Data Skeptic

  • Author: Vários
  • Narrator: Vários
  • Publisher: Podcast
  • Duration: 301:09:09
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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

  • Flesch Kincaid Readability Tests

    19/04/2021 Duration: 20min

    Given a document in English, how can you estimate the ease with which someone will find they can read it?  Does it require a college-level of reading comprehension or is it something a much younger student could read and understand? While these questions are useful to ask, they don't admit a simple answer.  One option is to use one of the (essentially identical) two Flesch Kincaid Readability Tests.  These are simple calculations which provide you with a rough estimate of the reading ease. In this episode, Kyle shares his thoughts on this tool and when it could be appropriate to use as part of your feature engineering pipeline towards a machine learning objective. For empirical validation of these metrics, the plot below compares English language Wikipedia pages with "Simple English" Wikipedia pages.  The analysis Kyle describes in this episode yields the intuitively pleasing histogram below.  It summarizes the distribution of Flesch reading ease scores for 1000 pages examined from both Wikipedias.  

  • Fairness Aware Outlier Detection

    09/04/2021 Duration: 39min

    Today on the show we have Shubhranshu Shekar, a Ph. D Student at Carnegie Mellon University, who joins us to talk about his work, FAIROD: Fairness-aware Outlier Detection.

  • Life May be Rare

    05/04/2021 Duration: 43min

    Today on the show Dr. Anders Sandburg, Senior Research Fellow at the Future of Humanity Institute at Oxford University, comes on to share his work “The Timing of Evolutionary Transitions Suggest Intelligent Life is Rare.” Works Mentioned: Paper: “The Timing of Evolutionary Transitions Suggest Intelligent Life is Rare.”by Andrew E Snyder-Beattie, Anders Sandberg, K Eric Drexler, Michael B Bonsall  Twitter: @anderssandburg

  • Social Networks

    29/03/2021 Duration: 49min

    Mayank Kejriwal, Research Professor at the University of Southern California and Researcher at the Information Sciences Institute, joins us today to discuss his work and his new book Knowledge, Graphs, Fundamentals, Techniques and Applications by Mayank Kejriwal, Craig A. Knoblock, and Pedro Szekley. Works Mentioned “Knowledge, Graphs, Fundamentals, Techniques and Applications”by Mayank Kejriwal, Craig A. Knoblock, and Pedro Szekley

  • The QAnon Conspiracy

    22/03/2021 Duration: 43min

    QAnon is a conspiracy theory born in the underbelly of the internet.  While easy to disprove, these cryptic ideas captured the minds of many people and (in part) paved the way to the 2021 storming of the US Capital. This is a contemporary conspiracy which came into existence and grew in a very digital way.  This makes it possible for researchers to study this phenomenon in a way not accessible in previous conspiracy theories of similar popularity. This episode is not so much a debunking of this debunked theory, but rather an exploration of the metadata and origins of this conspiracy. This episode is also the first in our 2021 Pilot Season in which we are going to test out a few formats for Data Skeptic to see what our next season should be.  This is the first installment.  In a few weeks, we're going to ask everyone to vote for their favorite theme for our next season.  

  • Benchmarking Vision on Edge vs Cloud

    15/03/2021 Duration: 47min

    Karthick Shankar, Masters Student at Carnegie Mellon University, and Somali Chaterji, Assistant Professor at Purdue University, join us today to discuss the paper "JANUS: Benchmarking Commercial and Open-Source Cloud and Edge Platforms for Object and Anomaly Detection Workloads" Works Mentioned: https://ieeexplore.ieee.org/abstract/document/9284314 “JANUS: Benchmarking Commercial and Open-Source Cloud and Edge Platforms for Object and Anomaly Detection Workloads.” by: Karthick Shankar, Pengcheng Wang, Ran Xu, Ashraf Mahgoub, Somali ChaterjiSocial Media Karthick Shankar https://twitter.com/karthick_sh Somali Chaterji https://twitter.com/somalichaterji?lang=en https://schaterji.io/

  • Goodhart's Law in Reinforcement Learning

    05/03/2021 Duration: 37min

    Hal Ashton, a PhD student from the University College of London, joins us today to discuss a recent work Causal Campbell-Goodhart’s law and Reinforcement Learning. "Only buy honey from a local producer." - Hal Ashton   Works Mentioned: “Causal Campbell-Goodhart’s law and Reinforcement Learning”by Hal AshtonBook  “The Book of Why”by Judea PearlPaper Thanks to our sponsor!  When your business is ready to make that next hire, find the right person with LinkedIn Jobs. Just visit LinkedIn.com/DATASKEPTIC to post a job for free! Terms and conditions apply

  • Video Anomaly Detection

    01/03/2021 Duration: 24min

    Yuqi Ouyang, in his second year of PhD study at the University of Warwick in England, joins us today to discuss his work “Video Anomaly Detection by Estimating Likelihood of Representations.”Works Mentioned: Video Anomaly Detection by Estimating Likelihood of Representations https://arxiv.org/abs/2012.01468 by: Yuqi Ouyang, Victor Sanchez

  • Fault Tolerant Distributed Gradient Descent

    22/02/2021 Duration: 36min

    Nirupam Gupta, a Computer Science Post Doctoral Researcher at EDFL University in Switzerland, joins us today to discuss his work “Byzantine Fault-Tolerance in Peer-to-Peer Distributed Gradient-Descent.”   Works Mentioned:  https://arxiv.org/abs/2101.12316 Byzantine Fault-Tolerance in Peer-to-Peer Distributed Gradient-Descent by Nirupam Gupta and Nitin H. Vaidya   Conference Details: https://georgetown.zoom.us/meeting/register/tJ0sc-2grDwjEtfnLI0zPnN-GwkDvJdaOxXF

  • Decentralized Information Gathering

    15/02/2021 Duration: 32min

    Mikko Lauri, Post Doctoral researcher at the University of Hamburg, Germany, comes on the show today to discuss the work Information Gathering in Decentralized POMDPs by Policy Graph Improvements. Follow Mikko: @mikko_lauri Github https://laurimi.github.io/

  • Leaderless Consensus

    05/02/2021 Duration: 27min

    Balaji Arun, a PhD Student in the Systems of Software Research Group at Virginia Tech, joins us today to discuss his research of distributed systems through the paper “Taming the Contention in Consensus-based Distributed Systems.”  Works Mentioned “Taming the Contention in Consensus-based Distributed Systems”  by Balaji Arun, Sebastiano Peluso, Roberto Palmieri, Giuliano Losa, and Binoy Ravindranhttps://www.ssrg.ece.vt.edu/papers/tdsc20-author-version.pdf “Fast Paxos” by Leslie Lamport  https://link.springer.com/article/10.1007/s00446-006-0005-x

  • Automatic Summarization

    29/01/2021 Duration: 27min

    Maartje ter Hoeve, PhD Student at the University of Amsterdam, joins us today to discuss her research in automated summarization through the paper “What Makes a Good Summary? Reconsidering the Focus of Automatic Summarization.”  Works Mentioned  “What Makes a Good Summary? Reconsidering the Focus of Automatic Summarization.” by Maartje der Hoeve, Juilia Kiseleva, and Maarten de Rijke Contact Email: m.a.terhoeve@uva.nl Twitter: https://twitter.com/maartjeterhoeve Website: https://maartjeth.github.io/#get-in-touch

  • Gerrymandering

    22/01/2021 Duration: 34min

    Brian Brubach, Assistant Professor in the Computer Science Department at Wellesley College, joins us today to discuss his work “Meddling Metrics: the Effects of Measuring and Constraining Partisan Gerrymandering on Voter Incentives". WORKS MENTIONED: Meddling Metrics: the Effects of Measuring and Constraining Partisan Gerrymandering on Voter Incentives by Brian Brubach, Aravind Srinivasan, and Shawn Zhao

  • Even Cooperative Chess is Hard

    15/01/2021 Duration: 23min

    Aside from victory questions like “can black force a checkmate on white in 5 moves?” many novel questions can be asked about a game of chess. Some questions are trivial (e.g. “How many pieces does white have?") while more computationally challenging questions can contribute interesting results in computational complexity theory. In this episode, Josh Brunner, Master's student in Theoretical Computer Science at MIT, joins us to discuss his recent paper Complexity of Retrograde and Helpmate Chess Problems: Even Cooperative Chess is Hard. Works Mentioned Complexity of Retrograde and Helpmate Chess Problems: Even Cooperative Chess is Hard by Josh Brunner, Erik D. Demaine, Dylan Hendrickson, and Juilian Wellman 1x1 Rush Hour With Fixed Blocks is PSPACE Complete by Josh Brunner, Lily Chung, Erik D. Demaine, Dylan Hendrickson, Adam Hesterberg, Adam Suhl, Avi Zeff

  • Consecutive Votes in Paxos

    11/01/2021 Duration: 30min

    Eil Goldweber, a graduate student at the University of Michigan, comes on today to share his work in applying formal verification to systems and a modification to the Paxos protocol discussed in the paper Significance on Consecutive Ballots in Paxos. Works Mentioned : Previous Episode on Paxos  https://dataskeptic.com/blog/episodes/2020/distributed-consensus Paper: On the Significance on Consecutive Ballots in Paxos by: Eli Goldweber, Nuda Zhang, and Manos Kapritsos Thanks to our sponsor: Nord VPN : 68% off a 2-year plan and one month free! With NordVPN, all the data you send and receive online travels through an encrypted tunnel. This way, no one can get their hands on your private information. Nord VPN is quick and easy to use to protect the privacy and security of your data. Check them out at nordvpn.com/dataskeptic

  • Visual Illusions Deceiving Neural Networks

    01/01/2021 Duration: 33min

    Today on the show we have Adrian Martin, a Post-doctoral researcher from the University of Pompeu Fabra in Barcelona, Spain. He comes on the show today to discuss his research from the paper “Convolutional Neural Networks can be Deceived by Visual Illusions.” Works Mentioned in Paper: “Convolutional Neural Networks can be Decieved by Visual Illusions.” by Alexander Gomez-Villa, Adrian Martin, Javier Vazquez-Corral, and Marcelo Bertalmio Examples: Snake Illusions https://www.illusionsindex.org/i/rotating-snakes Twitter: Alex: @alviur Adrian: @adriMartin13 Thanks to our sponsor! Keep your home internet connection safe with Nord VPN! Get 68% off plus a free month at nordvpn.com/dataskeptic  (30-day money-back guarantee!)

  • Earthquake Detection with Crowd-sourced Data

    25/12/2020 Duration: 29min

    Have you ever wanted to hear what an earthquake sounds like? Today on the show we have Omkar Ranadive, Computer Science Masters student at NorthWestern University, who collaborates with Suzan van der Lee, an Earth and Planetary Sciences professor at Northwestern University, on the crowd-sourcing project Earthquake Detective.  Email Links: Suzan: suzan@earth.northwestern.edu  Omkar: omkar.ranadive@u.northwestern.edu Works Mentioned:  Paper: Applying Machine Learning to Crowd-sourced Data from Earthquake Detective https://arxiv.org/abs/2011.04740 by Omkar Ranadive, Suzan van der Lee, Vivan Tang, and Kevin Chao Github: https://github.com/Omkar-Ranadive/Earthquake-Detective Earthquake Detective: https://www.zooniverse.org/projects/vivitang/earthquake-detective Thanks to our sponsors! Brilliant.org Is an awesome platform with interesting courses, like Quantum Computing! There is something for you and surely something for the whole family! Get 20% off Brilliant Premium at http://brilliant.com/dataskeptic

  • 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

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