Amit Levi
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Articles by Amit Levi
Computer Science > Data Structures and Algorithms
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Why Papaya Global’s Workforce Platform Was Built For The C-suite
The workforce has changed. The way companies fund and pay that workforce hasn’t kept up. For decades, payroll and workforce management were operational functions. Necessary. Important. But tactical. Today, they sit at the center of capital strategy. When companies operate across 180+ countries, manage employees, contractors, and contingent workers, and move money across borders daily, workforce payments become one of the largest and most complex financial flows in the enterprise.
[2602.04894] Extracting Recurring Vulnerabilities from Black-Box LLM-Generated Software
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
When Local and Non-Local Meet: Quadratic Improvement for Edge Estimation with Independent Set Queries
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
[2512.24143] Activation Steering for Masked Diffusion Language Models
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Papaya Global and Sumsub Partner to Provide Clients with AI-Powered Fraud Prevention and Customer Verification
Papaya Global, the workforce payroll and payments platform, and Sumsub, a full-cycle verification and compliance solutions provider, today announce their new partnership. Sumsub will support Papaya Global with AI-powered automated solutions for secure verification and fraud prevention, while maintaining speed, accuracy, and regulatory compliance. The partnership ensures compliant payment transfers for companies and their workforce throughout the world.
[2308.15988] Support Testing in the Huge Object Model
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
[2202.13060] Graph Attention Retrospective
[Submitted on 26 Feb 2022 ( v1 ), last revised 22 May 2023 (this version, v5)] Title:Graph Attention Retrospective Download a PDF of the paper titled Graph Attention Retrospective, by Kimon Fountoulakis and 4 other authors Download PDF Abstract: Graph-based learning is a rapidly growing sub-field of machine learning with applications in social networks, citation networks, and bioinformatics. One of the most popular models is graph attention networks.
First Come, First Served (FCFS)
What Does First Come, First Served (FCFS) Mean? First Come, First Served (FCFS) is a type of scheduling algorithm used by operating systems and networks to efficiently and automatically execute queued tasks, processes and requests by the order of their arrival. An FCFS scheduling algorithm may also be referred to as a first-in, first-out (FIFO) algorithm or a first-come, first-choice (FCFC) algorithm.
What is View? - Definition from Techopedia
What Does View (SQL View) Mean? A view is a subset of a database that is generated from a user query and gets stored as a permanent object. In a structured query language (SQL) database, for example, a view becomes a type of virtual table with filtered rows and columns that mimic those of the original database. While the table generated in a view is permanent, the data within fields is subject to change according to the source database.
A Look Inside the Modern Analytics Stack
Click here to learn more about Amit Levi. In the data-driven world we live in today, the field of analytics has become increasingly important to remain competitive in business. In fact, a study by McKinsey Global Institute shows that data-driven organizations are 23 times more likely to outperform competitors in customer acquisition and nine times as likely to surpass them in customer loyalty.
Bye Bye, BI: Why Companies Should Transition to AI for Better Business Monitoring
Click here to learn more about Amit Levi. We’ve come to rely on business intelligence (BI) tools as an essential part of business decision-making. From dashboards to automated reports, BI tools allow us to cash in our data for top-level insights. We won’t deny that using traditional BI tools can make tasks such as reporting much more efficient, but the reality is that they can create a false sense of security surrounding data awareness.
Parallel Processing
Techopedia Explains Parallel Processing Parallel processing runs two or more task segments simultaneously on multiple processors to reduce the overall time for processing massive volumes of data. How Parallel Processing Works In parallel processing, a complex task is split into multiple smaller tasks that are more proportionate in processing requirements, size, and number to the processing units on hand.
How Retailers Can Use AI Analytics to Increase Revenue
Powerful computing advances in recent years have enabled retailers to use artificial intelligence (AI) to help them realize their full potential. AI analytics uses machine learning to find differences and make assumptions automatically. A study byBusiness Insider suggests that as much as 85 percent of customer interactions will be controlled without a human by as soon as 2020. This is no more apparent than in the e-commerce and retail sectors.
How Retailers Can Use AI Analytics to Increase Revenue
Powerful computing advances in recent years have enabled retailers to use artificial intelligence (AI) to help them realize their full potential. AI analytics uses machine learning to find differences and make assumptions automatically. A study byBusiness Insider suggests that as much as 85 percent of customer interactions will be controlled without a human by as soon as 2020. This is no more apparent than in the e-commerce and retail sectors.
Four Key Attributes of Advanced Anomaly Detection
(arleksey/Shutterstock) AI anomaly detection is just one tool in an arsenal that Gartner now refers to as augmented analytics, but it’s among the most important. By providing real-time intelligence into both positive and negative anomalies, AI anomaly detection offers opportunities to recapture revenue, capitalize on moment-to-moment trends, and sidestep brand damage. But before we get into the four attributes of advanced anomaly detection, a couple of counter examples are in order.
4 Ways AI-Driven ETL Monitoring Can Help Avoid Glitches
ETL (extract, transform and load) is one of the most important processes in big data analytics — and simultaneously, it can be one of its biggest bottlenecks. (For more on big data, check out 5 Helpful Big Data Courses You Can Take Online.) The reason ETL is so important is that most data a business collects is not ready, in its raw form, for an analytics solution to digest.
4 Ways AI-Driven ETL Monitoring Can Help Avoid Glitches
ETL (extract, transform and load) is one of the most important processes in big data analytics — and simultaneously, it can be one of its biggest bottlenecks. (For more on big data, check out 5 Helpful Big Data Courses You Can Take Online.) The reason ETL is so important is that most data a business collects is not ready, in its raw form, for an analytics solution to digest.
Fintech Analytics: The Top 7 Metrics Every Fintech Company Should Monitor
In an incredibly competitive sector, fintech companies collecting big data streams should ask themselves: How do I make sure I’m poised to take advantage of market opportunities the moment they emerge? How do I diagnose and fix incidents before they have time to impact my business? How do I monitor the information I need to stay ahead? Am I monitoring the right data? Agility and innovation in fintech depend not only on collecting the data, but how you’re able to leverage it.
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