm adopted by many of today's applications, e.g., keyboard prediction and object recognition. Its core principle is to learn from large amount of users data while…
We shall describe the various activities done by us in Covid Times including outreach and educational workshops in Physics and Astronomy. We shall discuss the caveats in virtual teaching of Astronomy and the lessons learnt in the process.
Decentralized Intelligence Network (DIN) is a theoretical framework designed to address challenges in AI development, particularly focusing on data fragmentation and siloing issues. It facilitates effective AI training within sovereign data…