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Show Results For
- All HBS Web
(484)
- People (1)
- News (111)
- Research (208)
- Events (14)
- Multimedia (3)
- Faculty Publications (110)
- Research Summary
Internet Auctions for Close Substitutes
Economists agree that eBays auction design is sensible and potentially welfare-maximizing for the trade of collectibles, which are unique and idiosyncratic. For mainstream goods, which have close but imperfect substitutes (cars, cameras, computers, clothes), the... View Details
- 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).
James I. Cash
Professor Cash received a Bachelor of Science degree in Mathematics from Texas Christian University; a Master of Science in Computer Science from Purdue University's Graduate School of Mathematical Sciences; and a Doctor of Philosophy in Management Information... View Details
Adi Sunderam
Adi Sunderam is the Willard Prescott Smith Professor of Corporate Finance at Harvard Business School, a Research Associate at the National Bureau of Economic Research, and a Faculty Affiliate of the Harvard Economics department. He teaches Finance 2 in... View Details
- 2012
- Working Paper
Author-Level Eigenfactor Metrics: Evaluating the Influence of Authors, Institutions and Countries within the SSRN community
By: Jevin D. West, Michael C. Jensen, Ralph J. Dandrea, Gregg Gordon and Carl T. Bergstrom
In this paper, we show how the Eigenfactor® score, originally designed for ranking scholarly journals, can be adapted to rank the scholarly output of authors, institutions, and countries based on author-level citation data. Using the methods described herein, we... View Details
Keywords: Body of Literature; Measurement and Metrics; Networks; Rank and Position; Research; Motivation and Incentives
West, Jevin D., Michael C. Jensen, Ralph J. Dandrea, Gregg Gordon, and Carl T. Bergstrom. "Author-Level Eigenfactor Metrics: Evaluating the Influence of Authors, Institutions and Countries within the SSRN community." Harvard Business School Working Paper, No. 12-068, February 2012.
Feng Zhu
Feng Zhu is the MBA Class of 1958 Professor of Business Administration at Harvard Business School, where he leads the Platform Lab within the Digital, Data, and Design Institute, co-chairs the Harvard Business Analytics Program, and serves as the course head for the... View Details
- December 2020
- Article
The Parable of the Auctioneer: Complexity in Paul R. Milgrom's Discovering Prices
By: Scott Duke Kominers and Alexander Teytelboym
Designing marketplaces in complex settings requires both novel economic theory and real-world engineering, often drawing upon ideas from fields such as computer science and operations research. In Discovering Prices, Milgrom (2017) explains the theory and design... View Details
Kominers, Scott Duke, and Alexander Teytelboym. "The Parable of the Auctioneer: Complexity in Paul R. Milgrom's Discovering Prices." Journal of Economic Literature 58, no. 4 (December 2020): 1180–1196.
H. Kent Bowen
Professor Kent Bowen's current research and teaching is in the field of operations and technology management. He has served as course head for the required first year MBA course, Technology and Operations Management, two advanced level courses, Running and Growing... View Details
Ayelet Israeli
Ayelet Israeli is the Marvin Bower Associate Professor of Business Administration at the Harvard Business School Marketing Unit. She is the co-founder of the Customer Intelligence Lab at the Digital Data Design (D^3) Institute at Harvard Business School. She teaches... View Details
- March 2008
- Article
Testing a Purportedly More Learnable Auction Mechanism
We describe an auction mechanism in the class of Groves mechanisms that has received attention in the computer science literature because of its theoretical property of being more "learnable" than the standard second price auction mechanism. We bring this mechanism,... View Details
Milkman, Katherine L., James Burns, David Parkes, Gregory M. Barron, and Kagan Tumer. "Testing a Purportedly More Learnable Auction Mechanism." Special Issue on Theoretical, Empirical and Experimental Research on Auctions. Applied Economics Research Bulletin 2 (March 2008): 106–141. (Earlier version distributed as Harvard Business School Working Paper 08-064.)
- September 2023
- Article
Top Talent, Elite Colleges, and Migration: Evidence from the Indian Institutes of Technology
By: Prithwiraj Choudhury, Ina Ganguli and Patrick Gaulé
We study migration in the right tail of the talent distribution using a novel dataset of Indian high school students taking the Joint Entrance Exam (JEE), a college entrance exam used for admission to the prestigious Indian Institutes of Technology (IIT). We find a... View Details
Choudhury, Prithwiraj, Ina Ganguli, and Patrick Gaulé. "Top Talent, Elite Colleges, and Migration: Evidence from the Indian Institutes of Technology." Art. 103120. Journal of Development Economics 164 (September 2023).
- 02 Dec 2002
- Research & Ideas
The Secret of How Microsoft Stays on Top
numbers almost 40,000 firms. To understand the way Microsoft manages IP, you have to go back to the roots of the company. Back in the late 1970s, its first products were aimed at helping other programmers develop applications for the View Details
Keywords: by Sean Silverthorne
- 19 Nov 2001
- Research & Ideas
Alfred Chandler on the Electronic Century
public use—major new products of either consumer electronics or computer hardware with their essential software technologies. In the United States, no enterprise had the capability to commercialize new consumer electronics technologies.... View Details
- 2023
- Working Paper
Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development
By: Daniel Yue, Paul Hamilton and Iavor Bojinov
Predictive model development is understudied despite its centrality in modern artificial
intelligence and machine learning business applications. Although prior discussions
highlight advances in methods (along the dimensions of data, computing power, and
algorithms)... View Details
Keywords: Analytics and Data Science
Yue, Daniel, Paul Hamilton, and Iavor Bojinov. "Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development." Harvard Business School Working Paper, No. 23-029, December 2022. (Revised April 2023.)
- Article
How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness
By: Nripsuta Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes and Yang Liu
What is the best way to define algorithmic fairness? While many definitions of fairness have been proposed in the computer science literature, there is no clear agreement over a particular definition. In this work, we investigate ordinary people’s perceptions of three... View Details
Saxena, Nripsuta, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, and Yang Liu. "How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (2019).
How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness
What is the best way to define algorithmic fairness? While many definitions of fairness have been proposed in the computer science literature, there is no clear agreement over a particular definition. In this work, we investigate ordinary people’s perceptions of three... View Details
Satish K. Tadikonda
Satish Tadikonda is a Senior Lecturer in the Entrepreneurial Management Unit at Harvard Business School. In the MBA program, Satish teaches The Entrepreneurial Manager, a required first-year MBA course, and Entrepreneurship in Life Sciences, an elective course for... View Details
Nailing Prediction: Experimental Evidence on the Value of Tools in Predictive Model Development
Predictive model development is understudied despite its importance to modern businesses. Although prior discussions highlight advances in methods (along the dimensions of data, computing power, and algorithms) as the primary driver of model quality, the value of... View Details
- 12 Jun 2018
- First Look
New Research and Ideas, June 12, 2018
workers with heterogeneous human capital interface with machine learning, relative to the older Boolean search technology. We randomly assign individuals with and without computer science and engineering... View Details
Keywords: Dina Gerdeman