319 citations
- Intel (United States)US3 papers
- AGH University of KrakowPL1 paper
- Allen Institute for Artificial IntelligenceUS1 paper
- Binghamton UniversityUS1 paper
- Gdańsk University of TechnologyPL1 paper
- Harvard UniversityUS1 paper
- Institute of MathematicsPL1 paper
- Polish Academy of SciencesPL1 paper
- The University of Texas at AustinUS1 paper
- University of WarsawPL1 paper
- Wrocław University of Science and TechnologyPL1 paper
6 papers
Distributed Ranges: A Model for Distributed Data Structures, Algorithms, and Views
Benjamin Brock, Robert Cohn, Suyash Bakshi +6
Data structures and algorithms are essential building blocks for programs, and \emph{distributed data structures}, which automatically partition data across multiple memory locales…
Waste detection in Pomerania: non-profit project for detecting waste in environment
Sylwia Majchrowska, Agnieszka Mikołajczyk, Maria Ferlin +4
Waste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, either for economic or ecological reasons, and t…
AI Tax: The Hidden Cost of AI Data Center Applications
Daniel Richins, Dharmisha Doshi, Matthew Blackmore +9
Artificial intelligence and machine learning are experiencing widespread adoption in industry and academia. This has been driven by rapid advances in the applications and accuracy…
Evaluation of Docker Containers for Scientific Workloads in the Cloud
Pankaj Saha, Angel Beltre, Piotr Uminski +1
The HPC community is actively researching and evaluating tools to support execution of scientific applications in cloud-based environments. Among the various technologies, containe…
ScreenerNet: Learning Self-Paced Curriculum for Deep Neural Networks
Tae-Hoon Kim, Jonghyun Choi
We propose to learn a curriculum or a syllabus for supervised learning and deep reinforcement learning with deep neural networks by an attachable deep neural network, called Screen…
Atari games and Intel processors
Robert Adamski, Tomasz Grel, Maciej Klimek +1
The asynchronous nature of the state-of-the-art reinforcement learning algorithms such as the Asynchronous Advantage Actor-Critic algorithm, makes them exceptionally suitable for C…