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Show Results For
- All HBS Web
(1,723)
- People (9)
- News (318)
- Research (1,048)
- Events (15)
- Multimedia (10)
- Faculty Publications (860)
- 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... View Details
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. View Details
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? View Details
- Profile
Colt Stander
he says. “But the summer Analytics program really helped. It was a boot camp that boosted my confidence as well as my quantitative skills.” And upon reflection, design and business share similar challenges. The pathways aren’t clear,”... View Details
- 2023
- Article
Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset
By: Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu and Michael Lingzhi Li
Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the lack of standardized and comprehensive datasets. To address this gap, we introduce CMExam,... View Details
Keywords: Large Language Model; AI and Machine Learning; Analytics and Data Science; Health Industry
Liu, Junling, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu, and Michael Lingzhi Li. "Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 36 (2023).
- June 2023
- Article
How New Ideas Diffuse in Science
By: Mengjie Cheng, Daniel Scott Smith, Xiang Ren, Hancheng Cao, Sanne Smith and Daniel A. McFarland
What conditions help new ideas spread? Can knowledge entrepreneurs’ position and develop new ideas in ways that help them take off? Most innovation research focuses on products and their reference. That focus ignores the ideas themselves and the broader ideational... View Details
Keywords: Innovation Adoption; Natural Language Processing; Knowledge; Science; Innovation and Invention; Knowledge Sharing; Analytics and Data Science
Cheng, Mengjie, Daniel Scott Smith, Xiang Ren, Hancheng Cao, Sanne Smith, and Daniel A. McFarland. "How New Ideas Diffuse in Science." American Sociological Review 88, no. 3 (June 2023): 522–561.
- November 5, 2021
- Article
Leaders: Stop Confusing Correlation with Causation
By: Michael Luca
We’ve all been told that correlation does not imply causation. Yet many business leaders, elected officials, and media outlets still make causal claims based on misleading correlations. These claims are too often unscrutinized, amplified, and mistakenly used to guide... View Details
Keywords: Behavioral Economics; Data Analysis; Organizations; Decision Making; Analytics and Data Science; Analysis; Learning
Luca, Michael. "Leaders: Stop Confusing Correlation with Causation." Harvard Business Review Digital Articles (November 5, 2021).
- 2021
- Working Paper
Time Dependency, Data Flow, and Competitive Advantage
Data is fundamental to machine learning-based products and services and is considered strategic due to its externalities for businesses, governments, non-profits, and more generally for society. It is renowned that the value of organizations (businesses, government... View Details
Keywords: Economics Of AI; Value Of Data; Perishability; Time Dependency; Flow Of Data; Data Strategy; Analytics and Data Science; Value; Strategy; Competitive Advantage
Valavi, Ehsan, Joel Hestness, Marco Iansiti, Newsha Ardalani, Feng Zhu, and Karim R. Lakhani. "Time Dependency, Data Flow, and Competitive Advantage." Harvard Business School Working Paper, No. 21-099, March 2021.
- 18 Oct 2016
- News
China, artificial intelligence, and Jim Breyer
partner level,” he said. “They are brilliant, work 100 hours a week and are intensely competitive.” When considering in which startups to invest capital, Breyer said if the company does not include an artificial intelligence data analysis component he will not consider... View Details
Keywords: Jennifer Myers
- Profile
Maliha Khan
Why was getting a business education important to you? I saw an MBA as important for two reasons: I wanted key analytical and quantitative skills that would help me make decisions and give me more confidence in my judgment; and secondly,... View Details
- January–February 2025
- 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... View Details
Majzoubi, Majid, Eric Zhao, Tiona Zuzul, and Greg Fisher. "The Double-Edged Sword of Exemplar Similarity." Organization Science 36, no. 1 (January–February 2025): 121–144.
- 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... View Details
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... View Details
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... View Details
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 January 2025)
- 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... View Details
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 January 2025.)
- 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).
- April 2017
- Teaching Note
Basecamp: Pricing
This Teaching Note accompanies HBS No. 817-067 “Basecamp: Pricing” in which a data analyst at Basecamp is evaluating the results of pricing research and its potential implications for the venture's latest version of its project management software product. View Details
- February 2011
- Supplement
Dataset for "MercadoLibre.com" (CW)
By: Francisco de Asis Martinez-Jerez
Datasets of listings and powersellers transactions to perform analysis for the case. View Details
- February 2006
- Article
Do Stronger Intellectual Property Rights Increase International Technology Transfer? Empirical Evidence from U.S. Firm-Level Panel Data
By: Lee G. Branstetter, Raymond Fisman and C. Fritz Foley
Keywords: Intellectual Property; Rights; Information Technology; Information; Analytics and Data Science; United States
Branstetter, Lee G., Raymond Fisman, and C. Fritz Foley. "Do Stronger Intellectual Property Rights Increase International Technology Transfer? Empirical Evidence from U.S. Firm-Level Panel Data." Quarterly Journal of Economics 121, no. 1 (February 2006): 321–349.
- 2019
- Article
History, Micro Data, and Endogenous Growth
By: Ufuk Akcigit and Tom Nicholas
The study of economic growth is concerned with long-run changes, and therefore, historical data should be especially influential in informing the development of new theories. In this review, we draw on the recent literature to highlight areas in which study of history... View Details
Keywords: Economic Development; Growth; Innovation; Economic Growth; History; Analytics and Data Science; Innovation and Invention
Akcigit, Ufuk, and Tom Nicholas. "History, Micro Data, and Endogenous Growth." Annual Review of Economics 11 (2019): 615–633.