快连软件下载安装

Update May 23rd. Final update for this post. I’m happy to report that the Danish government – in part based on input from our advisory board – has decided to base the Danish contact tracing app on the DP-3T (as implemented by Google and Apple) framework. Details here http://www.sum.dk/Aktuelt/Nyheder/Coronavirus/2023/Maj/Politisk-aftale-om-frivillig-smittesporingsapp-for-covid-19.aspx

Update May 1st. Here’s another update. It also turns out the advisory board wasn’t officially announced until today. I hope the unintended embargo-breaking below won’t have any serious consequences. Here’s the official press release: http://digst.dk/nyheder/nyhedsarkiv/2023/maj/nyt-advisory-board-skal-raadgive-myndighederne-om-den-kommende-danske-smittestops-app/ see also here.

Update: April 27th, 2023. Well, it turns out I was wrong about Reason 1 below. And that I have lousy timing in writing blogposts with declarations in them.

Pretty much right after finishing the post below (original post was written on April 26th), I was invited to be a member of a newly established Advisory Board for the official Danish Contact Tracing App. The goal of the advisory board is to provide advice/feedback for the Agency for Digitization and the Ministry of Health regarding the App.

Since I care a lot about doing digital contact tracing in the right way (with respect to privacy & epidemiological relevance), I accepted the offer to join. Clearly that changes some aspects of what I’ve written below.

Over the past few weeks, I’ve commented on contact tracing in the Danish press. But starting today, I am going to stop chiming in on this topic.

Reason 1 is that I don’t feel like I’m making much of an impact in terms of where the official app is going (which was my main reason to start speaking about this in the first place). Reason 2 is that the news on this topic are moving fast and staying updated is exhausting. Reason 3 is that engagement in this topic is drawing me away from the deep & long-term work that I want to be focusing on. And finally, Reason 4 is that contact tracing connects deeply to projects I did years ago, so it feels a bit removed from my current core scientific work of network science and mobility modeling. Thus, I’ll be doing my best to pipe down from now on.

If you want updated info about contact tracing in Denmark, I recommend checking out Henrik Moltke’s twitter feed. For the overall (epidemiology and privacy) view on contact tracing, I personally follow Marcel Salathe at EPFL.

Here are my two key points on contact tracing:

• A decentralized protocol (such as DP-3T) is the best way to do things.
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快连软件下载安装

In the beginning of the epidemic, I supported (and made a small contribution to) the PEPP-PT initiative, which was then more of an umbrella organization, also including DP-3T. See 电脑版ssr如何使用 from DTU. At some point there was an internal argument (which I know nothing about), resulting in a split into a centralized (still privacy preserving) paradigm embodied by PEPP-PT and a decentralized paradigm represented by DP-3T and also incorporated in the Apple/Google solution to contact tracing.

I have provided continuous updates on my attitude towards this issue via Twitter. See below

快连软件下载安装

An important point to make when it comes to contact tracing is that it might not be a very good solution. Many of the issues are discussed in this Twitter thread by UNICEF Machine Learning Lead & Principal Researcher Vedran Sekara.

I’ve also talked about these issues in the Danish Press.

• Version2 (April 20th, 2023): DTU-professor advarer: Lad være at forvente for meget af corona-apps. This article provides has details on potential technical issues related to how we convert info on Bluetooth scans to an understanding of epidemiological interactions.
• Information (April 18th, 2023): Apple og Google lancerer værktøj, som vil kunne spore spredning af COVID-19. Here, I discuss the Google/Apple solution and how we leak data in many different contexts.
• Weekendavisen (April 3rd, 2023): Fagre nye færden. Talks about surveillance more generally.

Starting march 1st this year, I was promoted to full professor at DTU! Pretty exciting. And if you want proof, take a look at my ssr 下载 (conveniently screen-shot and marked up below).

We’re lucky to have Lab Alum Arkadiusz ‘Arek’ Stopczynski visiting the lab on January 9th and 10th. On the 9th, he’s busy being examiner at a PhD Defense, but on his second day in Denmark, he’s going to give a talk to tell us about what he’s been up to since starting at Google af couple of years ago.

In addition to working with us at DTU, Arek has also been a postdoc in Sandy Pentland’s lab at MIT’s MediaLab, he was an integral part of building the world’s first mobile brain scanner, and he’s given a great TEDx talk. And did I mention that we’ve just put out yet another paper together.

Below, you can find the talk details:

• Date: January 10th, 2023
• Time: 13:30-14:30
• Place: DTU Building 321, in the first floor lab space
• Title:  Data Science: Thinking Industry
• Abstract: The practice of Data Science involves employing different methodologies, techniques, and tools, both deconstructive and constructive. In this talk we will discuss some fundamental differences in how Academia and Industry (exemplified by large tech companies) approach teaching and applying Data Science. These differences have important implications for how we teach students and conduct research.

I hope you can make it. Arek will stick around afterwards if you’d like to chat and hang out.

I had an absolutely wonderful time at the Complex Networks 2018 conference last week in Cambridge, UK. I learned a lot and got caught up a bit with all the amazing work that’s going within complex network analysis and see some of the great new young researchers in the field.

At the community detection sessions, I also saw several talks that drew on our work on Link Clustering, expanding and building on those ideas. Now don’t get me wrong: That work is well cited, so I know people have been reading it. But my sense is that most of the citations are of the type “This is also something one could do” or from people applying the algorithm. Those are both great (and a much better fate than what befalls most of my papers), but it is still extra exciting to see people adopting, refining, and developing the ideas – using them for their own work with community detection methods!

Another exciting development was to see how lots of people are starting to apply machine learning (including embeddings, etc) to networks.

Finally, I also got to give my own keynote about our recent paper on the Chaperone Effect in Scientific Publishing. It was a brand new talk (since the paper just came out 2 days prior), but judging from the Twitter reaction, people liked it 🙂

On October 9th, we are lucky to have Pantelis Pipergias Analytis visiting the group. Pantelis recently moved as an assistant professor at the Danish Institute of Advanced Studies (D-IAS) at the  University of Southern Denmark.

Before moving to Denmark, he spent the past two years as a postdoctoral researcher at the Computer and Information Science department at Cornell University. Pantelis got his PhD from the Max Planck Institute for Human Development in Berlin.

Pantelis will give a talk based on his recent Nature Human Behavior paper Social learning strategies for matters of taste

• Date: October 9th
• Time: 13:30
• Place: Technical University of Denmark, Building 321, Room 134

Title: Social learning strategies for matters of taste

Abstract: Most choices people make are about ‘matters of taste’, on which there is no universal, objective truth. Nevertheless, people can learn from the experiences of individuals with similar tastes who have already evaluated the available options—a poten- tial harnessed by recommender systems. We mapped recommender system algorithms to models of human judgement and decision-making about ‘matters of fact’ and recast the latter as social learning strategies for matters of taste. Using computer simulations on a large-scale, empirical dataset, we studied how people could leverage the experiences of others to make better decisions. Our simulations showed that experienced individuals can benefit from relying mostly on the opinions of seemingly similar people; by contrast, inexperienced individuals cannot reliably estimate similarity and are better off picking the main- stream option despite differences in taste. Crucially, the level of experience beyond which people should switch to similarity- heavy strategies varies substantially across individuals and depends on how mainstream (or alternative) an individual’s tastes are and the level of dispersion in taste similarity with the other people in the group.

Our old friend Piotr, current postdoc at Northeastern, and graduate from the group is visiting from his new home beyond the Atlantic. This coming Thursday, Piotr will give a short about his most recent work. Details below.

• Time: Thursday, Sept 6th. 11AM
• Location: Technical University of Denmark.B321, lab-space
• Title: Fairness in ranking
  

Abstract: Ranked lists of persons and items are a core part of the user experience in many online services, such as search, social media feeds, hiring, and dating sites. Studies have shown disparate amount of attention received by high rank results, potentially leading to loss of opportunity and access to resources among the lower ranked items. In this short talk I will give an overview of the work on individual and group fairness in ranked lists and focus on our work in progress: a novel metric for investigating group unfairness in ranked lists. Our approach relies on estimating the amount of attention given to members of a protected group and comparing it to that group’s representation in a defined population. It offers two major developments compared to the state of the art. First, rather than assuming a logarithmic loss in importance as a function of the rank, we allow for attention distributions that are specific to the audited service and the habits of its users. For example, more items are consumed in a single viewing of a social media feed than as a result of a single query in a web search engine. Second, we allow non-binary protected attributes (gender, race, etc.), both to better reflect the way individuals identify, but also to enable measurements on aggregates of multiple search runs, rather than separately for each result list.We investigate the properties of the metric and compare them to the behavior of other established approaches using synthetic ranked lists. Finally, we showcase the metric through a simulated audit of a number of hiring and dating services.

Later this month we will have legendary researcher Bernardo Huberman visiting. And we’re lucky enough to have him giving a talk on one of the most exciting new developments in Network Science: Applying AI to networking problems.

Bernardo has been a central player throughout the rise of network theory (and mentor for field notables, such as Lada Adamic and Jure Leskovec), but that’s just a fraction of what he’s accomplished. If you care about anything related to information sciences, this is a talk you cannot miss.

Bernardo is a Fellow and vice president of the Core Innovation Team at CableLabs. He is also a Consulting Professor in the Department of Applied Physics and the Symbolic System Program at Stanford University. Previously he was Senior Fellow and Senior Vice President at Hewlett Packard Enterprise Company, and Director of the Mechanisms and Design Lab at Hewlett Packard Labs.

• 电脑下载ssr: August 29, 2017.
• 电脑版ssr如何使用: 14:00
• Location: Technical University of Denmark, Building 321, 1st floor: Room 134

Title: Artificial Intelligence and the Network

Abstract: Artificial Intelligence is the attempt to make computers emulate human cognition and thought processes. It has existed for a long time and has sprouted a number of subfields, from semantic networks and common sense reasoning to robotics, logic programming and machine learning. In spite of the glacial rate of progress in AI,  one subfield, machine learning, has recently taken off like wildfire. What powers this incredible growth is the availability of fast processors that have made possible computations than seemed hard to achieve a few years ago. As a result, we now have powerful systems that can easily recognize myriad images and spoken languages. This talk will describe some of the great successes of machine learning, their limitations, and their application to networking problems which pervade modern communications. I will also present a form of artificial intelligence that is distributed in nature and that mimics the ability of groups of people and social insects to solve extremely hard problems.

We’re lucky to have Max Schich visiting DTU tomorrow. Max is an associate professor for arts and technology at The University of Texas at Dallas and a founding member of the Edith O’Donnell Institute of Art History. His work converges hermeneutics, information visualization, computer science, and physics to understand art, history, and culture. Schich is the first author of “A Network Framework of Cultural History” (Science magazine, 2014) and a lead co-author of the animation “Charting Culture” (Nature video, 2014). He is an editorial advisor at Leonardo Journal, an editorial board member at Palgrave Communications (NPG), and the Journal for Digital Art History. He publishes in multiple disciplines and speaks to translate his ideas to diverse audiences across academia and industry. His work received global press coverage in 28 languages.

Details

• Time: April 17th, 14:00
• 电脑ssr软件: DTU, Building 321, first floor lab space
• Title: Towards a Morphology of Durations

电脑版ssr如何使用 History has no periodic table of elements and no theory of temporal structure, as George Kubler pointed out in 1962, yet, as he also points out, things occupy time in a bounded number of ways. The obvious question still is: Can we capture the shape of time? – Tackling this challenge, this talk looks at historical time systematically, dealing with more or less exponential growth, the archaeological paradox, global and meso-level patterns, cycles, periodicity, condensation, and a bouquet of oddities.

SSR Windows客户端 共享给局域网手机教程-SSR中文网:2021-7-18 · SSR Windows客户端在电脑上连接成功后，我伊可伍通过简单的设置，让电脑做为伋理，局域网中的手机等设备，连接这台电脑上网，从而实现局域网整体科学上网。 小提示：这种共享方法，由于要保持电脑开机状态，所伍仅适用于手机需要临时科学上网的情况，一般不适用于日常使用。

Sometime last year I became an adjunct professor at University of Copenhagen’s Department of Sociology. And just to be clear: I’m still primarily the Technical University of Denmark. The adjunct position is more of a way of signaling that I work closely with social science researchers (e.g. through my associate director position at SODAS).

Anyway, the important thing here is that I’m finally giving my inaugural lecture. The lecture is a fun chance for me to reflect on what’s happened up to now. My goal is to make the lecture be fun, entertaining, and personal (in a way that I hope will shed light on the mechanics of the scientific process). I hope you’ll come and see it. 

Here are the details:

• Date & Time: Friday April 20th
• Location: Room 35.01.44, University of Copenhagen. [It’s not super easy to find building 35, so here’s special directions: The easiest way is to go to Gammeltoftgade 15, Copenhagen K and enter the brand-new building (Building 35), then head to the basement & follow the signs to 35.01.44]
• Official link.