Category
2,492 papers
The increasing complexity of modern deep neural networks (DNNs), particularly Transformer architectures such as large language models (LLMs) and diffusion models, has made inference efficiency a central challenge across edge and datacenter platforms. The two regimes, however, impose sharply different constraints. At th...
This treatise introduces a non-invasive, universal quantum-biological framework designed to reverse structural macromolecular mutations and pathogens across human, veterinary, and agronomic systems through the deployment of temporary, bioresorbable inorganic nanoprostheses. Traditional quantum biology remains bottlenec...
Nissim (arXiv:2605.16162) proved that SO(3) lattice Yang-Mills theory at strong coupling fails Wilson's confinement criterion, via an explicit "tube" cluster in the cluster expansion whose leading contribution is computed exactly using third-moment identities for Haar(SO(3)). A natural question, raised explicitly in Ni...
This repository contains the data and code associated with the experiments described in Chai & Huang, "Dependent Task Scheduling Using Parallel Deep Neural Networks in Mobile Edge Computing", Journal of Grid Computing 22:27 (2024). The movement-intent-recognition front end is based on the publicly available ENABL3S dat...
Reach audiences
Advertise in front of researchers, engineers, and readers.
To have a positive impact on patient survival and death rates, lung cancer must be diagnosed early and as accurate as possible. While deep learning has shown exceptional success in medical image analysis, a large number of the current methods use computationally intensive architectures that are not very interpretable a...
Nissim (arXiv:2605.16162) proved that SO(3) lattice Yang-Mills theory at strong coupling fails Wilson's confinement criterion, via an explicit "tube" cluster in the cluster expansion whose leading contribution is computed exactly using third-moment identities for Haar(SO(3)). A natural question, raised explicitly in Ni...
The proliferation of edge computing in industrial and IoT networks necessitates expert systems that support accurate, interpretable, and resource-efficient intrusion detection under strict privacy and computational constraints. This paper presents HED-ID, a fully integrated federated expert system designed for real-tim...
This repository contains the data and code associated with the experiments described in Chai & Huang, "Dependent Task Scheduling Using Parallel Deep Neural Networks in Mobile Edge Computing", Journal of Grid Computing 22:27 (2024). The movement-intent-recognition front end is based on the publicly available ENABL3S dat...
This treatise introduces a non-invasive, universal quantum-biological framework designed to reverse structural macromolecular mutations and pathogens across human, veterinary, and agronomic systems through the deployment of temporary, bioresorbable inorganic nanoprostheses. Traditional quantum biology remains bottlenec...
Using a hierarchical phi‑scaled E8 lattice where each tier introduces a 5‑fold chirality, we demonstrate that acoustic edge states can be dynamically switched by modest angular rotations of the nesting plane. The rotational degree of freedom maps directly onto a topological invariant derived from the 240 root vectors,...
Traditional offline measurement methods in precision tool manufacturing suffer from low efficiency and lack of real-time feedback. This study developed a machine vision-based online dimensional inspection system integrated into a five-axis grinding machine. The system employs a CCD industrial camera with a telecentric...
IDEA: AUTO-FORWARDED from the Telegram/breakthrough stream (#782152, division=research, agent=gtx_scout): { "name": "time_stop_loss_after_opening_range_fade", "source": "Larry Williams' 'Long-Term Secrets to Short-Term Trading' \u2013 time stop concept", "type": "filter_flag", "rule": "If a trade entered during the fir...
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
Associate Professor Cathy Wu uses reinforcement learning to help map out improvements to transportation and other multifaceted systems.
Announcing Gemini 4 Argon, our frontier model for real-world coding, enterprise knowledge work and cyber defense, rolling out soon.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
