Data Skeptic

  • Author: Vários
  • Narrator: Vários
  • Publisher: Podcast
  • Duration: 302:56:35
  • More information

Informações:

Synopsis

Data Skeptic is a data science podcast exploring machine learning, statistics, artificial intelligence, and other data topics through short tutorials and interviews with domain experts.

Episodes

  • Byzantine Fault Tolerant Consensus

    22/12/2020 Duration: 35min

    Byzantine fault tolerance (BFT) is a desirable property in a distributed computing environment. BFT means the system can survive the loss of nodes and nodes becoming unreliable. There are many different protocols for achieving BFT, though not all options can scale to large network sizes. Ted Yin joins us to explain BFT, survey the wide variety of protocols, and share details about HotStuff.

  • Alpha Fold

    11/12/2020 Duration: 23min

    Kyle shared some initial reactions to the announcement about Alpha Fold 2's celebrated performance in the CASP14 prediction.  By many accounts, this exciting result means protein folding is now a solved problem. Thanks to our sponsors! Brilliant is a great last-minute gift idea! Give access to 60 + interactive courses including Quantum Computing and Group Theory. There's something for everyone at Brilliant. They have award-winning courses, taught by teachers, researchers and professionals from MIT, Caltech, Duke, Microsoft, Google and many more. Check them out at  brilliant.org/dataskeptic to take advantage of 20% off a Premium memebership. Betterhelp is an online professional counseling platform. Start communicating with a licensed professional in under 24 hours! It's safe, private and convenient. From online messages to phone and video calls, there is something for everyone. Get 10% off your first month at betterhelp.com/dataskeptic

  • Arrow's Impossibility Theorem

    04/12/2020 Duration: 26min

    Above all, everyone wants voting to be fair. What does fair mean and how can we measure it? Kenneth Arrow posited a simple set of conditions that one would certainly desire in a voting system. For example, unanimity - if everyone picks candidate A, then A should win! Yet surprisingly, under a few basic assumptions, this theorem demonstrates that no voting system exists which can satisfy all the criteria. This episode is a discussion about the structure of the proof and some of its implications. Works Mentioned A Difficulty in the Concept of Social Welfare by Kenneth J. Arrow   Three Brief Proofs of Arrows Impossibility Theorem by John Geanakoplos   Thank you to our sponsors!   Better Help is much more affordable than traditional offline counseling, and financial aid is available! Get started in less than 24 hours. Data Skeptic listeners get 10% off your first month when you visit: betterhelp.com/dataskeptic   Let Springboard School of Data jumpstart your data career! With 100% online and remote schooling, su

  • Face Mask Sentiment Analysis

    27/11/2020 Duration: 41min

    As the COVID-19 pandemic continues, the public (or at least those with Twitter accounts) are sharing their personal opinions about mask-wearing via Twitter. What does this data tell us about public opinion? How does it vary by demographic? What, if anything, can make people change their minds? Today we speak to, Neil Yeung and Jonathan Lai, Undergraduate students in the Department of Computer Science at the University of Rochester, and Professor of Computer Science, Jiebo-Luoto to discuss their recent paper. Face Off: Polarized Public Opinions on Personal Face Mask Usage during the COVID-19 Pandemic. Works Mentioned https://arxiv.org/abs/2011.00336 Emails: Neil Yeung nyeung@u.rochester.edu Jonathan Lia jlai11@u.rochester.edu Jiebo Luo jluo@cs.rochester.edu Thanks to our sponsors! Springboard School of Data offers a comprehensive career program encompassing data science, analytics, engineering, and Machine Learning. All courses are online and tailored to fit the lifestyle of working professionals. Up to 20 Da

  • Counting Briberies in Elections

    20/11/2020 Duration: 37min

    Niclas Boehmer, second year PhD student at Berlin Institute of Technology, comes on today to discuss the computational complexity of bribery in elections through the paper “On the Robustness of Winners: Counting Briberies in Elections.” Links Mentioned: https://www.akt.tu-berlin.de/menue/team/boehmer_niclas/ Works Mentioned: “On the Robustness of Winners: Counting Briberies in Elections.” by Niclas Boehmer, Robert Bredereck, Piotr Faliszewski. Rolf Niedermier Thanks to our sponsors: Springboard School of Data: Springboard is a comprehensive end-to-end online data career program. Create a portfolio of projects to spring your career into action. Learn more about how you can be one of twenty $500 scholarship recipients at springboard.com/dataskeptic. This opportunity is exclusive to Data Skeptic listeners. (Enroll with code: DATASK) Nord VPN: Protect your home internet connection with unlimited bandwidth. Data Skeptic Listeners-- take advantage of their Black Friday offer: purchase a 2-year plan, get 4 additiona

  • Sybil Attacks on Federated Learning

    13/11/2020 Duration: 31min

    Clement Fung, a Societal Computing PhD student at Carnegie Mellon University, discusses his research in security of machine learning systems and a defense against targeted sybil-based poisoning called FoolsGold. Works Mentioned: The Limitations of Federated Learning in Sybil Settings Twitter: @clemfung Website: https://clementfung.github.io/ Thanks to our sponsors: Brilliant - Online learning platform. Check out Geometry Fundamentals! Visit Brilliant.org/dataskeptic for 20% off Brilliant Premium! BetterHelp - Convenient, professional, and affordable online counseling. Take 10% off your first month at betterhelp.com/dataskeptic

  • Differential Privacy at the US Census

    06/11/2020 Duration: 29min

    Simson Garfinkel, Senior Computer Scientist for Confidentiality and Data Access at the US Census Bureau, discusses his work modernizing the Census Bureau disclosure avoidance system from private to public disclosure avoidance techniques using differential privacy. Some of the discussion revolves around the topics in the paper Randomness Concerns When Deploying Differential Privacy.   WORKS MENTIONED: “Calibrating Noise to Sensitivity in Private Data Analysis” by Cynthia Dwork, Frank McSherry, Kobbi Nissim, Adam Smith "Issues Encountered Deploying Differential Privacy" by Simson L Garfinkel, John M Abowd, and Sarah Powazek "Randomness Concerns When Deploying Differential Privacy" by Simson L. Garfinkel and Philip Leclerc  Check out: https://simson.net/page/Differential_privacy Thank you to our sponsor, BetterHelp. Professional and confidential in-app counseling for everyone. Save 10% on your first month of services with www.betterhelp.com/dataskeptic

  • Distributed Consensus

    30/10/2020 Duration: 27min

    Computer Science research fellow of Cambridge University, Heidi Howard discusses Paxos, Raft, and distributed consensus in distributed systems alongside with her work “Paxos vs. Raft: Have we reached consensus on distributed consensus?” She goes into detail about the leaders in Paxos and Raft and how The Raft Consensus Algorithm actually inspired her to pursue her PhD. Paxos vs Raft paper: https://arxiv.org/abs/2004.05074 Leslie Lamport paper “part-time Parliament” https://lamport.azurewebsites.net/pubs/lamport-paxos.pdf Leslie Lamport paper "Paxos Made Simple" https://lamport.azurewebsites.net/pubs/paxos-simple.pdf Twitter : @heidiann360 Thank you to our sponsor Monday.com! Their apps challenge is still accepting submissions! find more information at monday.com/dataskeptic

  • ACID Compliance

    23/10/2020 Duration: 23min

    Linhda joins Kyle today to talk through A.C.I.D. Compliance (atomicity, consistency, isolation, and durability). The presence of these four components can ensure that a database’s transaction is completed in a timely manner. Kyle uses examples such as google sheets, bank transactions, and even the game rummy cube.   Thanks to this week's sponsors: Monday.com - Their Apps Challenge is underway and available at monday.com/dataskeptic Brilliant - Check out their Quantum Computing Course, I highly recommend it! Other interesting topics I’ve seen are Neural Networks and Logic. Check them out at Brilliant.org/dataskeptic

  • National Popular Vote Interstate Compact

    16/10/2020 Duration: 30min

    Patrick Rosenstiel joins us to discuss the The National Popular Vote.

  • Defending the p-value

    12/10/2020 Duration: 30min

    Yudi Pawitan joins us to discuss his paper Defending the P-value.

  • Retraction Watch

    05/10/2020 Duration: 32min

    Ivan Oransky joins us to discuss his work documenting the scientific peer-review process at retractionwatch.com.  

  • Crowdsourced Expertise

    21/09/2020 Duration: 27min

    Derek Lim joins us to discuss the paper Expertise and Dynamics within Crowdsourced Musical Knowledge Curation: A Case Study of the Genius Platform.  

  • The Spread of Misinformation Online

    14/09/2020 Duration: 35min

    Neil Johnson joins us to discuss the paper The online competition between pro- and anti-vaccination views.

  • Consensus Voting

    07/09/2020 Duration: 22min

    Mashbat Suzuki joins us to discuss the paper How Many Freemasons Are There? The Consensus Voting Mechanism in Metric Spaces. Check out Mashbat’s and many other great talks at the 13th Symposium on Algorithmic Game Theory (SAGT 2020)

  • Voting Mechanisms

    31/08/2020 Duration: 27min

    Steven Heilman joins us to discuss his paper Designing Stable Elections. For a general interest article, see: https://theconversation.com/the-electoral-college-is-surprisingly-vulnerable-to-popular-vote-changes-141104 Steven Heilman receives funding from the National Science Foundation. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.

  • False Consensus

    24/08/2020 Duration: 33min

    Sami Yousif joins us to discuss the paper The Illusion of Consensus: A Failure to Distinguish Between True and False Consensus. This work empirically explores how individuals evaluate consensus under different experimental conditions reviewing online news articles. More from Sami at samiyousif.org Link to survey mentioned by Daniel Kerrigan: https://forms.gle/TCdGem3WTUYEP31B8

  • Fraud Detection in Real Time

    18/08/2020 Duration: 38min

    In this solo episode, Kyle overviews the field of fraud detection with eCommerce as a use case.  He discusses some of the techniques and system architectures used by companies to fight fraud with a focus on why these things need to be approached from a real-time perspective.

  • Listener Survey Review

    11/08/2020 Duration: 23min

    In this episode, Kyle and Linhda review the results of our recent survey. Hear all about the demographic details and how we interpret these results.

  • Human Computer Interaction and Online Privacy

    27/07/2020 Duration: 32min

    Moses Namara from the HATLab joins us to discuss his research into the interaction between privacy and human-computer interaction.

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