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Is there art in number?

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Recent Questions - Mathematics Stack Exchange most recent 30 from

  • official name of algebraic system
    by rko15 on July 10, 2020 at 9:49 pm

    What is the official name of an additive abelian group with a biadditive multiplication (left and right distributivity of multiplication over addition and no other assumptions)?

  • solution of $f'(x)+f(-x)=e^{-x^2}$
    by zeraoulia rafik on July 10, 2020 at 9:49 pm

    let $f$ be a function such that $f:\mathbb{R}\to \mathbb{R}$, I want to determine all functions of class $C^1$ such that $f'(-x)+f(x)=e^{-x^2}$ for all $x\in \mathbb{R}$, Now we have $f'(-x)+f(x)=e^{-x^2}$ this implies that $f'(x)=e^{-x^2}-f(-x)$, since $f'$ is of class $C^1$ this means that $f$ is of class $c^2$, That equation equivalent to : $f''(x)=-2x e^{-x^2}-f'(-x)$ implies to $f''(x)-f(x)=-2x e^{-x^2}-e^{x^2}$ , if I take now $x\mapsto \lambda\cos(x)+\mu\sin(x),\lambda,\mu\in\mathbb R$ as a solution without second term in order to get particular solution it would be complicated and given by error function which forbide me to get a general solution, I ask now if there is any simple way to solve that functional ?

  • Why is -1 not a prime number?
    by BobS on July 10, 2020 at 9:49 pm

    I understand the reason 1 is not considered to be a prime number, but what is the reasoning for -1 not being considered a prime number? It's only factors are 1 and itself, -1, wouldn't that make it a prime number?

  • Classification of weak del Pezzo surfaces
    by diracula on July 10, 2020 at 9:47 pm

    In this question I work over the complex numbers. Up to isomorphisms, the del Pezzo surfaces are the blow-ups of the projective plane $\mathbb{P}^2$ at $0 \leq n \leq 8$ points in general position (ignoring the possibility of the product $\mathbb{P}^1 \times \mathbb{P}^1$). In the extension to the weak or almost del Pezzo surfaces, the points are instead in almost general position (ignoring the possibility of the product $\mathbb{P}^1 \times \mathbb{P}^1$ and the Hirzebruch surface $\Sigma_2$). While repositioning $n$ points in general position corresponds only to deforming the complex structure, different almost general positions involve discrete choices, giving rise to weak del Pezzo surfaces with very different properties (intersection forms, Mori cones, etc). My question is: while there are hence just 9 or 10 del Pezzo surfaces, what is the number of non-isomorphic weak del Pezzo surfaces? From reading the chapter in Dolgachev's Classical Algebraic Geometry, the classification of weak del Pezzo surfaces with $n$ blow-ups seems to essentially correspond to a choice of Dynkin diagrams whose ranks sum to at most $n$. But I have not read or understood the precise statement here. I will be happy to be directed to a textbook reference on this.

  • A question ramsey type statements
    by user1001001 on July 10, 2020 at 9:43 pm

    Suppose we ask for the minimum $R(H)$ s.t every $2-$coloring of the complete graph $K_{R(H)}$ must contain a monochromatic copy of $H$. It is known that $R(H)$ is finite for all $H$. What can be said about $R(H)$ as a function of $H$. Meaning, what types of graphs yield a lower/higher Ramsey number? Sorry if this is a bit qualitative but any ideas/known results in this general direction would be of help. Intuitively it seems, for example, that if the number of edges $m = \Theta(n)$ for some class of graphs $H_n$, then $R(H_n)\leq R(K_n)$. This might be wildly wrong though. Sorry if this is a bit qualitative but any ideas/known results in this general direction would be of help.

Bad Science Ben Goldacre's Bad Science column from the Guardian and more...

  • Evidence to House of Commons Sci Tech Select Committee on Research Integrity
    by Ben Goldacre on December 5, 2017 at 11:42 am

    Sorry not to be in regular blogging mode at the moment. Here’s a video of our evidence session to parliament, where they are running an inquiry into research integrity. I think clinical trials are the best possible way to approach this issue. Lots of things in “research integrity” are hard to capture in hard logical

  • How do the world’s biggest drug companies compare, in their transparency commitments?
    by Ben Goldacre on July 27, 2017 at 6:33 am

    Here’s a paper, and associated website, that we launch today: we have assessed, and then ranked, all the biggest drug companies in the world, to compare their public commitments on trials transparency. Regular readers will be familiar with this ongoing battle. In medicine we use the results of clinical trials to make informed treatments about

  • Meaningful Transparency Commitments: the WHO Joint Statement from Trial Funders
    by Ben Goldacre on July 26, 2017 at 4:17 pm

    By now I hope you all know about the ongoing global scandal of clinical trial results being left unpublished, and of course our AllTrials campaign. Doctors, researchers, and patients cannot make truly informed choices about which treatments work best if they don’t have access to all the trial results. Earlier this year, I helped out

  • How many epidemiologists does it take to change a lightbulb?
    by Ben Goldacre on February 1, 2017 at 12:49 pm

    Robin Ince just asked if I know any epidemiologist lightbulb jokes. I wrote this for him. How many epidemiologists does it take to change a lightbulb? We’ve found 12,000 switches hidden around the house. Some of them turn this lightbulb on, some of them don’t; some of them only work sometimes; and some of them

  • “Transparency, Beyond Publication Bias”. A video of my super-speedy talk at IJE.
    by Ben Goldacre on October 11, 2016 at 8:01 am

    People often talk about “trials transparency” as if this means “all trials must be published in an academic journal”. In reality, true transparency goes much further than this. We need Clinical Study Reports, and individual patient data, of course. But we also need the consent forms, so we can see what patients were told. We need

FlowingData Strength in Numbers

AnnMaria's Blog Words from the Prez

  • Tomorrow, I will be serious. Today, it’s quarantine clothes
    by annmaria on April 10, 2020 at 2:57 am

    In my first ever post on fashion, I discuss rules for attire in web meetings. Number one: Wear clothes.

  • The Blog Hour
    by annmaria on April 9, 2020 at 2:55 am

    To fight off quarantine boredom, my granddaughter, Eva, and I have a nightly blogging challenge. Feel free to join us.

  • Being (less) stressed during a pandemic
    by annmaria on April 8, 2020 at 2:51 am

    Want to be stressed less? Start your day with something you look forward to and check out what your public library has to offer (yes, really)

  • Everything is NOT just fine
    by annmaria on April 3, 2020 at 10:17 pm

    If you think you should be feeling as if everything is fine, STOP IT! Everything is NOT fine. Even if you are healthy and your rent is paid, there is still a pandemic.

  • 5 Basics of Consulting Success: Part 1
    by annmaria on February 24, 2020 at 1:16 am

    Of all the qualities necessary to be a successful statistical consultant, none is more important than communication, even if that communication is only with your future self.

Data & Society Data & Society advances public understanding of the social implications of data-centric technologies and automation.

  • Farewell to the Data & Society 2019-2020 Faculty Fellows
    by natalie on July 7, 2020 at 6:18 pm

    As Data & Society says goodbye to our 2019-2020 Fellows, we’re celebrating their accomplishments over the past year, from co-authoring a Feminist Data Manifest-No and deep-reading census data, to advocating for an economic justice framework in digital privacy law. Learn about the incredible work of Michele Gilman, Anita Say Chan, and Dan Bouk and their

  • Introducing the 2020-21 Data & Society Faculty Fellows
    by natalie on June 11, 2020 at 2:08 pm

    Data & Society Research Institute is thrilled to welcome Meredith D. Clark and Shaka McGlotten as its incoming 2020-2021 Faculty Fellows. Starting this September, our Faculty Fellows will bring their unique expertise to our community on Black cyberfeminist theory and journalistic practice, networked intimacies, queer theory, media, and art. The Faculty Fellows Program at Data

  • Data & Society to operate online in 2020
    by natalie on May 27, 2020 at 1:30 pm

    In response to the COVID-19 pandemic, we at Data & Society have decided that the best course for our team and our network is to continue working remotely through the end of 2020. Preserving our ability to work safely allows us to continue to spotlight critical guiding expertise during this period of unrest and uncertainty.

  • The Workplace-Surveillance Technology Boom
    by natalie on May 12, 2020 at 8:40 pm

    Explainer on workplace monitoring and surveillance cited in Slate.

  • Privacy Advocates Are Sounding Alarms Over Coronavirus Surveillance
    by natalie on May 12, 2020 at 7:57 pm

    Faculty Fellow Michele Gilman quoted on surveillance in the age of COVID-19.

MIT News - Data - Big data - Analytics - Statistics - IDSS - Operations research MIT News is dedicated to communicating to the media and the public the news and achievements of the students, faculty, staff and the greater MIT community.

  • Blockdrop to Accelerate Neural Network training by IBM Research
    by Sharmistha Chatterjee on July 9, 2020 at 9:00 pm

    Scaling AI with Dynamic Inference Paths in Neural Networks Introduction IBM Research, with the help of the University of Texas Austin and the University of Maryland, has created a technology, called BlockDrop, that promises to speed convolutional neural network operations without any loss of fidelity. This could further excel the use of neural nets, particularly in places with limited computing capability. Increase in accuracy…

  • Difference Between Correlation and Regression in Statistics
    by Vincent Granville on July 9, 2020 at 3:00 pm

    Correlation is a measure of linear association between two variables X and Y, while linear regression is a technique to make predictions, using the following model: Y = a1 X1 + ... + a…

  • How to Communicate Data
    by Stephanie Glen on July 8, 2020 at 6:02 pm

    The following graphic is based on Sam Priddy's excellent DSC/Tableau Webinar How to Accelerate and Scale Your Data Science Workflows. Sam covered many interesting points for organizing, analyzing and presenting data--including which graph is best suited for different data types. This graphic is an overview of some of Sam's points. For more…

  • Added Chapter on Reinforcement Learning to my book “Bayesuvius” on Bayesian Networks
    by Robert R. Tucci on July 7, 2020 at 9:00 pm

    I just uploaded a new chapter to my github proto-book "Bayesuvius". This chapter deals with Reinforcement Learning (RL) done right, i.e., with Bayesian Networks 🙂 My chapter is heavily based on the excellent course notes for CS 285 taught at UC Berkeley by Prof. Sergey Levine. All I did was to translate some of those lectures into B net lingo. During a recent conversation that I had on LinkedIn with some very smart Machine Learning experts, the experts opined that the fields…

  • Building a Deep-Learning-Based Movie Recommender System
    by Kate Shao on July 6, 2020 at 8:30 am

    With the continuous development of network technology and the ever-expanding scale of e-commerce, the number and variety of goods grow rapidly and users need to spend a lot of time to find the goods they want to buy. This is information overload. To solve this problem, the recommendation system came into being. The recommendation system is a…

  • Book: Evaluating Machine Learning Models
    by Emmanuelle Rieuf on March 14, 2017 at 6:12 pm

    Data science today is a lot like the Wild West: there’s endless opportunity and excitement, but also a lot of chaos and confusion. If you’re new to data science and applied machine learning, evaluating a machine-learning model can seem pretty overwhelming. Now you have help. With this O’Reilly report, machine-learning expert Alice Zheng takes you through the model…

  • Book: Python For Dummies
    by Emmanuelle Rieuf on August 25, 2016 at 10:50 pm

    Python is one of the most powerful, easy-to-read programming languages around, but it does have its limitations. This general purpose, high-level language that can be extended and embedded is a smart option for many programming problems, but a poor solution to others.  Python For Dummies is the quick-and-easy guide to getting…

  • Book: Python Machine Learning Blueprints
    by Emmanuelle Rieuf on August 24, 2016 at 8:16 pm

    Key Features Put machine learning principles into practice to solve real-world problems Get to grips with Python's impressive range of Machine Learning libraries and frameworks From retrieving data from APIs to cleaning and visualization, become more confident at tackling every stage of the data pipeline Book…

  • Book: Data Science Essentials in Python
    by Emmanuelle Rieuf on August 23, 2016 at 6:10 pm

    Go from messy, unstructured artifacts stored in SQL and NoSQL databases to a neat, well-organized dataset with this quick reference for the busy data scientist. Understand text mining, machine learning, and network analysis; process numeric data with the NumPy and Pandas modules; describe and analyze data using statistical and…

  • Book: Statistics for Non-Statisticians
    by Emmanuelle Rieuf on August 23, 2016 at 1:08 am

    Aimed at practitioners The presentation is as non-mathematical as possible Includes many examples of the use of statistical functions in spreadsheets Employs a realistic sample survey as an exemplar throughout the book Fills a gap in the existing literature on…

  • Book: Systems Analytics: Adaptive Machine Learning workbook
    by Emmanuelle Rieuf on August 10, 2016 at 5:45 pm

    SYSTEMS Analytics title refers to a new development effort in the field of Machine Learning grounded firmly in Systems Theory; the subtitle, “ADAPTIVE Machine Learning”, captures the link to the current state of the art. My intention in writing this book is to bring mathematically trained graduates in engineering, physics, mathematics and…

  • Book: Superforecasting: The Art and Science of Prediction
    by Emmanuelle Rieuf on August 3, 2016 at 11:11 pm

    To be published on September 13, 2016; you can pre-order here ($17.) By Philip Tetlock and Dan Gardner. 352 Pages.Everyone would benefit from seeing further into the future, whether buying stocks, crafting…

  • Book: Efficient R Programming
    by Emmanuelle Rieuf on July 1, 2016 at 5:37 am

    This is the online version of the O’Reilly book: Efficient R programming.  To build the book: Install the latest version of RIf you are using RStudio, make sure that’s up-to-date as wellInstall the book dependencies.…

  • Python Machine Learning
    by Emmanuelle Rieuf on June 28, 2016 at 7:01 pm

    Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsAbout This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems…

  • Book: Effective Data Visualization: The Right Chart for the Right Data
    by Emmanuelle Rieuf on June 28, 2016 at 6:38 pm

    Written by sought-after speaker, designer, and researcher Stephanie D. H. Evergreen, Effective Data Visualizationshows readers how to create Excel charts and graphs that best communicate data findings. This comprehensive how-to guide functions as a set of blueprints—supported by research and the author’s extensive experience with clients in industries all over the world—for conveying data in an impactful way. Delivered in Evergreen’s humorous and approachable style, the book covers the…