This version corrects two citation errors found by an automated check and confirmed by hand. In the Selection Process, HANDOFF was cited as arXiv:2606.06491 (TempoVLA) and now cites arXiv:2606.06493, and RoboNaldo was cited as arXiv:2606.11091 (QUIET, a network-neuroscience paper) and now cites arXiv:2606.11092. A refe...
Saluca Agentic AI Research Team· Zenodo (CERN European Organi...· 0 citations
The increasing use of artificial intelligence on smartphones, Internet of Things devices, edge servers, and other distributed platforms has created new opportunities for intelligent applications but has also intensified concerns regarding the privacy of machine-learning data. Conventional centralized machine learning r...
Dr. Pankaj Kumar· Zenodo (CERN European Organi...· 0 citations
The increasing use of artificial intelligence on smartphones, Internet of Things devices, edge servers, and other distributed platforms has created new opportunities for intelligent applications but has also intensified concerns regarding the privacy of machine-learning data. Conventional centralized machine learning r...
Dr. Pankaj Kumar· Zenodo (CERN European Organi...· 0 citations
This work provides a comprehensive roadmap for developing intelligent, sustainable and resilient EV charging ecosystems that will resolve technical, economical, and ecologicalconsiderations while protecting the privacy of data and securing the system.
Narendra Kumar· International Journal of Dig...· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
A Real-time Integrated Adaptive Stable Offloading (RIASO) algorithm is proposed based on Lyapunov optimization (LO), Multi Output Learning (MOL), and DRL that optimizes network data processing capabilities while maintaining long-term data queue stability and average consumed power constraints that makes it adaptable to...
Hala Elhadidy, H. Saleh, R. Rizk et al.· Cluster Computing· 0 citations
This article presents an energy-efficient and process-, voltage-, and temperature (PVT)-robust time-domain (TD) compute-in-memory (CIM) macro for edge artificial intelligence (AI) devices. It features: 1) a PVT inner-tracking (PIT) technique that aligns the PVT responses of TD computation and TD quantization, deliverin...
Yuanzhe Zhao, Yu-Heng Wang, Heng Xie et al.· IEEE Journal of Solid-State...· 0 citations
The rapid proliferation of intelligent sensors has led to increased latency and privacy risks when processing data on a remote server. This work proposes a spin-transfer torque magnetic random access memory (STT-MRAM) compute-in-memory (CIM) macro to enhance inference efficiency for an artificial intelligence (AI) mode...
Jia-le Cui, Ting-xuan Shi, Shuyu Wang et al.· IEEE Journal of Solid-State...· 0 citations
Rate splitting multiple access (RSMA) is a promising multiple access (MA) technology that can be used to enhance the performance of military multiple-input multiple-output (MIMO) systems. By virtue of its rate-splitting method, this technology can flexibly regulate the interference management strategy, achieving superi...
Nonvolatile AI-edge processors based on near-memory-compute (nvNMC) enable energy-efficient multiply-and-accumulate (MAC) operations with short wakeup latency for edge inference operations. Lossless compression is required for floating-point (FP) neural network (NN) models under on-chip memory capacity constraints; how...
De-Qi You, W. Khwa, Bo Zhang et al.· IEEE Journal of Solid-State...· 0 citations
As businesses strive to improve efficiency, reduce latency, and leverage the power of data, understanding the strengths and limitations of these two computing paradigms is crucial. Full article: https://davidohnstad.com/edge-computing-vs-cloud-computing-which-is-the-future/
David Ohnstad· Zenodo (CERN European Organi...· 0 citations
WHAT THIS PACKAGE DOES This package goes with the revised Paper-1 manuscript "Exact Finite-Sample Permutation Moments for Walsh Interaction-Order Energies: A Projector Specialization of Quadratic-Form Randomization Theory" (v1.1). It contains the full open-source code, exhaustive verification, benchmarks, and environme...
Roshankumar chandaliya, Roshankumar chandaliya· Zenodo (CERN European Organi...· 0 citations
The future of the field lies in the transition from single-modality visual perception to multi-dimensional collaborative detection systems, and this review serves as a comprehensive reference for optimizing object detection algorithms tailored for complex remote sensing and low-altitude security environments.
Ke Gu· Computer Vision, Graphics an...· 0 citations
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
For decades, a fundamental question about the difficulty of computing in high-dimensional spaces has resisted proof. New research resolves this question, removing a major theoretical obstacle to understanding the efficiency of randomized algorithms used across science and computing. The Kannan–Lovász–Simonovits (KLS) conjecture was proposed in 1995. It asks whether, for a broad class of high-dimensional […] The post Solving a 31-year-old grand challenge in mathematics – the KLS conjecture appear…
MIT News · Artificial Intelligence· news.mit.eduOct 15, 2026
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
