Data Skeptic

Mahdi Abolghasemi, Lecturer at Monash University, joins us today to talk about his work "Demand forecasting in supply chain: The impact of demand volatility in the presence of promotion."

 

Direct download: forecasting-in-supply-chain.mp3
Category:general -- posted at: 6:00am PST

The retail holiday “black Friday” occurs the day after Thanksgiving in the United States. It’s dubbed this because many retail companies spend the first 10 months of the year running at a loss (in the red) before finally earning as much as 80% of their revenue in the last two months of the year.

This episode features four interviews with guests bringing unique data-driven perspectives on the topic of analyzing this seeming outlier in a time series dataset.

Direct download: black-friday.mp3
Category:general -- posted at: 7:24am PST

Alex Terenin, Postdoctoral Research Associate at the University of Cambridge, joins us today to talk about his work "Aligning Time Series on Incomparable Spaces."

Direct download: aligning-time-series-on-incomparable-spaces.mp3
Category:general -- posted at: 6:00am PST

Today we are joined again by Ben Fulcher, leader of the Dynamics and Neural Systems Group at the University of Sydney in Australia, to talk about hctsa, a software package for running highly comparative time-series analysis.

Direct download: comparing-time-series-with-hctsa.mp3
Category:general -- posted at: 6:01am PST

Gerrit van den Burg, Postdoctoral Researcher at The Alan Turing Institute, joins us today to discuss his work "An Evaluation of Change Point Detection Algorithms."

Direct download: change-point-detection-algorithms.mp3
Category:general -- posted at: 6:14am PST

Bahman Rostami-Tabar, Senior Lecturer in Management Science at Cardiff University, joins us today to talk about his work "Forecasting and its Beneficiaries."

Direct download: time-series-for-good.mp3
Category:general -- posted at: 6:00am PST

Alex Mallen, Computer Science student at the University of Washington, and Henning Lange, a Postdoctoral Scholar in Applied Math at the University of Washington, join us today to share their work "Deep Probabilistic Koopman: Long-term Time-Series Forecasting Under Periodic Uncertainties."

Direct download: long-term-time-series-forecasting.mp3
Category:general -- posted at: 6:00am PST

Fotios Petropoulos, Professor of Management Science at the University of Bath in The U.K., joins us today to talk about his work "Fast and Frugal Time Series Forecasting."

Direct download: fast-and-frugal-time-series-forecasting.mp3
Category:general -- posted at: 1:13pm PST

Manie Tadayon, a PhD graduate from the ECE department at University of California, Los Angeles, joins us today to talk about his work “Comparative Analysis of the Hidden Markov Model and LSTM: A Simulative Approach.”

Direct download: causal-inference-in-educational-systems.mp3
Category:general -- posted at: 6:00am PST

Sankeerth Rao Karingula, ML Researcher at Palo Alto Networks, joins us today to talk about his work “Boosted Embeddings for Time Series Forecasting.”


Works Mentioned
Boosted Embeddings for Time Series Forecasting
by Sankeerth Rao Karingula, Nandini Ramanan, Rasool Tahmasbi, Mehrnaz Amjadi, Deokwoo Jung, Ricky Si, Charanraj Thimmisetty, Luisa Polania Cabrera, Marjorie Sayer, Claudionor Nunes Coelho Jr

https://www.linkedin.com/in/sankeerthrao/

https://twitter.com/sankeerthrao3 

https://lod2021.icas.cc/ 

Direct download: boosted-embeddings-for-time-series.mp3
Category:general -- posted at: 6:00am PST

David Daly, Performance Engineer at MongoDB, joins us today to discuss "The Use of Change Point Detection to Identify Software Performance Regressions in a Continuous Integration System".

Works Mentioned
The Use of Change Point Detection to Identify Software Performance Regressions in a Continuous Integration System
by David Daly, William Brown, Henrik Ingo, Jim O’Leary, David BradfordSocial Media

David's Website
David's Twitter
Mongodb


Direct download: change-point-detection-in-continuous-integration-systems.mp3
Category:general -- posted at: 6:00am PST

Samya Tajmouati, a PhD student in Data Science at the University of Science of Kenitra, Morocco, joins us today to discuss her work Applying K-Nearest Neighbors to Time Series Forecasting: Two New Approaches.

Direct download: applying-k-nearest-neighbors-to-time-series.mp3
Category:general -- posted at: 6:00am PST

Dr. Feng Li, (@f3ngli) is an Associate Professor of Statistics in the School of Statistics and Mathematics at Central University of Finance and Economics in Beijing, China. He joins us today to discuss his work Distributed ARIMA Models for Ultra-long Time Series.

Direct download: ultra-long-time-series.mp3
Category:general -- posted at: 6:00am PST

Angus Dempster, PhD Student at Monash University in Australia, comes on today to talk about MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification, a fast deterministic transform for time series classification. MINIROCKET reformulates ROCKET, gaining a 75x improvement on larger datasets with essentially the same performance. In this episode, we talk about the insights that realized this speedup as well as use cases.

Direct download: minirocket.mp3
Category:general -- posted at: 6:00am PST

Chongshou Li, Associate Professor at Southwest Jiaotong University in China, joins us today to talk about his work Why are the ARIMA and SARIMA not Sufficient.

Direct download: arima-is-not-sufficient.mp3
Category:general -- posted at: 6:00am PST

Ben Fulcher, Senior Lecturer at the School of Physics at the University of Sydney in Australia, comes on today to talk about his project Comp Engine.

Follow Ben on Twitter: @bendfulcher
For posts about time series analysis : @comptimeseries
comp-engine.org

Direct download: comp-engine.mp3
Category:general -- posted at: 6:00am PST

Nitin Pundir, PhD candidate at University Florida and works at the Florida Institute for Cybersecurity Research, comes on today to talk about his work “RanStop: A Hardware-assisted Runtime Crypto-Ransomware Detection Technique.”

FICS Research Lab - https://fics.institute.ufl.edu/ 

LinkedIn - https://www.linkedin.com/in/nitin-pundir470/

Direct download: detecting-ransomware.mp3
Category:general -- posted at: 6:00am PST

Florian Eckerli, a recent graduate of Zurich University of Applied Sciences, comes on the show today to discuss his work Generative Adversarial Networks in Finance: An Overview.

Direct download: gans-in-finance.mp3
Category:general -- posted at: 6:00am PST

Today on the show we have Daniel Omeiza, a doctoral student in the computer science department of the University of Oxford, who joins us to talk about his work Efficient Machine Learning for Large-Scale Urban Land-Use Forecasting in Sub-Saharan Africa.

Direct download: predicting-urban-land-use.mp3
Category:general -- posted at: 6:00am PST

Today on the show we have Elizabeth Barnes, Associate Professor in the department of Atmospheric Science at Colorado State University, who joins us to talk about her work Identifying Opportunities for Skillful Weather Prediction with Interpretable Neural Networks. Find more from the Barnes Research Group on their site.

Weather is notoriously difficult to predict. Complex systems are demanding of computational power. Further, the chaotic nature of, well, nature, makes accurate forecasting especially difficult the longer into the future one wants to look. Yet all is not lost!

In this interview, we explore the use of machine learning to help identify certain conditions under which the weather system has entered an unusually predictable position in it’s normally chaotic state space.

Direct download: opportunities-for-skillful-weather-prediction.mp3
Category:general -- posted at: 6:00am PST

Today on the show we have Andrea Fronzetti Colladon (@iandreafc), currently working at the University of Perugia and inventor of the Semantic Brand Score, joins us to talk about his work studying human communication and social interaction.

We discuss the paper Look inside. Predicting Stock Prices by Analyzing an Enterprise Intranet Social Network and Using Word Co-Occurrence Networks.

Direct download: predicting-stock-prices.mp3
Category:general -- posted at: 6:00am PST

Today on the show we have Boris Oreshkin @boreshkin, a Senior Research Scientist at Unity Technologies, who joins us today to talk about his work N-BEATS: Neural Basis Expansion Analysis for Interpretable Time Series Forecasting.

Works Mentioned:
N-BEATS: Neural Basis Expansion Analysis for Interpretable Time Series Forecasting
By Boris N. Oreshkin, Dmitri Carpov, Nicolas Chapados, Yoshua Bengio
https://arxiv.org/abs/1905.10437

Social Media
Linkedin

Twitter 

Direct download: nbeats.mp3
Category:general -- posted at: 8:04am PST

Today we are back with another episode discussing AI in the work field. AI has, is, and will continue to facilitate the automation of work done by humans. Sometimes this may be an entire role. Other times it may automate a particular part of their role, scaling their effectiveness.

Carl Stimson, a Freelance Japanese to English translator, comes on the show to talk about his work in translation and his perspective about how AI will change translation in the future. 

Direct download: translation-automation.mp3
Category:general -- posted at: 6:48pm PST

Shane Ross, Professor of Aerospace and Ocean Engineering at Virginia Tech University, comes on today to talk about his work “Beach-level 24-hour forecasts of Florida red tide-induced respiratory irritation.”

Direct download: time-series-at-the-beach.mp3
Category:general -- posted at: 6:00am PST

Lior Shamir, Associate Professor of Computer Science at Kansas University, joins us today to talk about the recent paper Automatic Identification of Outliers in Hubble Space Telescope Galaxy Images.

Follow Lio on Twitter @shamir_lior

Direct download: automatic-identification-of-outlier-galaxy-images.mp3
Category:general -- posted at: 12:11pm PST

Shereen Elsayed and Daniela Thyssens, both are PhD Student at Hildesheim University in Germany, come on today to talk about the work “Do We Really Need Deep Learning Models for Time Series Forecasting?”

Direct download: do-we-need-deep-learning-in-time-series.mp3
Category:general -- posted at: 9:10am PST

Sam Ackerman, Research Data Scientist at IBM Research Labs in Haifa, Israel, joins us today to talk about his work Detection of Data Drift and Outliers Affecting Machine Learning Model Performance Over Time.

Check out Sam's IBM statistics/ML blog at: http://www.research.ibm.com/haifa/dept/vst/ML-QA.shtml
 
Direct download: detecting-drift.mp3
Category:general -- posted at: 5:05pm PST

Julien Herzen, PhD graduate from EPFL in Switzerland, comes on today to talk about his work with Unit 8 and the development of the Python Library: Darts. 

Direct download: darts-library-for-time-series.mp3
Category:general -- posted at: 7:52am PST

Welcome to Timeseries! Today’s episode is an interview with Rob Hyndman, Professor of Statistics at Monash University in Australia, and author of Forecasting: Principles and Practices.

Direct download: forecasting-principles-and-practice.mp3
Category:general -- posted at: 7:57am PST

Today's experimental episode uses sound to describe some basic ideas from time series.

This episode includes lag, seasonality, trend, noise, heteroskedasticity, decomposition, smoothing, feature engineering, and deep learning.

 

Direct download: prequisites-for-time-series.mp3
Category:general -- posted at: 11:36am PST

Today’s show in two parts. First, Linhda joins us to review the episodes from Data Skeptic: Pilot Season and give her feedback on each of the topics.

Second, we introduce our new segment “Orders of Magnitude”. It’s a statistical game show in which participants must identify the true statistic hidden in a list of statistics which are off by at least an order of magnitude. Claudia and Vanessa join as our first contestants.  Below are the sources of our questions.

Heights

Bird Statistics

Amounts of Data

Our statistics come from this post




Direct download: oom.mp3
Category:general -- posted at: 11:55am PST

AI has, is, and will continue to facilitate the automation of work done by humans. Sometimes this may be an entire role. Other times it may automate a particular part of their role, scaling their effectiveness. Unless progress in AI inexplicably halts, the tasks done by humans vs. machines will continue to evolve. Today’s episode is a speculative conversation about what the future may hold.

Co-Host of Squaring the Strange Podcast, Caricature Artist, and an Academic Editor, Celestia Ward joins us today! Kyle and Celestia discuss whether or not her jobs as a caricature artist or as an academic editor are under threat from AI automation.

Mentions

Direct download: theyre-coming-for-our-jobs.mp3
Category:general -- posted at: 9:00am PST

Today on the show Derek Driggs, a PhD Student at the University of Cambridge. He comes on to discuss the work Common Pitfalls and Recommendations for Using Machine Learning to Detect and Prognosticate for COVID-19 Using Chest Radiographs and CT Scans.

Help us vote for the next theme of Data Skeptic!

Vote here: https://dataskeptic.com/vote

Direct download: pandemic-machine-learning-pitfalls.mp3
Category:general -- posted at: 12:00am PST

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.

 

Direct download: flesch-kincaid-readability-tests.mp3
Category:general -- posted at: 12:50am PST

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.

Direct download: fairness-aware-outlier-detection.mp3
Category:general -- posted at: 8:30am PST

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

Direct download: life-may-be-rare.mp3
Category:general -- posted at: 7:24am PST

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

Direct download: social-networks.mp3
Category:general -- posted at: 7:21am PST

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.

 

Direct download: the-qanon-conspiracy.mp3
Category:general -- posted at: 7:39am PST

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/

Direct download: benchmarking-vision-on-edge-vs-cloud.mp3
Category:general -- posted at: 5:00am PST

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
Direct download: goodharts-law-in-reinforcement-learning.mp3
Category:general -- posted at: 5:00am PST

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

Direct download: video-anomaly-detection.mp3
Category:general -- posted at: 6:00am PST

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

Direct download: fault-tolerant-distributed-gradient-descent.mp3
Category:general -- posted at: 6:30am PST

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/

Direct download: decentralized-information-gathering.mp3
Category:general -- posted at: 5:30am PST

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 Ravindran
https://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

Direct download: leaderless-consensus.mp3
Category:general -- posted at: 9:47am PST

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

Direct download: automatic-summarization.mp3
Category:general -- posted at: 8:00am PST

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

Direct download: gerrymandering.mp3
Category:general -- posted at: 8:00am PST

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

Direct download: even-cooperative-chess-is-hard.mp3
Category:general -- posted at: 10:02am PST

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

Direct download: consecutive-votes-in-paxos.mp3
Category:general -- posted at: 6:00am PST

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!)

Direct download: visual-illusions-deceiving-neural-networks.mp3
Category:general -- posted at: 6:00am PST

1