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pro vyhledávání: '"Sanderson, Conrad"'
Approximate k-Nearest Neighbour (ANN) methods are often used for mining information and aiding machine learning on large scale high-dimensional datasets. ANN methods typically differ in the index structure used for accelerating searches, resulting in
Externí odkaz:
http://arxiv.org/abs/2404.19284
Publikováno v:
IEEE Conference on Artificial Intelligence, 2024
While the operationalisation of high-level AI ethics principles into practical AI/ML systems has made progress, there is still a theory-practice gap in managing tensions between the underlying AI ethics aspects. We cover five approaches for addressin
Externí odkaz:
http://arxiv.org/abs/2401.08103
Publikováno v:
Journal of Heuristics, Vol. 29, No. 4-6, pp. 487-544, 2023
A travelling thief problem (TTP) is a proxy to real-life problems such as postal collection. TTP comprises an entanglement of a travelling salesman problem (TSP) and a knapsack problem (KP) since items of KP are scattered over cities of TSP, and a th
Externí odkaz:
http://arxiv.org/abs/2310.07156
Publikováno v:
IEEE Aerospace Conference, 2022
Recent advances in Unmanned Aerial Vehicles (UAVs) have resulted in their quick adoption for wide a range of civilian applications, including precision agriculture, biosecurity, disaster monitoring and surveillance. UAVs offer low-cost platforms with
Externí odkaz:
http://arxiv.org/abs/2308.10671
This report provides an introduction to the Bandicoot C++ library for linear algebra and scientific computing on GPUs, overviewing its user interface and performance characteristics, as well as the technical details of its internal design. Bandicoot
Externí odkaz:
http://arxiv.org/abs/2308.03120
Autor:
Hajkowicz, Stefan, Sanderson, Conrad, Karimi, Sarvnaz, Bratanova, Alexandra, Naughtin, Claire
Publikováno v:
Technology in Society, Vol. 74, 2023
Analysing historical patterns of artificial intelligence (AI) adoption can inform decisions about AI capability uplift, but research to date has provided a limited view of AI adoption across various fields of research. In this study we examine worldw
Externí odkaz:
http://arxiv.org/abs/2306.09145
Publikováno v:
Procedia Computer Science, Vol. 222, pp. 367-376, 2023
Wildfire propagation is a highly stochastic process where small changes in environmental conditions (such as wind speed and direction) can lead to large changes in observed behaviour. A traditional approach to quantify uncertainty in fire-front progr
Externí odkaz:
http://arxiv.org/abs/2305.06139
Publikováno v:
International Joint Conference on Neural Networks (IJCNN), 2023
Many sets of ethics principles for responsible AI have been proposed to allay concerns about misuse and abuse of AI/ML systems. The underlying aspects of such sets of principles include privacy, accuracy, fairness, robustness, explainability, and tra
Externí odkaz:
http://arxiv.org/abs/2304.08275
Autor:
Curtin, Ryan R., Edel, Marcus, Shrit, Omar, Agrawal, Shubham, Basak, Suryoday, Balamuta, James J., Birmingham, Ryan, Dutt, Kartik, Eddelbuettel, Dirk, Garg, Rishabh, Jaiswal, Shikhar, Kaushik, Aakash, Kim, Sangyeon, Mukherjee, Anjishnu, Sai, Nanubala Gnana, Sharma, Nippun, Parihar, Yashwant Singh, Swain, Roshan, Sanderson, Conrad
Publikováno v:
Journal of Open Source Software, Vol. 8, No. 82, 2023
For over 15 years, the mlpack machine learning library has served as a "swiss army knife" for C++-based machine learning. Its efficient implementations of common and cutting-edge machine learning algorithms have been used in a wide variety of scienti
Externí odkaz:
http://arxiv.org/abs/2302.00820
Autor:
Dabrowski, Joel Janek, Pagendam, Daniel Edward, Hilton, James, Sanderson, Conrad, MacKinlay, Daniel, Huston, Carolyn, Bolt, Andrew, Kuhnert, Petra
We apply the Physics Informed Neural Network (PINN) to the problem of wildfire fire-front modelling. We use the PINN to solve the level-set equation, which is a partial differential equation that models a fire-front through the zero-level-set of a le
Externí odkaz:
http://arxiv.org/abs/2212.00970