Continual Distributed Learning for Crisis Management
Manipal Institute of Technology（马尼帕尔理工学院）；University of Massachusetts Amherst（马萨诸塞大学阿默斯特分校）；K J Somaiya College of Engineering（KJ索马亚工程学院）
Aman Priyanshu, Mudit Sinha, Shreyans Mehta
备注：
6 pages, 3 figures, Accepted at 3rd Workshop on Continual and Multimodal Learning for Internet of Things and Presented at IEEESBM Manipal Paper Presentation
Social media platforms such as Twitter, Facebook etc can be utilised as an important source of information during disaster events. This information can be used for disaster response and crisis management if processed accurately and quickly. However, the data present in such situations is ever-changing, and using considerable resources during such a crisis is not feasible. Therefore, we have to develop a low resource and continually learning system that incorporates text classification models which are robust against noisy and unordered data. We utilised Distributed learning which enabled us to learn on resource-constrained devices, then to alleviate catastrophic forgetting in our target neural networks we utilized regularization. We then applied federated averaging for distributed learning and to aggregate the central model for continual learning.
Task-Core Memory Management and Consolidation for Long-term Continual Learning
School of Computer Science and Technology, East China Normal University（东华师范大学计算机科学与技术学院）；School of Electrical and Electronic Engineering, Nanyang Technological University（南洋理工大学电子与电气工程学院）；Computation and Artificial Intelligence Innovative College, Fudan University（复旦大学计算与人工智能创新学院）
Towards stable training of parallel continual learning
College of Intelligence and Computing, Tianjin University（天津大学智能与计算学部）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；School of Automation, Southeast University（东南大学自动化学院）
More Sensors Only One Field: Rethinking Continual Spatio-Temporal Forecasting
City University of Hong Kong (Dongguan)（香港城市大学（东莞））；City University of Hong Kong（香港城市大学）；Zhuhai College of Science and Technology（珠海科技学院）；Northwestern Polytechnical University（西北工业大学）
FastODT: A tree-based framework for efficient continual learning
Masaryk University（马萨里克大学）；Czech Republic（捷克共和国）；Warsaw University of Technology（华沙技术大学）；Poland（波兰）；Mycroft Mind；New York University（纽约大学）；New York, NY, USA（纽约市，纽约州，美国）；Analog AI；Abu Dhabi, UAE（阿布扎赫，阿联酋）
Towards Lifelong Aerial Autonomy: Geometric Memory Management for Continual Visual Place Recognition in Dynamic Environments
Department of Precision Instrument, Tsinghua University（清华大学精密仪器系）；College of Instrument Science and Opto-electronics Engineering, Beijing Information Science and Technology University（北京信息科技大学仪器科学与光电工程学院）；Key Laboratory of Complex System Intelligent Control and Decision Making, Beijing Institute of Technology（北京理工大学复杂系统智能控制与决策重点实验室）；School of Aerospace Engineering, Beijing Institute of Technology（北京理工大学宇航学院）
Preventing Latent Rehearsal Decay in Online Continual SSL with SOLAR
Department of Computer Science, University of Pisa（比萨大学计算机科学系）；Media Integration and Communication Center (MICC), University of Florence（佛罗伦萨大学媒体集成与通信中心（MICC））
