Filter Results:
(422)
Show Results For
- All HBS Web
(422)
- People (1)
- News (88)
- Research (285)
- Events (4)
- Multimedia (4)
- Faculty Publications (162)
Show Results For
- All HBS Web
(422)
- People (1)
- News (88)
- Research (285)
- Events (4)
- Multimedia (4)
- Faculty Publications (162)
Page 1 of 422
Results →
- 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
McFowland III, Edward, Skyler Speakman, and Daniel B. Neill. "Fast Generalized Subset Scan for Anomalous Pattern Detection." Art. 12. Journal of Machine Learning Research 14 (2013): 1533–1561.
- 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
Doss, Charles R., and Edward McFowland III. "Nonparametric Subset Scanning for Detection of Heteroscedasticity." Journal of Computational and Graphical Statistics 31, no. 3 (2022): 813–823.
- Article
Pattern Detection in the Activation Space for Identifying Synthesized Content
By: Celia Cintas, Skyler Speakman, Girmaw Abebe Tadesse, Victor Akinwande, Edward McFowland III and Komminist Weldemariam
Generative Adversarial Networks (GANs) have recently achieved unprecedented success in photo-realistic image synthesis from low-dimensional random noise. The ability to synthesize high-quality content at a large scale brings potential risks as the generated samples may... View Details
Cintas, Celia, Skyler Speakman, Girmaw Abebe Tadesse, Victor Akinwande, Edward McFowland III, and Komminist Weldemariam. "Pattern Detection in the Activation Space for Identifying Synthesized Content." Pattern Recognition Letters 153 (January 2022): 207–213.
- 2011
- Article
Scalable Detection of Anomalous Patterns With Connectivity Constraints
By: Skyler Speakman, Edward McFowland III and Daniel B. Neill
We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and... View Details
- November 2021
- Article
Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data
By: William Herlands, Edward McFowland III, Andrew Gordon Wilson and Daniel B. Neill
Identifying anomalous patterns in real-world data is essential for understanding where, when, and how systems deviate from their expected dynamics. Yet methods that separately consider the anomalousness of each individual data point have low detection power for subtle,... View Details
Herlands, William, Edward McFowland III, Andrew Gordon Wilson, and Daniel B. Neill. "Gaussian Process Subset Scanning for Anomalous Pattern Detection in Non-iid Data." Proceedings of Machine Learning Research (PMLR) 84 (2018): 425–434. (Also presented at the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), 2018.)
- 2015
- Article
Scalable Detection of Anomalous Patterns With Connectivity Constraints
By: Skyler Speakman, Edward McFowland III and Daniel B. Neill
We present GraphScan, a novel method for detecting arbitrarily shaped connected clusters in graph or network data. Given a graph structure, data observed at each node, and a score function defining the anomalousness of a set of nodes, GraphScan can efficiently and... View Details
Speakman, Skyler, Edward McFowland III, and Daniel B. Neill. "Scalable Detection of Anomalous Patterns With Connectivity Constraints." Journal of Computational and Graphical Statistics 24, no. 4 (2015): 1014–1033.
- 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
Elsner, Daniel, Pouya Aleatrati Khosroshahi, Alan MacCormack, and Robert Lagerström. "Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise Applications." Proceedings of the Hawaii International Conference on System Sciences 52nd (2019): 5827–5836.
- September 1998
- Article
Detecting Lower Earnings Quality
By: David F. Hawkins
Hawkins, David F. "Detecting Lower Earnings Quality." Accounting Bulletin, no. 69 (September 1998).
- Article
Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error
By: Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan and Edward McFowland III
Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving... View Details
Keywords: Autoencoder Networks; Pattern Detection; Subset Scanning; Computer Vision; Statistical Methods And Machine Learning; Machine Learning; Deep Learning; Data Mining; Big Data; Large-scale Systems; Mathematical Methods; Analytics and Data Science
Cintas, Celia, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan, and Edward McFowland III. "Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error." Proceedings of the International Joint Conference on Artificial Intelligence 29th (2020).
- 2018
- Simulation
Financial Analysis Simulation: Data Detective
By: Suraj Srinivasan and V.G. Narayanan
In this simulation, students learn to identify typical industry characteristics revealed in financial data. Equipped with an interactive and flexible set of tools, students analyze disguised financials and—using their knowledge of operational practices and reasoning... View Details
Keywords: Financial Analysis; Financial Accounting; Financial Ratios; Accounting; Financial Statements; Analysis
Srinivasan, Suraj, and V.G. Narayanan. "Financial Analysis Simulation: Data Detective." Core Curriculum Readings Series. Simulation and Teaching Note. Boston: Harvard Business Publishing 8742, 2018. Electronic.
- 2014
- Working Paper
Firm Competitiveness and Detection of Bribery
By: George Serafeim
Using survey data from firms around the world I analyze how detection of bribery has impacted a firm's competitiveness over the past year. Managers report that the most significant impact was on employee morale, followed by business relations, and then reputation and... View Details
Keywords: Competitiveness; Corruption; Bribery; Employee Engagement; Reputation; Regulation; Competition; Crime and Corruption; Ethics; Performance
Serafeim, George. "Firm Competitiveness and Detection of Bribery." Harvard Business School Working Paper, No. 14-012, July 2013. (Revised February 2014, April 2014.)
- April 2024
- Article
Detecting Routines: Applications to Ridesharing CRM
By: Ryan Dew, Eva Ascarza, Oded Netzer and Nachum Sicherman
Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines—which we define as repeated behaviors with recurring, temporal... View Details
Keywords: Ride-sharing; Routine; Machine Learning; Customer Relationship Management; Consumer Behavior; Segmentation
Dew, Ryan, Eva Ascarza, Oded Netzer, and Nachum Sicherman. "Detecting Routines: Applications to Ridesharing CRM." Journal of Marketing Research (JMR) 61, no. 2 (April 2024): 368–392.
- 14 Aug 2013
- Working Paper Summaries
Firm Competitiveness and Detection of Bribery
Keywords: by George Serafeim
- February 2024
- Article
Conveying and Detecting Listening in Live Conversation
By: Hanne Collins, Julia A. Minson, Ariella S. Kristal and Alison Wood Brooks
Across all domains of human social life, positive perceptions of conversational listening (i.e., feeling heard) predict well-being, professional success, and interpersonal flourishing. But a fundamental question remains: Are perceptions of listening accurate? Prior... View Details
Collins, Hanne, Julia A. Minson, Ariella S. Kristal, and Alison Wood Brooks. "Conveying and Detecting Listening in Live Conversation." Journal of Experimental Psychology: General 153, no. 2 (February 2024): 473–494.
- December 2023
- Case
The Valuation Multiple Detective
By: Jonas Heese, Paul M. Healy and Pietro Bonetti
Heese, Jonas, Paul M. Healy, and Pietro Bonetti. "The Valuation Multiple Detective." Harvard Business School Case 124-049, December 2023.
- March 2002
- Article
2001 10-K's: Detecting Enronitis Symptoms
By: David F. Hawkins
Keywords: Reports
Hawkins, David F. "2001 10-K's: Detecting Enronitis Symptoms." Accounting Bulletin, no. 105 (March 2002).
- July 1992
- Background Note
Swiss Fire Detection Equipment Industry
Enright, Michael J. "Swiss Fire Detection Equipment Industry." Harvard Business School Background Note 793-030, July 1992.
Detecting Routines: Applications to Ridesharing CRM
Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines--which we define as repeated behaviors with recurring, temporal... View Details
- February 2022 (Revised February 2024)
- Case
Sekisui House and the In-Home Early Detection Platform
By: John D. Macomber and Akiko Kanno
To address an aging population and sales declines, a major Japanese homebuilder considers pivoting to provide and support an in-home health detection platform, in competition with tech companies. This case considers the point of view of major builders regarding how... View Details
Keywords: Voice Assistants; Architecture; Smart Home; Aging Society; Digitalization; Real Estate; Home Automation; Sensors; Strategy; Digital Platforms; Health Care and Treatment; Housing; Age; Real Estate Industry; Construction Industry; Health Industry; Japan
Macomber, John D., and Akiko Kanno. "Sekisui House and the In-Home Early Detection Platform." Harvard Business School Case 222-070, February 2022. (Revised February 2024.)