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  • Article

Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise Applications

By: Daniel Elsner, Pouya Aleatrati Khosroshahi, Alan MacCormack and Robert Lagerström
Existing application performance management (APM) solutions lack robust anomaly detection capabilities and root cause analysis techniques that do not require manual efforts and domain knowledge. In this paper, we develop a density-based unsupervised machine learning... View Details
Keywords: Big Data; Data Science And Analytics Management; Governance And Compliance; Organizational Systems And Technology; Anomaly Detection; Application Performance Management; Machine Learning; Enterprise Architecture; Analytics and Data Science
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  • Article

Fast Generalized Subset Scan for Anomalous Pattern Detection

By: Edward McFowland III, Skyler Speakman and Daniel B. Neill
We propose Fast Generalized Subset Scan (FGSS), a new method for detecting anomalous patterns in general categorical data sets. We frame the pattern detection problem as a search over subsets of data records and attributes, maximizing a nonparametric scan statistic... View Details
Keywords: Pattern Detection; Anomaly Detection; Knowledge Discovery; Bayesian Networks; Scan Statistics; Analytics and Data Science
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  • 2022
  • Article

Nonparametric Subset Scanning for Detection of Heteroscedasticity

By: Charles R. Doss and Edward McFowland III
We propose Heteroscedastic Subset Scan (HSS), a novel method for identifying covariates that are responsible for violations of the homoscedasticity assumption in regression settings. Viewing the problem as one of anomalous pattern detection, we use subset scanning... View Details
Keywords: Scan Statistics; Anomaly Detection; Regression; Model Diagnostics
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  • 2018
  • Working Paper

Detecting Anomalies: The Relevance and Power of Standard Asset Pricing Tests

By: Malcolm Baker, Patrick Luo and Ryan Taliaferro
The two standard approaches for identifying capital market anomalies are cross-sectional coefficient tests, in the spirit of Fama and MacBeth (1973), and time-series intercept tests, in the spirit of Jensen (1968). A new signal can pass the first test, which we label a... View Details
Keywords: Investment Management; Anomalies; Portfolio Construction; Transaction Costs; Investment; Management; Asset Pricing; Market Transactions; Cost
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  • November–December 2020
  • Article

The Risks You Can't Foresee: What to Do When There's No Playbook

By: Robert S. Kaplan, Herman B. Leonard and Anette Mikes
No matter how good their risk management systems are, companies can’t plan for everything. Some risks are outside people’s realm of experience or so remote no one could have imagined them. Some result from a perfect storm of coinciding breakdowns, and some materialize... View Details
Keywords: Novel Risks; Risk Management; Crisis Management
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  • January 2021
  • Case

Anodot: Autonomous Business Monitoring

By: Antonio Moreno and Danielle Golan
Autonomous business monitoring platform Anodot leveraged machine learning to provide real-time alerts regarding business anomalies. Anodot’s solution was used in various industries in order to primarily monitor business health, such as revenue and payments, product... View Details
Keywords: Digital Platforms; Internet and the Web; Knowledge Sharing; Information Management; Sales; Value Creation; Product Positioning; Israel
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  • 24 Apr 2014
  • News

Multiple generations of computing

computer-memory system modeled after the human neocortex. The first product, Grok, detects anomalies in IT systems by automatically finding complex patterns in streams of data. In reflecting on her career... View Details
  • 26 Feb 2019
  • First Look

New Research and Ideas, February 26, 2019

https://www.hbs.edu/faculty/Pages/item.aspx?num=55668 2019 Proceedings of the Hawaii International Conference on System Sciences Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise... View Details
Keywords: Dina Gerdeman
  • 19 Dec 2006
  • First Look

First Look: December 19, 2006

  Working PapersAnomalies in Estimates of Cross-Price Elasticities for Marketing Mix Models: Theory and Empirical Test Authors:Andre Bonfrer, Ernest R. Berndt, and Alvin Silk Abstract We investigate the theoretical possibility and empirical regularity of two... View Details
Keywords: Sean Silverthorne
  • 08 Dec 2003
  • Research & Ideas

Is That Really Your Best Offer?

begin to detect a pattern. Serious poker players strive to disguise their tells with sunglasses or use eye drops so that their pupils don't dilate as they take in a spectacular hand, but it's not easy to control the emotions that bubble... View Details
Keywords: by Michael Wheeler
  • 31 Jan 2012
  • First Look

First Look: Jan. 31

prior work in fairness, the studies show that this effect is driven by violations of norms and the perceived similarity between the inferior, degraded version of a product and the full-featured model offered by the brand. Fundamental Data View Details
Keywords: Sean Silverthorne & Carmen Nobel
  • 06 Dec 2018
  • News

Source Code

scenarios, expected behaviors—and that this is a critical element of human intelligence. Translated into code, these biological functions became a unique learning algorithm, which Numenta’s business partner Grok makes available as an View Details
Keywords: Dan Morrell; illustrations by Daniel Hertzberg