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Show Results For
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All HBS Web
(1,701)
- People (9)
- News (315)
- Research (1,021)
- Events (12)
- Multimedia (10)
- Faculty Publications (834)
- Profile
Amanda Pratt
were very analytical and process oriented," she says. But there's another side to Amanda, one that wants to explore options and is willing to embrace novelty. Instead of going to a traditional engineering school, she chose a new...
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Keywords:
Healthcare/Biotech
- Forthcoming
- Article
The Double-Edged Sword of Exemplar Similarity
By: Majid Majzoubi, Eric Zhao, Tiona Zuzul and Greg Fisher
We investigate how a firm’s positioning relative to category exemplars shapes security analysts’ evaluations. Using a two-stage model of evaluation (initial screening and subsequent assessment), we propose that exemplar similarity enhances a firm’s recognizability and...
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Majzoubi, Majid, Eric Zhao, Tiona Zuzul, and Greg Fisher. "The Double-Edged Sword of Exemplar Similarity." Organization Science (forthcoming). (Pre-published online May 7, 2024.)
- 2023
- Working Paper
Design-Based Inference for Multi-arm Bandits
By: Dae Woong Ham, Iavor I. Bojinov, Michael Lindon and Martin Tingley
Multi-arm bandits are gaining popularity as they enable real-world sequential decision-making across application areas, including clinical trials, recommender systems, and online decision-making. Consequently, there is an increased desire to use the available...
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Ham, Dae Woong, Iavor I. Bojinov, Michael Lindon, and Martin Tingley. "Design-Based Inference for Multi-arm Bandits." Harvard Business School Working Paper, No. 24-056, March 2024.
- 2023
- Article
On Minimizing the Impact of Dataset Shifts on Actionable Explanations
By: Anna P. Meyer, Dan Ley, Suraj Srinivas and Himabindu Lakkaraju
The Right to Explanation is an important regulatory principle that allows individuals to request actionable explanations for algorithmic decisions. However, several technical challenges arise when providing such actionable explanations in practice. For instance, models...
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Meyer, Anna P., Dan Ley, Suraj Srinivas, and Himabindu Lakkaraju. "On Minimizing the Impact of Dataset Shifts on Actionable Explanations." Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI) 39th (2023): 1434–1444.
- 2022
- Article
OpenXAI: Towards a Transparent Evaluation of Model Explanations
By: Chirag Agarwal, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik and Himabindu Lakkaraju
While several types of post hoc explanation methods have been proposed in recent literature, there is very little work on systematically benchmarking these methods. Here, we introduce OpenXAI, a comprehensive and extensible opensource framework for evaluating and...
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Agarwal, Chirag, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, and Himabindu Lakkaraju. "OpenXAI: Towards a Transparent Evaluation of Model Explanations." Advances in Neural Information Processing Systems (NeurIPS) (2022).
- March 2022 (Revised July 2022)
- Technical Note
Linear Regression
This note provides an overview of linear regression for an introductory data science course. It begins with a discussion of correlation, and explains why correlation does not necessarily imply causation. The note then describes the method of least squares, and how to...
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Keywords:
Data Science;
Linear Regression;
Mathematical Modeling;
Mathematical Methods;
Analytics and Data Science
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Linear Regression." Harvard Business School Technical Note 622-100, March 2022. (Revised July 2022.)
- 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...
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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).
- Profile
Kayode Ogunro
employer. How has HBS prepared you for your new job? My job will require a substantial amount of travel to Europe and Africa and more hands on management of deals and projects than I would face with a typical investment firm. My HBS experience has definitely helped me...
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- 22 Sep 2015
- News
Promoting a Healthy Policy Agenda
different factors to be considered. And so bringing a very objective and analytical approach to that, I think, is important and helpful.” (Published September 2015)
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- Other Article
How to Make Remote Monitoring Tech Part of Everyday Health Care
By: Samantha F. Sanders, Ariel Dora Stern and William J. Gordon
Remote patient monitoring is a subset of telehealth that involves the collection, transmission, evaluation, and communication of patient health data from electronic devices. These devices include wearable sensors, implanted equipment, and handheld instruments. During...
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Keywords:
Health Care and Treatment;
Information Technology;
Analytics and Data Science;
Technology Adoption
Sanders, Samantha F., Ariel Dora Stern, and William J. Gordon. "How to Make Remote Monitoring Tech Part of Everyday Health Care." Harvard Business Review (website) (July 2, 2020).
- April 1996 (Revised June 1996)
- Background Note
Cleveland Turnaround (C), The: Facts and Figures
By: James E. Austin and Jaan Elias
Traces the Cleveland community's efforts to move the city from economic, social, and political crisis in the late 1970s into revitalization and progress in the 1980s and 1990s. Special attention is given to the role of business leaders and the public-private...
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Keywords:
Leading Change;
Analytics and Data Science;
Economic Growth;
Business and Community Relations;
Cleveland
Austin, James E., and Jaan Elias. "Cleveland Turnaround (C), The: Facts and Figures." Harvard Business School Background Note 796-153, April 1996. (Revised June 1996.)
- Article
Mitigating Bias in Adaptive Data Gathering via Differential Privacy
By: Seth Neel and Aaron Leon Roth
Data that is gathered adaptively—via bandit algorithms, for example—exhibits bias. This is true both when gathering simple numeric valued data—the empirical means kept track of by stochastic bandit algorithms are biased downwards—and when gathering more complicated...
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Neel, Seth, and Aaron Leon Roth. "Mitigating Bias in Adaptive Data Gathering via Differential Privacy." Proceedings of the International Conference on Machine Learning (ICML) 35th (2018).
- December 1996 (Revised November 2006)
- Background Note
General Mills, Inc.: Appendix of Comparable Company Data
By: William J. Bruns Jr.
Financial ratios for comparable companies to be used in conjunction with an analysis of the General Mills Annual Report.
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Bruns, William J., Jr. "General Mills, Inc.: Appendix of Comparable Company Data." Harvard Business School Background Note 197-037, December 1996. (Revised November 2006.)
- January 2016
- Case
Acxiom
By: John Deighton
Acxiom built the market for personal data, yet sales have been flat for a decade during which marketing's appetite for data has exploded. Will the acquisition of a digital data onboarder LiveRamp give marketers what they want from a data broker?
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History's Guiding Light
entrepreneurs and business leaders from across emerging markets, was a goldmine. It allowed me to explore questions on emerging market business issues from the eyes of those on the ground. CEM also provided me fruitful ground to experiment with View Details
- 08 May 2019
- News
Fellowships Enable Students to Broaden Their Impact
the data analytics team, he brought to the nonprofit his solid background in behavioral economics from Emory University and his financial acumen from his trading days. Agarwal’s goal was to use data and technology to help make the schools...
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- 09 Dec 2015
- Research Event
How Do You Predict Demand and Set Prices For Products Never Sold Before?
explained that the world of business analytics includes descriptive analytics (analyzing what has happened), predictive analytics (analyzing data to figure out what will...
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- 2023
- Article
Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators
By: Benjamin Jakubowski, Siram Somanchi, Edward McFowland III and Daniel B. Neill
Regression discontinuity (RD) designs are widely used to estimate causal effects in the absence of a randomized experiment. However, standard approaches to RD analysis face two significant limitations. First, they require a priori knowledge of discontinuities in...
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Jakubowski, Benjamin, Siram Somanchi, Edward McFowland III, and Daniel B. Neill. "Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators." Journal of Machine Learning Research 24, no. 133 (2023): 1–57.
- March 2023
- Supplement
Allianz Türkiye (B): Adapting to a Changing World
By: John D. Macomber and Fares Khrais
Keywords:
Insurance And Reinsurance;
Natural Disasters;
Turkey;
Insurance;
Climate Change;
Analytics and Data Science;
Insurance Industry;
Financial Services Industry;
Turkey
Macomber, John D., and Fares Khrais. "Allianz Türkiye (B): Adapting to a Changing World." Harvard Business School Supplement 223-076, March 2023.
- November–December 2015
- Article
Active Postmarketing Drug Surveillance for Multiple Adverse Events
By: Joel Goh, Margrét V. Bjarnadóttir, Mohsen Bayati and Stefanos A. Zenios
Postmarketing drug surveillance is the process of monitoring the adverse events of pharmaceutical or medical devices after they are approved by the appropriate regulatory authorities. Historically, such surveillance was based on voluntary reports by medical...
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Keywords:
Drug Surveillance;
Health Care;
Stochastic Models;
Queueing;
Diffusion Approximation;
Brownian Motion;
Health Care and Treatment;
Analytics and Data Science;
Analysis
Goh, Joel, Margrét V. Bjarnadóttir, Mohsen Bayati, and Stefanos A. Zenios. "Active Postmarketing Drug Surveillance for Multiple Adverse Events." Operations Research 63, no. 6 (November–December 2015): 1528–1546. (Finalist, 2012 INFORMS Health Applications Society Pierskalla Award.)