AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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2,356 papers
We study proportional fairness in graphical resource allocation, where agents are vertices, indivisible items are edges, and each item must be allocated to one of its two endpoints. It has been proved that PROP1 orientations always exist and PROPx orientations may not, but it has remained open whether the intermediate...
A deterministic polynomial-time approximation for Maximum Weighted $3-Set Packing, breaking the $\sqrt3$ locality-gap barrier of squared-weight local search and proving that $\sqrt3$ is a locality-gap lower bound for the squared-weight objective even with exchanges of arbitrary size.
Vehicular edge computing (VEC) enables latency-sensitive applications by bringing computing and networking resources closer to vehicles. However, existing approaches often overlook network contention among co-located services with heterogeneous and dynamic latency requirements. While time-sensitive networking (TSN) pro...
Two-dimensional (2D) non-layered oxides, such as MoO2, are emerging candidates for next-generation electronics, optoelectronics and sensors, especially novel in-sensor computing. However, there is a lack of effective method to grow large-area 2D MoO2 single crystals due to multiple preferred orientations induced by unc...
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DECISION: REJECT ELEMENT: No element survives — the pool-density ≥90 filter is a statistical artifact, not an E8-geometry-compatible edge. EXPECTED IMPACT: The +1.5pp backtest gain (n=1800) is within noise for a 32.5%→34.0% shift (σ≈1.1pp). Merlin's own live-window projection shows only +8.6pp on 7 trades (n=7, meaning...
Maize faces a wide variety of pests and diseases, and its growing environment is complex, which makes detecting these problems quite challenging. Existing object detection algorithms usually require a lot of computing power, but edge computing devices are limited in terms of processing resources and memory, making it h...
Decision Support Systems (DSS) in precision agriculture have evolved from static rule-based engines into data-driven frameworks powered by Internet of Things (IoT) telemetry and supervised machine learning. While recent literature increasingly focuses on deep learning and volatile commodity forecasting, empirical farm-...
Deliverable D3.5 Production Planning & Reconfiguration v1 provides an overall status update of two core components developed within the CIRCMAN5.0 project’s Work Package 3 (WP3). They are aligned with WP3’s purpose that is to deliver novel simulation and modelling software to improve process and product manufacturing....
Connectomics datasets now provide synapse-resolution wiring diagrams for entire insect nervous systems, raisinga question that is easy to pose but rarely tested directly: does the specific wiring these datasets reveal confer afunctional advantage over a structurally-matched random control, when deployed as an actual re...
The Music Perception Toolbox is an open‑source package—available in both MATLAB and Python—for computing perceptually and cognitively motivated measures of pitch similarity, consonance, and scale and rhythmic structure. Inputs may be symbolic pitches or spectral peaks extracted from audio. The toolbox covers three fami...
This dataset contains the 25,000-sample training dataset used in "Deep Learning-Accelerated Inverse Design of a Nonlinear Duffing-Type Metamaterial: Amplitude-Programmable, Bifurcation-Aware Bandgap Prediction." Each row corresponds to a sampled design point (nonlinear stiffness k3, mass ratio m2/m1, excitation amplitu...
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.
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