MBZUAI researchers have developed 'Byzantine antidote' (Bant), a novel defense mechanism against Byzantine attacks in federated learning. Bant uses trust scores and a trial function to dynamically filter and neutralize corrupted updates, even when a majority of nodes are compromised. The research was presented at the 40th Annual AAAI Conference on Artificial Intelligence.
MBZUAI researchers are presenting a new approach to open-world object detection at the AAAI conference. The method enables machines to distinguish between known and unknown objects in images, and then learn to classify the unknown objects. PhD student Sahal Shaji Mullappilly is the lead author of the study, titled "Semi-Supervised Open-World Detection". Why it matters: This research addresses a key limitation in current object detection systems, allowing for more adaptable and robust AI in real-world applications.
Dr. Hao Dong from Peking University presented research on addressing the challenge of limited large-scale training data in embodied AI, particularly for manipulation, task planning, and navigation. The presentation covered simulation learning and large models. Dr. Dong is a chief scientist of China's National Key Research and Development Program and an area chair/associate editor for NeurIPS, CVPR, AAAI, and ICRA. Why it matters: Overcoming data scarcity is crucial for advancing embodied AI research and enabling more sophisticated robotic applications in the region.
MBZUAI Assistant Professors Bin Gu and Huan Xiong are advancing spiking neural networks (SNNs) to improve computational power and energy efficiency. They will present their latest research on SNNs at the 38th Annual AAAI Conference on Artificial Intelligence in Vancouver. SNNs process information in discrete events, mimicking biological neurons and offering improved energy efficiency compared to traditional neural networks. Why it matters: This research could enable running advanced AI applications like GPTs on mobile devices, unlocking their full potential due to the energy efficiency of SNNs.
Turing Award winner Raj Reddy spoke at the MBZUAI Executive Program. Reddy is a Professor of Computer Science and Robotics at Carnegie Mellon University (CMU) and has held leadership roles at CMU, AAAI, and IEEE. His research focuses on AI, human-computer interaction, and technology's societal impact. Why it matters: High-profile speakers at UAE AI programs can help attract talent and investment to the region.
Based solely on its title, the research paper "Exploring Visual Context for Weakly Supervised Person Search" investigates methods for leveraging visual cues to improve person search capabilities. This work explores advancements in weakly supervised learning techniques for identifying individuals across different image or video frames. The publication is associated with The Association for the Advancement of Artificial Intelligence (AAAI), indicating a contribution to the broader AI research community. Why it matters: Improvements in person search technology are vital for applications in security, surveillance, and intelligent systems, which have significant implications for smart city initiatives and public safety in the region.