338 Matching Annotations
  1. Last 7 days
  2. Apr 2021
  3. Mar 2021
  4. Feb 2021
    1. Typically, a process associated with a controlling terminal is foreground process and its process group is called foreground process group. When you start a process from the command line, it's a foreground process:
    1. The shell process itself is in yet another process group all of its own and so doesn't receive the signal when one of those process groups is in the foreground. It's that simple.
    2. Switching "jobs" between foreground and background is (some details aside) a matter of the shell telling the terminal which process group is now the foreground one.
  5. Jan 2021
    1. Utterly encapsulating gapless dark ambient experience.

      Now there's a touchstone for the ages

  6. Dec 2020
  7. Nov 2020
    1. EBF was much more potent than Pax5 in inducing B celldevelopment, as its expression in MPPs yielded at least 100-foldmore B lineage progeny than did expression of Pax5 (Fig. 3band data not shown). These data suggest that promotion of B cellgeneration from MPPs by EBF is not mediated solely throughactivation of Pax5 expression.

      EBF expression represses and restricts alternative lineage genes, also help promote B cell independently of Pax 5.

    1. We do not utilize a formulaic or standard, formalized benchmarking level or element in setting our executive compensation relative to that of other companies. 
  8. Oct 2020
    1. It happened in 2000, when Gore had more popular votes than Bush yet fewer electoral votes, but that was the first time since 1888.

      it happened again in 2016

    1. Subgroups of the computer underground with different attitudes and motives use different terms to demarcate themselves from each other. These classifications are also used to exclude specific groups with whom they do not agree.
    1. The default groups, that we talked about before, like domain users and domain admins are security groups. They're used to grant or deny access to IT resources.
    2. A distribution group, is only designed to group accounts and contacts for email communication. You can't use distribution groups for assigning permission to resources.
  9. moodle.southwestern.edu moodle.southwestern.edu
    1. unbiased

      The Republican party will never stop claiming the media is bias, so I am surprised they are claiming they have resolved this issue. I would think they would want to keep acknowledging it as an issue.

  10. moodle.southwestern.edu moodle.southwestern.edu
    1. "The President has been regulating to death a free market economy" - it's interesting how much this preamble throws Trump under the bus

    2. "our enemies no longer fear us and our friends no long trust us" - I guess the democrats and republicans agree on this.

    3. "This platform is optimistic because the American people are optimistic." This is completely unsupported by everything stated before it.

    4. "covenant" "Creator" "God-given natural resources" "prepared to deal with evil in the world" show religious tone

    1. Friends and foes alike neither admire nor fear President Trump’s leadership

      I feel like there are countries who fear his leadership.

    2. The challenges before us—the worst public health crisis in a century, the worst economic downturn since the Great Depression, the worst period of global upheaval in a generation, the urgent global crisis posed by climate change, the intolerable racial injustice that still stains the fabric of our nation—will test America’s character like never before.

      I know that we are making history but it doesn't exactly feel like it. The election feels like a joke. There is a stark difference between what came out of Roosevelt's mouth and either of the presidential candidates mouth's. Now it is a matter of choosing the lesser of two evils than a heroic leader to help our country achieve greatness.

    3. a more perfect union

      I feel like this goal has been abandoned.

  11. Sep 2020
    1. So how should we think about federalism in the ageof coronavirus? The answer is to emphasize theimportance of building social solidarity — the beliefin a shared fate for all Americans that transcendsstate or regional identities

      What makes Americans not have a social solidarity?

    2. institutional antagonism willprevent the concentration of power, encouragesindividualist mentalities that lead to self-interestedactions and erode national unity.

      What makes Americans so individualistic? What is different about Taiwan’s society that made their people more selfless?

    1. “We’re changing federalism from the idea of shared expertise in different policy areas into partisan stakes in the ground that are meant to obstruct opponents,” Robertson says.

      This is so true with the Trump Administrations "Alternative Facts" it is as though we will soon be living in the dystopian novel Brave New World.

    2. “The coronavirus response is actually sort of a perfect measuring stick of our transition to our contemporary, very polarized model of federalism.”

      I want to reference the Netflix documentary Social Dilemma. The documentary says that the reason politics has become so polarized is because of social media. Everyone is operating off of a different set of facts.

    3. He has threatened to withhold federal funds from school districts that don’t open for in-person instruction.

      Is it within Trump's right to do this?

    4. He has threatened to withhold federal funds from school districts that don’t open for in-person instruction.

      Is it within trump's rights to do this?

    1. It could create incentives for action by conditioning a portion of funds going to states in any future relief packages on states’ adherence to the measures

      Why did this not happen? I feel like it isn’t the federalist system in general that are failing us— it’s the leaders of the system. Why did congress not make a playbook and create incentives for states to follow them? This reminds me of how the drinking age became 21 in every state from the funding of the highways.

    2. Lacking strong federal leadership to guide a uniform response, the United States quickly fulfilled the World Health Organization’s prediction that it would become the new epicenter of Covid-19.

      I wonder if a democrat was in office when covid hit if we would have stronger federal leadership. Would we have been in a state of emergency if someone who believed in the facts of science wasn’t in office? I have trouble believing that there is nothing the president could have done to prevent covid from getting this out of hand.

    3. subject to constitutionally protected individual rights such as due process, equal protection, and freedom of travel and association

      I didn’t know that it is within our rights to travel and associate with whomever we choose. I wouldn’t think the government would be able to control who would be able to leave their house or hang out with who anyway. I guess this shows how right the article about uninformed citizens we read last week is right.

    4. Strong, decisive national action is therefore imperative.

      I could not agree with this statement more. I think if the US had some kind of national healthcare program the coronavirus would be much more under control.

    1. El matrimonio igualitario Argentina, Uruguay, México, Brasil y Colombia son los únicos países de América Latina que han legalizado el matrimonio de parejas homosexuales, con todas las condiciones legales que tienen los matrimonios convencionales. De igual manera, Holanda, Bélgica, Suecia, Alemania, Sudáfrica, España, Inglaterra, Portugal y otras 12 naciones más han hecho lo propio.   Entretanto, sólo 11 países permiten la unión civil entre parejas del mismo sexo (no incluye todos los derechos legítimos maritales) entre estos Ecuador, Chile, Austria, Italia y Grecia. Cambio de identidad El proceso de cambio de género o sexo es un proceso quirúrgico y psicológico que contempla el cambio físico. En la actualidad, naciones como Venezuela, Colombia, Uruguay, Bolivia y Perú permiten que la transformación también sea legal, con el cambio del nombre y género en los documentos de identidad de las personas LGBTI. Sin embargo, en Brasil y Argentina, este tipo de decretos han sido desaprobados o son procesos difíciles por lo riguroso de los exámenes y requisitos que truncan el derecho al trámite. Igualdad en derechos patrimoniales Las garantías, protecciones legales en los matrimonios tras el fallecimiento y divorcio también son logros alcanzados en menos de 20 años por la comunidad LGBTI. Pero estos aún están condicionados dependiendo del país, por la diferencia entre permitir la unión civil (algunos derechos de cónyuges) o el matrimonio igualitario (derechos legítimos).   Adopción homoparental Uruguay, México, Canadá (el primer país en permitirlo en 1999) y algunos estados de EE.UU. han legalizado la adopción para personas unidas del mismo sexo. Asimismo, España, Holanda, Francia y otros permiten que las parejas no heterosexuales puedan tener hijos por medio de la adopción legal. Protección a víctimas de discriminación Hasta 1948 la homosexualidad era considerada una enfermedad mental, pero esto cambió lo que permitió la apertura de sistemas de protección a víctimas de discriminación y agresión. En la actualidad, existen programas de atención social y judicial para el seguimiento de los casos de hostigamiento y asesinatos contra los homosexuales. Además hay coberturas de salud gratuitas para tratar enfermedades como el sida y la programas de integración laboral en distintas áreas. Tags Día contra la Homofobia LGBTI Derechos Discriminación BBC - La Vanguardia - El Excelsior - La Semana Por: teleSUR- db - SB - JCM Noticias Relacionadas OLP exhorta a Oriente Medio a tomar medidas contra Guatemala Bolivia afirma que Venezuela frena dominación de EE.UU. Chavismo toma Caracas en cierre de campaña de Nicolás Maduro Rodríguez: Comicios en Venezuela definen futuro de América Lati googletag.cmd.push(function() { googletag.display('div-gpt-ad-1493942656293-0'); });//]]>--> por Taboolapor TaboolaEnlaces PatrocinadosEnlaces PatrocinadosEnlaces PromovidosEnlaces PromovidosTe RecomendamosHepatitis C | Search AdsSigns of Hepatitis C (Some May Surprise)Hepatitis C | Search AdsPeoplewhizOne Thing All Cheaters Have In Common, Brace YourselfPeoplewhizDID U KNOW ReviewsUnsold 2019 SUVs Going for Pennies on the Dollar: Great For SeniorsDID U KNOW ReviewsDownload Now on Google Play | Neverland CasinoSan Jose Woman Was Playing on This Free Slot Machine App, When All Of A Sudden She Won BigDownload Now on Google Play | Neverland CasinoGet it on Google Play | House Of FunCasinos Will Hate You For Doing This but They Can’t Stop YouGet it on Google Play | House Of FunFungus Clear SupplementsSurgeon: Nail Fungus? Do This Immediately (Watch)Fungus Clear SupplementsCCPA Notice window._taboola = window._taboola || []; _taboola.push({ mode: 'thumbnails-a', container: 'taboola-below-article-thumbnails', placement: 'Below Article Thumbnails', target_type: 'mix' }); window.fbAsyncInit = function() { FB.init({ appId : '1009084795820552', xfbml : true, version : 'v2.5' }); }; (function(d, s, id){ var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) {return;} js = d.createElement(s); js.id = id; js.src = "//connect.facebook.net/es_LA/sdk.js"; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); (function(d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = "//connect.facebook.net/es_LA/sdk.js#xfbml=1&version=v2.5&appId=1009084795820552"; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); $(document).ready(function () { $("#comentNativos").addClass("coment"); $("#btn-face").addClass("activeComent"); $("#btn-cf").click(function () { // alert("btn-facebook"); $("#comentNativos").addClass("coment"); $("#btn-face").addClass("activeComent"); $(".fb_ltr").css({width: "940px"}); $("#comentFace").removeClass("coment"); $("#btn-nativo").removeClass("activeComent"); }); $("#btn-cn").click(function () { // alert("btn-nativo"); $("#comentFace").addClass("coment"); $("#comentNativos").removeClass("coment"); $("#btn-nativo").addClass("activeComent"); $("#btn-face").removeClass("activeComent"); }); }); Comentarios con facebook () Comentarios con teleSUR (0) Comentarios 0 Ingresa o Regístrate para poder comentar, usar el foro y más Ingresar Regístrate Nota sin comentarios. //]]>--> footer .legal{ font-size:15px; background:var(--bg-footer-legal,#1c2036); border-bottom: 2px solid #fff; opacity:.5; float:left; } footer .colFootRedes .wpFootSuscrip input[type="text"]:focus{ border: 2px solid #555; border-radius:5px; width:320px; height:46px; } footer .colFootRedes .wpFootSuscrip input[type="text"]{ border: 2px solid #555; border-radius:5px; width:320px; height:46px; } footer .colFooti h4{ color:transparent; cursor:context-menu; } .vivoFooter{ position:relative; } .vivoFooter h4{ position:absolute; margin-top: 6%; margin-left:8em; } footer .wpRedesFoot{ top:135px; border:none; } footer .wpRedesFoot a{ margin-top:-20px; } footer .wpRedesFoot a:hover{ opacity:0.5; } .vivoFooterBoton{ Width:25em; height:3.5em; border-radius:5px; border: none; color:#fff; margin-top:5px; background:#9a1212; transition:1s; font-weight:bolder; } .vivoFooterBoton:hover{ opacity:0.8; transition:1s; } .vivoFooterBoton a{ font-size:16px; } .colFoot img{ margin-left:3px; margin-bottom:-5%; } footer .colFoot{ font-size:12px; line-height:15px; } .colFooti a{ font-size:14px; line-height:15px; } footer .colFootRedes .wpFootSuscrip input[type="submit"]{ background:url("/https://www.telesurtv.net/arte/subNew.png"); background-repeat: no-repeat; width:9%; line-height:32px; margin-left:0px; color:transparent; } footer .colFooti{ color:transparent; font-size:0px; cursor:context-menu; } @media only screen and (max-width: 600px) { footer .wpRedesFoot a{ margin-right:-5px; } footer .colFootRedes .wpFootSuscrip input[type="text"]{ width:210px; } footer .colFootRedes .wpFootSuscrip input[type="text"]:focus{ width:210px; } footer .colFootRedes .wpFootSuscrip input[type="submit"]{ width:12%; color:transparent; } .vivoFooterBoton{ width:20em; margin-top:8px; margin-bottom:5px; } footer .colFooti{ margin-left:28%; margin-bottom:5%; } } Términos de uso Sobre teleSUR Acerca teleSUR Contactos Equipo Empleos Terminos de uso Cobertura satelital Canales Latinoamérica y el Caribe Mundo Deportes Cultura Opinión Programación Servicios Catálogo Multimedia Blog Videos teleSUR Inglés teleSUR Inglés
  12. Aug 2020
  13. Jul 2020
  14. Jun 2020
  15. May 2020
  16. Apr 2020
    1. The world’s largest exhibitions organizer, London-based Informa plc, outlined on Thursday morning a series of emergency actions it’s taking to alleviate the impact of the COVID-19 pandemic on its events business, which drives nearly two-thirds of the company’s overall revenues. Noting that the effects have been “significantly deeper, more volatile and wide-reaching,” than was initially anticipated, the company says it’s temporarily suspending dividends, cutting executive pay and issuing new shares worth about 20% of its total existing capital in an effort to strengthen its balance sheet and reduce its approximately £2.4 billion ($2.9 billion) in debt to £1.4 billion ($1.7 billion). Further, Informa says it’s engaged in “constructive discussions” with its U.S.-based debt holders over a covenant waiver agreement.

      Informa Group, que posee editoriales como Taylor & Francis, de Informa Intelligent Division toma medidas en su sector de conferencias y eventos. Provee dos tercios de sus ingresos totales, 2.9 billion dólares. Emite acciones y para el mercado norteamericano acuerdos de deuda. Mientras la parte editorial que aporta un 35% de los ingresos se mantiene sin cambios y con pronósticos estables y sólidos. Stephen Carter CEO

  17. Jan 2020
    1. hyperphagia
    2. anteverted nares
    3. short nose
    4. low-set ears
    5. widely spaced eyes
    6. thick eyebrows
    7. flat face
    8. dolichocephaly
    9. speech impairment
    10. severe developmental delay
    1. aortic dilatation
    2. small patent ductus arteriosus
    3. ventricular septal defect
    4. atrial septal defect
    5. mitral valve regurgitation
    6. aggressive behaviors
    7. attention deficit hyperactivity disorder
    8. central obesity
    9. cryptorchidism
    10. Talipes equinovarus
    11. arachnodactyly
    12. scoliosis
    13. excavatum
    14. pectus carinatum
    15. short philtrum
    16. large ears
    17. midface hypoplasia
    18. open-mouth appearance
    19. long face
    20. hypotonia
    21. tall stature
    22. intellectual disability (ID)
    23. developmental delay
    1. Suppose the algorithm chooses a tree that splits on education but not on age. Conditional on this tree, the estimated coefficients are consistent. But that does not imply that treatment effects do not also vary by age, as education may well covary with age; on other draws of the data, in fact, the same procedure could have chosen a tree that split on age instead

      a caveat

    2. hese heterogenous treatment effects can be used to assign treatments; Misra and Dubé (2016) illustrate this on the problem of price targeting, applying Bayesian regularized methods to a large-scale experiment where prices were randomly assigned

      todo -- look into the implication for treatment assignment with heterogeneity

    3. Chernozhukov, Chetverikov, Demirer, Duflo, Hansen, and Newey (2016) take care of high-dimensional controls in treatment effect estimation by solving two simultaneous prediction problems, one in the outcome and one in the treatment equation.

      this seems similar to my idea of regularizing on only a subset of the variables

    4. These same techniques applied here result in split-sample instrumental variables (Angrist and Krueger 1995) and “jackknife” instrumental variables

      some classical solutions to IV bias are akin to ML solutions

    5. Understood this way, the finite-sample biases in instrumental variables are a consequence of overfitting.

      traditional 'finite sample bias of IV' is really overfitting

    6. Even when we are interested in a parameter β ˆ, the tool we use to recover that parameter may contain (often implicitly) a prediction component. Take the case of linear instrumental variables understood as a two-stage procedure: first regress x = γ′z + δ on the instrument z, then regress y = β′x + ε on the fitted values x ˆ. The first stage is typically handled as an estimation step. But this is effectively a prediction task: only the predictions x ˆ enter the second stage; the coefficients in the first stage are merely a means to these fitted values.

      first stage of IV -- handled as an estimation problem, but really it's a prediction problem!

    7. Prediction in the Service of Estimation

      This is especially relevant to economists across the board, even the ML skeptics

    8. New Data

      The first application: constructing variables and meaning from high-dimensional data, especially outcome variables

      • satellite images (of energy use, lights etc) --> economic activity
      • cell phone data, Google street view to measure wealth
      • extract similarity of firms from 10k reports
      • even traditional data .. matching individuals in historical censuses
    9. Zhao and Yu (2006) who establish asymptotic model-selection consistency for the LASSO. Besides assuming that the true model is “sparse”—only a few variables are relevant—they also require the “irrepresentable condition” between observables: loosely put, none of the irrelevant covariates can be even moderately related to the set of relevant ones.

      Basically unrealistic for microeconomic applications imho

    10. First, it encourages the choice of less complex, but wrong models. Even if the best model uses interactions of number of bathrooms with number of rooms, regularization may lead to a choice of a simpler (but worse) model that uses only number of fireplaces. Second, it can bring with it a cousin of omitted variable bias, where we are typically concerned with correlations between observed variables and unobserved ones. Here, when regular-ization excludes some variables, even a correlation between observed variables and other observed (but excluded) ones can create bias in the estimated coefficients.

      Is this equally a problem for procedures that do not assum sparsity, such as the Ridge model?

    11. 97the variables are correlated with each other (say the number of rooms of a house and its square-footage), then such variables are substitutes in predicting house prices. Similar predictions can be produced using very different variables. Which variables are actually chosen depends on the specific finite sample.

      Lasso-chosen variables are unstable because of what we usually call 'multicollinearity.'<br> This presents a problem for making inferences from estimated coefficients.

    12. Through its regularizer, LASSO produces a sparse prediction function, so that many coefficients are zero and are “not used”—in this example, we find that more than half the variables are unused in each run

      This is true but they fail to mention that LASSO also shrinks the coefficients on variables that it keeps towards zero (relative to OLS). I think this is commonly misunderstood (from people I've spoken with).

    13. One obvious problem that arises in making such inferences is the lack of stan-dard errors on the coefficients. Even when machine-learning predictors produce familiar output like linear functions, forming these standard errors can be more complicated than seems at first glance as they would have to account for the model selection itself. In fact, Leeb and Pötscher (2006, 2008) develop conditions under which it is impossible to obtain (uniformly) consistent estimates of the distribution of model parameters after data-driven selection.

      This is a very serious limitation for Economics academic work.

    14. First, econometrics can guide design choices, such as the number of folds or the function class.

      How would Econometrics guide us in this?

    15. These choices about how to represent the features will interact with the regularizer and function class: A linear model can reproduce the log base area per room from log base area and log room number easily, while a regression tree would require many splits to do so.

      The choice of 'how to represent the features' is consequential ... it's not just 'throw it all in' (kitchen sink approach)

    16. Ta b l e 2Some Machine Learning Algorithms

      This is a very helpful table!

    17. Picking the prediction func-tion then involves two steps: The first step is, conditional on a level of complexity, to pick the best in-sample loss-minimizing function.8 The second step is to estimate the optimal level of complexity using empirical tuning (as we saw in cross-validating the depth of the tree).

      ML explained while standing on one leg.

    18. egularization combines with the observability of predic-tion quality to allow us to fit flexible functional forms and still find generalizable structure.

      But we can't really make statistical inferences about the structure, can we?

    19. This procedure works because prediction quality is observable: both predic-tions y ˆ and outcomes y are observed. Contrast this with parameter estimation, where typically we must rely on assumptions about the data-generating process to ensure consistency.

      I'm not clear what the implication they are making here is. Does it in some sense 'not work' with respect to parameter estimation?

    20. In empirical tuning, we create an out-of-sample experiment inside the original sample.

      remember that tuning is done within the training sample

    21. Performance of Different Algorithms in Predicting House Values

      Any reason they didn't try a Ridge or an Elastic net model here? My instinct is that these will beat LASSO for most Economic applications.

    22. We consider 10,000 randomly selected owner-occupied units from the 2011 metropolitan sample of the American Housing Survey. In addition to the values of each unit, we also include 150 variables that contain information about the unit and its location, such as the number of rooms, the base area, and the census region within the United States. To compare different prediction tech-niques, we evaluate how well each approach predicts (log) unit value on a separate hold-out set of 41,808 units from the same sample. All details on the sample and our empirical exercise can be found in an online appendix available with this paper athttp://e-jep.org

      Seems a useful example for trying/testing/benchmarking. But the link didn't work for me. Can anyone find it? Is it interactive? (This is why I think papers should be html and not pdfs...)

    23. Making sense of complex data such as images and text often involves a prediction pre-processing step.

      In using 'new kinds of data' in Economics we often need to do a 'classification step' first

    24. The fundamental insight behind these breakthroughs is as much statis-tical as computational. Machine intelligence became possible once researchers stopped approaching intelligence tasks procedurally and began tackling them empirically.

      I hadn't thought about how this unites the 'statistics to learn stuff' part of ML and the 'build a tool to do a task' part. Well-phrased.

    25. In another category of applications, the key object of interest is actually a parameter β, but the inference procedures (often implicitly) contain a prediction task. For example, the first stage of a linear instrumental variables regres-sion is effectively prediction. The same is true when estimating heterogeneous treatment effects, testing for effects on multiple outcomes in experiments, and flexibly controlling for observed confounders.

      This is most relevant tool for me. Before I learned about ML I often thought about using 'stepwise selection' for such tasks... to find the best set of 'control variables' etc. But without regularisation this seemed problematic.

    26. Machine Learning: An Applied Econometric Approach

      Shall we use Hypothesis to have a discussion ?

  18. Dec 2019
    1. coagulopathy
    2. hyperammonemia
    3. Abnormal femoral head epiphysis
    4. Irregular vertebrae
    5. Hypoplastic vertebrae
    6. INR
    7. RALF
    8. Hepatomegaly
    9. Prothrombin time
    10. Total bilirubin
    11. AST
    12. ALT
    13. Glucose