optimiz search results




optimiz - 20 / 308
www.unite.ai | Yesterday
Summary:
In today s rapidly evolving cloud landscape, reducing cloud costs while enhancing application performance has become critical priority for both established enterprises and fast growing digital native businesses. The 8220 State of Cloud Optimization...


Keywords: analysis, metric, design, correlation, optimization

python.plainenglish.io | Today
Summary:
IntroductionCat Swarm Optimization CSO is an intriguing and innovative optimization algorithm inspired by the observational behavior of cats. Proposed by Chu et al. in 2006, this algorithm is nature inspired metaheuristic that belongs to the swarm ...


Keywords: swift, mathematic, ios, optimization, clustering

bigdataanalyticsnews.com | Today
Summary:
Maintaining and optimizing legacy code can be daunting task. Spaghetti code, outdated libraries, and cryptic comments plague developers, hindering productivity and innovation. Challenges of legacy code Technical debt Years of accumulated changes, fi...


Keywords: generative, java, programming, algorithms, python

www.whatech.com | Today
Summary:
Optimize your dating app for success across platforms and devices with this comprehensive guide. Learn strategies for platform specific design, responsive layouts, performance optimization, accessibility, cross platform dating app development, and mo...


Keywords: react native, test, gpu, framework

www.analyticsinsight.net | Yesterday
Summary:
Unlocking Success Proven Ecommerce SEO Strategies to Optimize Your Online Store In the ever expanding world of online commerce, having robust Ecommerce SEO strategy is crucial for driving visibility, attracting traffic, and ultimately boosting sales...


Keywords: algorithms, design, rust, analytic, responsive

stackoverflow.com | Yesterday
Summary:
The error that got wasValueError Missing learning rate, please set self.learning rate at optimizer creation time.The code that used wasimport numpy as npimport tensorflow as tffrom tensorflow import kerasclass GradientDescent keras.optimizers.Optimi...


Keywords: tensorflow

stackoverflow.com | Yesterday
Summary:
The error that got wasValueError Missing learning rate, please set self.learning rate at optimizer creation time.The code that used wasimport numpy as npimport tensorflow as tffrom tensorflow import kerasclass GradientDescent keras.optimizers.Optimi...


Keywords: tensorflow

www.marktechpost.com | Yesterday
Summary:
img width 696 height 372 src class attachment large size large wp post image alt style float left margin 0 15px 15px 0 decoding async fetchpriority high srcset 1024w, 300w, 768w, 1536w, 2048w, 150w, 696w, 1068w, 1920w, 785w size...


Keywords: analysis, hyperparameter, framework, machine learning

arxiv.org | Yesterday
Summary:
Solving combinatorial optimization problems (COPs) is a promising application of quantum computation, with the Quantum Approximate Optimization Algorithm (QAOA) being one of the most studied quantum algorithms for solving them. However, multiple factors make the parameter search of the QAOA a hard optimization problem. In this work, we study transfer learning (TL), a methodology to reuse pre-trained QAOA parameters of one problem instance into different COP instances. To this end, we select smal...


Keywords: optimization, quantum comp, transfer learning,

faun.pub | Today
Summary:
In this comprehensive guide, Ill walk you through the step by step process of how get paid by Google and show you how to monetize your blog. From setting up blogging platform to implementing SEO strategies, social media marketing, implementing Google...


Keywords: mobile, security, analytic, optimization, search

arxiv.org | Yesterday
Summary:
We study a general scalarization approach via utility functions in multi-objective optimization. It consists of maximizing utility which is obtained from the objectives' bargaining with regard to a disagreement reference point. The theoretical framework for a broad class of utility functions from microeconomics is developed. For that, we associate a utility-dependent single-objective optimization problem with the given multi-objective optimization problem. We show that Pareto optimal points of t...


Keywords: framework, optimization, scala

www.reddit.com | Yesterday
Summary:
Hello, hired someone for speed optimizing my site yesterday. He did so with plugin called 39 Seraphinite 39 . Everything was good and in the green, so the payment was done. x200B Later that day, was scrolling through my site on my mobile and su...


Keywords: test, mobile, optimization

arxiv.org | Yesterday
Summary:
We introduce a new Langevin dynamics based algorithm, called e-TH$\varepsilon$O POULA, to solve optimization problems with discontinuous stochastic gradients which naturally appear in real-world applications such as quantile estimation, vector quantization, CVaR minimization, and regularized optimization problems involving ReLU neural networks. We demonstrate both theoretically and numerically the applicability of the e-TH$\varepsilon$O POULA algorithm. More precisely, under the conditions that ...


Keywords: neural network, network, optimization, quant

www.reddit.com | Today
Summary:
am sharing recent open source project AutoPrompt, developed by colleague. This framework is about making prompt optimization smarter, faster, and more cost effective, especially in real world use cases, such as classification, ranking, and content ge...


Keywords: optimization, classification, framework

www.techmeme.com | Today
Summary:
Dean Takahashi VentureBeat Qualcomm unveils AI Hub, new library of 75 pre optimized AI models, X80 5G modem, and FastConnect 7900, chip that integrates Wi Fi 7, Bluetooth, and UWB mdash Qualcomm unveiled suite of AI, 5G, and Wi Fi devices at Mobil...


Keywords: ai , mobile

arxiv.org | Yesterday
Summary:
Stochastic optimization problems are powerful models for the operation of systems under uncertainty and are in general computationally intensive to solve. Two-stage stochastic optimization is one such problem, where the objective function involves calculating the expected cost of future decisions to inform the best decision in the present. In general, even approximating this expectation value is a #P-Hard problem. We provide a quantum algorithm to estimate the expected value function in a two-st...


Keywords: optimization, quant

arxiv.org | Yesterday
Summary:
In the near term, quantum approximate optimization algorithms (QAOAs) hold great potential to solve combinatorial optimization problems. These are hybrid algorithms, i.e., a combination of quantum and classical algorithms. Several proof-of-concept applications of QAOAs for solving combinatorial problems, such as portfolio optimization, energy optimization in power systems, and job scheduling, have been demonstrated. However, whether QAOAs can efficiently solve optimization problems from classica...


Keywords: algorithms, optimization, quant

arxiv.org | Yesterday
Summary:
Sea Horse Optimizer (SHO) is a noteworthy metaheuristic algorithm that emulates various intelligent behaviors exhibited by sea horses, encompassing feeding patterns, male reproductive strategies, and intricate movement patterns. To mimic the nuanced locomotion of sea horses, SHO integrates the logarithmic helical equation and Levy flight, effectively incorporating both random movements with substantial step sizes and refined local exploitation. Additionally, the utilization of Brownian motion fa...


Keywords: optimization

dev.to | Yesterday
Summary:
In Go, pointers are variables that store memory addresses, enabling indirect referencing and manipulation of data stored in memory. While pointers provide flexibility, they also introduce complexity and potential pitfalls such as memory leaks, null p...


Keywords: analysis, optimization, ios

arxiv.org | Yesterday
Summary:
We present new stellarator equilibria that have been optimized for reduced turbulent transport using nonlinear gyrokinetic simulations within the optimization loop. The optimization routine involves coupling the pseudo-spectral GPU-native gyrokinetic code GX with the stellarator equilibrium and optimization code DESC. Since using GX allows for fast nonlinear simulations, we directly optimize for reduced nonlinear heat fluxes. To handle the noisy heat flux traces returned by these simulations, we...


Keywords: gpu, optimization


Please log in to see more search results.