Explore Microsoft's innovative approach to query optimization in production environments, addressing challenges with general-purpose optimization and introducing specialized cloud-based optimizers. Learn about the implementation details, experiments conducted, and the solution proposed. Discover how

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Optimization in process engineering involves obtaining the best possible solution for a given process by minimizing or maximizing a specific performance criterion while considering various constraints. This process is crucial for achieving improved yields, reducing pollutants, energy consumption, an

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This proposal aims to improve bandwidth utilization in IEEE 802.11 networks by allowing devices to transmit on idle channels within the operating bandwidth. It addresses the inefficiencies caused by the current limitation where devices do not transmit on idle portions if the primary channel is busy.

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Swarm Intelligence (SI) is an artificial intelligence technique inspired by collective behavior in nature, where decentralized agents interact to achieve goals. Swarms are loosely structured groups of interacting agents that exhibit collective behavior. Examples include ant colonies, flocking birds,

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The document discusses challenges and requirements related to bandwidth indication in RTS/CTS frames with PPDU in 320 MHz, focusing on scenarios where bandwidth signaling may lead to misinterpretation by stations. It highlights the need for dynamic bandwidth and preamble puncturing information in RT

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The DNN Inference Optimization Challenge, organized by Liya Yuan from ZTE, focuses on optimizing deep neural network (DNN) models for efficient inference on-device, at the edge, and in the cloud. The challenge addresses the need for high accuracy while minimizing data center consumption and inferenc

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This proposal aims to address the inefficient utilization of bandwidth in IEEE 802.11 networks by allowing stations to transmit on idle channels within their operating bandwidth. The document discusses the problem statement, high-level solution, relevant capabilities of transmitters and receivers, p

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This document discusses the proposal for enhancing IEEE 802.11 with support for 320MHz bandwidth ranging operations. It aims to improve ranging accuracy by expanding 802.11az frames and procedures to accommodate the increased bandwidth. The focus is on MAC-related changes, exploring different option

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Explore the realm of digital modulation techniques such as ASK, FSK, PSK, QPSK, QAM, and more. Learn about bandwidth efficiency, baud rates, minimum bandwidth, and how to calculate them. Discover the importance of M-ary modulation and how it impacts data transmission rates and bandwidth requirements

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Discrete Optimization is a field of applied mathematics that uses techniques from combinatorics, graph theory, linear programming, and algorithms to solve optimization problems over discrete structures. This involves creating mathematical models, defining objective functions, decision variables, and

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This study delves into the generalization of Empirical Risk Minimization (ERM) in stochastic convex optimization, focusing on minimizing true objective functions while considering generalization errors. It explores the application of ERM in machine learning and statistics, particularly in supervised

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Revisiting the tone plan optimization for IEEE 802.11-19/1340r2, addressing issues with RUs near band edges, accommodating various STA bandwidth capabilities, and the inefficiencies of non-SST 11ax STAs in different BSS scenarios. Proposals include adapting to unknown future 11ax features, minimizin

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Explore the world of optimization through convex and general problems, understanding the concepts, constraints, and the difference between convex and non-convex optimization. Discover the significance of local and global optima in solving complex optimization challenges.

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Explore the basic components of optimization problems, such as objective functions, constraints, and global vs. local optima. Learn about single vs. multiple objective functions and constrained vs. unconstrained optimization problems. Dive into the statement of optimization problems and the concept

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The research discusses innovative ideas for enhancing sensitivity and bandwidth limits in the context of white light cavity technologies. It explores methods such as external/internal squeezing and signal recycling to surpass existing Mizuno Limits, shedding light on crucial issues for future upgrad

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Explore the challenges faced by Moore's Law in relation to bandwidth limitations and the innovative solutions such as 3D-DRAM caches and compressed memory systems. Discover how compressing DRAM caches can improve bandwidth and capacity, leading to enhanced performance in memory-intensive application

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The document discusses the implementation of Selective Spatial Transmission (SST) and Dynamic Subband Operation (DSO) to enable wider bandwidth OFDMA in IEEE 802.11be and 802.11bn standards. It covers enhancements for 80MHz, 160MHz, and 320MHz EHT DL and UL OFDMA transmissions, emphasizing the benef

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Recent research highlights advancements in solving sampling problems in convex optimization, exemplified by works by Yin Tat Lee and Santosh Vempala. The complexity of convex problems, such as the Minimum Cost Flow Problem and Submodular Minimization, are being unraveled through innovative formulas

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This piece discusses approximation algorithms for stochastic optimization problems, focusing on modeling uncertainty in inputs, adapting to stochastic predictions, and exploring different optimization themes. It covers topics such as weakening the adversary in online stochastic optimization, two-sta

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Discussion on Dynamic Subband Operation in IEEE 802.11-23/2141r0 focusing on enabling flexible bandwidth allocation between APs and non-APs for improved resource utilization and system performance. The proposal aims to address bandwidth mismatches and enhance efficiency in channel access allocation

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The document discusses bandwidth and packet type detection schemes for 40-50GHz millimeter wave communication systems in IEEE 802.11aj specifications. It proposes a preamble design for auto-detection of bandwidth and packet type to improve channel estimation and decoding efficiency. By utilizing dif

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This presentation discusses the challenges faced by TCP in high bandwidth-delay product networks, highlighting issues such as oscillations and instability. It explores solutions like adjusting aggressiveness based on feedback delay, decoupling efficiency and fairness control, and introduces XCP as a

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This presentation by Gurdev Singh from Samsung addresses a technique for optimized content transfer in mesh networks by splitting content into file chunks based on the bandwidth of the channel. By considering the bandwidth or link quality of destination nodes, the content is divided so that lower ba

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Efficiently coordinating off-chip read/write bandwidth through the Bandwidth-aware LLC proposal yields a 12% performance improvement in an 8-core system across multiple workloads. This approach optimizes DRAM read latency, surpassing existing policies and filling performance gaps while confirming lo

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In the February 2020 update, Stefano Russo from LPNHE Paris presented the progress on the time distribution system R&D for the Hyper-Kamiokande experiment. The focus is on implementing a bidirectional data exchange link with a large bandwidth capacity for synchronous, phase-deterministic protocol. T

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Real-world design problems often require multi-objective optimization, and the Flower Pollination Algorithm (FPA) developed by Xin-She Yang in 2012 mimics the pollination process of flowering plants to efficiently solve such optimization tasks. FPA has shown promising results in extending to multi-o

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Bandwidth is a crucial aspect of network capacity, describing the data transfer speed and carrying capacity of a channel. Channel capacity involves factors like data rate, bandwidth, noise, and error rate. Noise sources include thermal noise, impulse noise, and delay distortion, impacting signal qua

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Efficient bandwidth estimation is crucial for network management and QoS applications, with cognitive passive methods offering insights without additional traffic loads. This research explores the impact of control messaging overhead, network topology, channel usage, hidden/exposed terminals, and pa

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This paper discusses DeltaINT, a novel framework for in-band network telemetry aimed at reducing bandwidth overhead while ensuring high generality and convergence. It addresses the limitations of existing methods by providing theoretical analysis on bandwidth mitigation guarantees and offering softw

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Gigabit Ethernet over Polymer Optical Fiber (GEPOF) is a promising technology addressing the growing bandwidth requirements in home networking. Advances in FTTH technology enable high-speed connections for Smart Homes, supporting services like cloud computing, 4K video streaming, and Internet of Thi

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Efficiently managing DRAM caches is crucial due to increasing memory demands and bandwidth limitations. Strategies like using DRAM as a cache, architectural considerations for large DRAM caches, and understanding replacement policies are explored in this study to enhance memory bandwidth and capacit

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This presentation provides a comprehensive overview of bandwidth and dispersion in fiber optic communication. It covers essential terminologies like microns, nanometers, millimeters, and dB, explaining concepts such as bandwidth capacity, dispersion cancellation, and modal bandwidth in multimode fib

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Third-generation communication systems utilize Pseudo-Noise (PN) codes to share bandwidth without interference, while first and second-generation systems divide bandwidth into smaller channels. PN codes are vectors with 1s and -1s, orthogonal to each other. Users transmit data using PN coding, combi

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This research presents a hybrid optimization heuristic approach for efficient instruction scheduling in programmable accelerator codesign. It discusses Google's TPU architecture, problem-solving strategies, and computation graph mapping, routing, and timing optimizations. The technique overview high

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This presentation discusses the application of machine learning for optimizing EBIS beam intensity and RHIC luminosity. It covers topics such as motivation, EBIS beam intensity optimization, luminosity optimization, and outlines the plan and summary of the project. Collaborators from MSU, LBNL, and

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Bayesian optimization is being used at LCLS to tune the Free Electron Laser (FEL) pulse energy efficiently. The current approach involves a tradeoff between human optimization and numerical optimization methods, with Gaussian processes providing a probabilistic model for tuning strategies. Prior mea

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The document discusses the introduction of 35/45MHz channel bandwidth in UE RF requirements for various bands. It covers equation-based requirements and limitations in UL configurations based on bandwidth allocation. The scope includes capturing content from the first round discussions and clarifyin

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This submission delves into the necessity of expanding the bandwidth of Channel State Information (CSI) in wireless environments to cater to the demands of time-sensitive wireless sensing applications. It explores the implications of high-bandwidth CSI on enhancing wireless channel understanding, ac

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The evolution of metalearning in the machine learning community is traced from the initial workshop in 1998 to recent developments in hyper-parameter optimization. Challenges in classifier selection and the validity of hyper-parameter optimization claims are discussed, urging the exploration of spec

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This research focuses on enabling transparent memory compression for commodity memory systems to address the growing demand for memory bandwidth. By implementing hardware compression without relying on operating system support, the goal is to optimize memory capacity and bandwidth efficiently. The a

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