ICDCS EAI 2020: EAI: Workshop on Efficient Artificial Intelligence For Edge Computing in conjunction with The 40th IEEE International Conference on Distributed Computing Systems (ICDCS-20) Singapore, Singapore, July 8-10, 2020 |
Conference website | https://eai-icdcs.github.io/ |
Submission link | https://easychair.org/conferences/?conf=eai2020 |
Submission deadline | March 27, 2020 |
EAI 2020 focuses on an emerging and impactful topic Efficient Artificial Intelligence (EAI), that facilitate the edge computing by fitting AI models into the edge-AI device. Deep learning has achieved wide success in applications including image classification, video analytics, audio processing thanks to the rapid development of machine learning frameworks (Tensorflow, Pytorch, Caffe) and the accessibility of high-end GPUs. However, requirements in data privacy, communication bandwidth, and processing latency are driving AI to the edge. Edge AI devices operate with tight resource budgets such as memory, power and computing horsepower. AI technology with high-end GPUs for training and running large neural networks are not suitable for edge AI.
The main principles of efficient AI for edge computing are efficiency, effectiveness, and adaptability. Efficiency is the ability to achieve the required performance with constrained resources (e.g. compute, memory, storage, and power). Effectiveness is the ability to achieve a good quality of results (QoR) with efficiency taken into consideration. Adaptability deals with the ability to adapt to changing needs, environment, and operational conditions. Together, these three principles of efficient AI formulate the key metrics toward ultra-efficient AI for edge devices. In the last few years, we have witnessed a growing research trend in these principles. Various kinds of techniques are proposed such as post-training or training-aware quantization and pruning, hardware-software co-design, low power machine learning, etc. The research and development progress has been complemented in popular machine learning frameworks with many applications in image classification, video analysis, IoTs, circuit/chip design, health monitoring and more.
Submission Guidelines
All papers must be original and not simultaneously submitted to another journal or conference. All papers need to be submitted electronically in PDF format through EasyChair. Papers must be formatted for 8.5x11-inch paper. The length of the paper must be no more than 6 pages (or 8 pages with over-length charge) in the IEEE double-column format (10-pt font), including references and everything. The reviews will be single blind. At least one of the authors of every accepted paper must register and present the paper at the workshop.
All submissions will be considered for oral and poster presentations at EAI. The decision on presentation format will be based primarily on an assessment of the breadth of interest, and the construction. We will seek sponsorship to set up the best paper and best poster awards.
Committees
Program Committee
- TBD
Organizing committee
- Joey Tianyi Zhou, Institute of High Performance Computing, Agency for Science, Technology and Research
- Tao Luo, Institute of High Performance Computing, Agency for Science, Technology and Research
- Wei Zhang, Department of Electronic & Computer Engineering, The Hong Kong University of Science and Technology
- Weichen Liu, School of Computer Science and Engineering, Nanyang Technological University
- Weng-Fai Wong, Department of Computer Science School of Computing, National University of Singapore
- Yew Soon Ong, School of Computer Science and Engineering, Nanyang Technological University
Invited Speakers
- Shangjiang Tang, Associate Professor from Tianjin University
- Yao Chen, Research Scientist from Advanced Digital Sciences Center UIUC
- Zeng Zeng, Senior Scientist from I2R, A*STAR
Venue
Please visit ICDCS 2020 main conference for venue information.