Publications
Publications
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- All HBS Web
(429)
- Faculty Publications (106)
- 2020
- Conference Presentation
A Performance-optimized Limb Detection Model Selectively Predicts Behavioral Responses Based on Movement Similarity
By: X. Zhao, J. De Freitas, L. Tarhan and G. A. Alvarez
- 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
- May 2020
- Article
Scalable Holistic Linear Regression
By: Dimitris Bertsimas and Michael Lingzhi Li
We propose a new scalable algorithm for holistic linear regression building on Bertsimas & King (2016). Specifically, we develop new theory to model significance and multicollinearity as lazy constraints rather than checking the conditions iteratively. The resulting... View Details
- 2019
- Article
The Frequency of Corporate Misconduct: Public Enforcement versus Private Reality
By: Eugene F. Soltes
Perceptions about the frequency of misconduct—among the public, academics and even
regulators—have largely been formed by examining enforcement statistics, which rely on the detection and sanctioning of the misconduct. This study aims to illuminate the real occurrence... View Details
- November 9, 2019
- Article
Effect of Revealing Authors' Conflicts of Interests in Peer Review: Randomized Controlled Trial
By: Leslie K. John, George Loewenstein, Andrew Marder and Michael Callaham
Objective: To assess the impact of disclosing authors’ conflict of interest declarations to peer reviewers at a medical journal.
Design: Randomised controlled trial.
Setting: The study was conducted within the manuscript review process at the... View Details
Design: Randomised controlled trial.
Setting: The study was conducted within the manuscript review process at the... View Details
- Article
Effect of Different Financial Incentive Structures on Promoting Physical Activity Among Adults: A Randomized Clinical Trial
By: Chethan Bachireddy, Andrew Joung, Leslie K. John, Francesca Gino, Bradford Tuckfield, Luca Foschini and Katherine L. Milkman
Importance: Few adults engage in recommended levels of physical activity. Financial incentives can promote physical activity, but little is known about how their structure influences their effectiveness; for example, whether incentives are more effective if they are... View Details
- 2020
- Working Paper
Are ISS Recommendations Informative? Evidence from Assessments of Compensation Practices
By: Ana Albuquerque, Mary Ellen Carter and Susanna Gallani
Using detailed information from the largest proxy advisor in the U.S., Institutional Shareholder Services (ISS), we examine whether proxy advisors’ assessments of firms’ compensation practices are able to identify poor compensation practices as measured by subsequent... View Details
- 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
- September 2018 (Revised December 2019)
- Case
Zebra Medical Vision
By: Shane Greenstein and Sarah Gulick
An Israeli startup founded in 2014, Zebra Medical Vision developed algorithms that produced diagnoses from X-rays, mammograms, and CT-scans. The algorithms used deep learning and digitized radiology scans to create software that could assist doctors in making... View Details
Keywords: Radiology; Machine Learning; X-ray; CT Scan; Medical Technology; Probability; FDA 510(k); Diagnosis; Business Startups; Health Care and Treatment; Information Technology; Applications and Software; Competitive Strategy; Product Development; Commercialization; Decision Choices and Conditions; Health Industry; Medical Devices and Supplies Industry; Technology Industry; Israel
- 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
- 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
- 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
- Article
Why Compliance Programs Fail: And How to Fix Them
By: Hui Chen and Eugene Soltes
Firms spend millions of dollars annually on whistle-blower hotlines, training, and other efforts to ensure adherence to laws, regulations, and company policies. Yet malfeasance remains entrenched in the corporate world. Why? Too many firms treat compliance as a... View Details
- February 2018
- Article
Retention Futility: Targeting High-Risk Customers Might Be Ineffective.
By: Eva Ascarza
Companies in a variety of sectors are increasingly managing customer churn proactively, generally by detecting customers at the highest risk of churning and targeting retention efforts towards them. While there is a vast literature on developing churn prediction models... View Details
- 2023
- Working Paper
Efficient Discovery of Heterogeneous Quantile Treatment Effects in Randomized Experiments via Anomalous Pattern Detection
By: Edward McFowland III, Sriram Somanchi and Daniel B. Neill
In the recent literature on estimating heterogeneous treatment effects, each proposed method makes its own set of restrictive assumptions about the intervention’s effects and which subpopulations to explicitly estimate. Moreover, the majority of the literature provides... View Details
- 2018
- Working Paper
How Scheduling Can Bias Quality Assessment: Evidence from Food Safety Inspections
By: Maria Ibanez and Michael W. Toffel
Many production processes are subject to inspection to ensure they meet quality, safety, and environmental standards imposed by companies and regulators. Inspection accuracy is critical to inspections being a useful input to assessing risks, allocating quality... View Details
- November 2016
- Case
ShotSpotter
By: Mitchell Weiss and Sarah McAra
SST, Inc. offered a subscription-based gunfire detection service, ShotSpotter Flex, to cities across the United States in addition to a few abroad. Over its 20-year history, SST had mostly honed a reliable business-to-government sales model, and the company had been... View Details
- July–August 2016
- Article
How to Negotiate with a Liar
By: Leslie John
People, including negotiators, lie every day, so when you're trying to make a deal, it's important to defend against deception. The best strategy, says the author, is to focus not on detecting lies but on preventing them. She outlines five tactics that research has... View Details
- June 2016
- Article
Detecting Figures and Part Labels in Patents: Competition-based Development of Graphics Recognition Algorithms
By: Christoph Riedl, Richard Zanibbi, Marti A. Hearst, Siyu Zhu, Michael Menietti, Jason Crusan, Ivan Metelsky and Karim R. Lakhani
- February 2016 (Revised September 2017)
- Case
Neurotrack and the Alzheimer's Puzzle
By: Richard G. Hamermesh, Liz Kind and Carin-Isabel Knoop
Elli Kaplan founded Neurotrack in 2012 with a breakthrough noninvasive cognitive diagnostics test that will detect Alzheimer's disease in its earliest pre-symptomatic stages. While the company has gained great traction in the three years since it was started, with no... View Details