by instadatahelp | Sep 3, 2023 | AI Blogs
Theoretical Optimality and Practical Improvements of Decentralized Learning Authors: Yucheng Lu, Christopher De Sa; Published in 2023, Volume 24, Issue 93, Pages 1-62. Abstract Scaling up parallel machine learning systems through decentralization has shown great...
by instadatahelp | Sep 3, 2023 | AI Blogs
In the fast-paced digital age, the analysis of document layouts is crucial for automated information extraction and interpretation. Our research focuses on training the MViTv2 transformer model architecture with cascaded mask R-CNN on the BaDLAD dataset. This allows...
by instadatahelp | Sep 3, 2023 | AI Blogs
Model-Based Multi-Agent Reinforcement Learning in Zero-Sum Markov Games with Near-Optimal Sample Complexity Kaiqing Zhang, Sham M. Kakade, Tamer Basar, Lin F. Yang; 24(175):1−53, 2023. Abstract Model-based reinforcement learning (RL) is a fundamental approach in RL...
by instadatahelp | Sep 3, 2023 | AI Blogs
Mobile devices have become the most widely used technology, but they are also vulnerable to botnet-related malware. One example is FluBot, a botnet malware that specifically targets mobile devices. FluBot uses Domain Generation Algorithms (DGA) to communicate with its...
by instadatahelp | Sep 3, 2023 | AI Blogs
Statistical Inference for Noisy Incomplete Binary Matrix Authors: Yunxiao Chen, Chengcheng Li, Jing Ouyang, Gongjun Xu; Volume 24, Issue 95, Pages 1-66, 2023. Abstract This paper focuses on statistical inference for noisy incomplete binary (or 1-bit) matrices. While...
by instadatahelp | Sep 3, 2023 | AI Blogs
The content can be rewritten as: arXivLabs is a platform where collaborators can create and share new features for arXiv directly on our website. Both individuals and organizations that collaborate with arXivLabs have embraced and adopted our values of openness,...
