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Show Results For
- All HBS Web
(12,552)
- People (75)
- News (2,866)
- Research (3,663)
- Events (32)
- Multimedia (332)
- Faculty Publications (2,349)
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- March–April 1997
- Article
Virtuous Capital: What Foundations Can Learn From Venture Capitalists
By: Allen Grossman
Grossman, Allen. "Virtuous Capital: What Foundations Can Learn From Venture Capitalists." Harvard Business Review 75, no. 2 (March–April 1997).
- 21 Aug 2019
- Research & Ideas
What Machine Learning Teaches Us about CEO Leadership Style
performance. “Machine learning is able to utilize data that is both large in size, but also in a different form than what would traditionally fit into an Excel spreadsheet,” says Harvard Business School’s... View Details
Keywords: by Michael Blanding
- August 2023
- Article
Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel
By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh
Practitioners increasingly use machine learning (ML) models, yet models have become more complex and harder to understand. To understand complex models, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use... View Details
Slack, Dylan, Satyapriya Krishna, Himabindu Lakkaraju, and Sameer Singh. "Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel." Nature Machine Intelligence 5, no. 8 (August 2023): 873–883.
- July 1997
- Article
What Doctors Can Learn from the Business World
- 7 May 2003
- Other Presentation
Building a Competitive U.A.E Economy: The New Learning
Competitiveness presentation delivered in Dubai, United Arab Emirates. View Details
Porter, Michael E. "Building a Competitive U.A.E Economy: The New Learning." Institute for Strategy and Competitiveness, Dubai, UAE, May 7, 2003.
- February 1990 (Revised February 1992)
- Supplement
Manufacturing Learning Laboratory at Digital Equipment Corp. (C)
By: Dorothy Leonard-Barton and paul Sagawa
Leonard-Barton, Dorothy, and paul Sagawa. "Manufacturing Learning Laboratory at Digital Equipment Corp. (C)." Harvard Business School Supplement 690-055, February 1990. (Revised February 1992.)
- November 2022
- Supplement
What are the lessons learned to make intrapreneurship successful in a large company
Casadesus-Masanell, Ramon. "What are the lessons learned to make intrapreneurship successful in a large company." Harvard Business School Multimedia/Video Supplement 723-859, November 2022.
- April 13, 2017
- Article
What Precision Medicine Can Learn from the NFL
By: Richard G. Hamermesh and Kathryn E. Giusti
Hamermesh, Richard G., and Kathryn E. Giusti. "What Precision Medicine Can Learn from the NFL." Forbes.com (April 13, 2017).
- January 12, 2017
- Article
What Cancer Researchers Can Learn from Direct-to-Consumer Companies
By: Richard G. Hamermesh and Kathryn E. Giusti
Hamermesh, Richard G., and Kathryn E. Giusti. "What Cancer Researchers Can Learn from Direct-to-Consumer Companies." Harvard Business Review (website) (January 12, 2017).
- May 2009
- Article
Learning From Economic Experiments in China and India
By: Tarun Khanna
Khanna, Tarun. "Learning From Economic Experiments in China and India." Academy of Management Perspectives 23, no. 2 (May 2009): 36–43.
- December 1997 (Revised October 2012)
- Teaching Note
McKinsey & Company: Managing Knowledge and Learning (TN)
Teaching Note for (9-396-357). View Details
Keywords: Consulting Industry
- 2021
- Chapter
Towards a Unified Framework for Fair and Stable Graph Representation Learning
By: Chirag Agarwal, Himabindu Lakkaraju and Marinka Zitnik
As the representations output by Graph Neural Networks (GNNs) are increasingly employed in real-world applications, it becomes important to ensure that these representations are fair and stable. In this work, we establish a key connection between counterfactual... View Details
Agarwal, Chirag, Himabindu Lakkaraju, and Marinka Zitnik. "Towards a Unified Framework for Fair and Stable Graph Representation Learning." In Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence, edited by Cassio de Campos and Marloes H. Maathuis, 2114–2124. AUAI Press, 2021.
- 2021
- Working Paper
Once Bitten, Twice Shy: Learning from Corporate Fraud and Corporate Governance Spillovers
By: Trung Nguyen
This paper finds that investors learn from their experience with corporate fraud and financial misconduct and modify their investment behavior to avoid suspicious firms and increase corporate governance efforts. More specially, mutual funds that experienced corporate... View Details
Keywords: Institutional Investors; Investor Experience; Shareholder Voting; Corporate Fraud; Corporate Governance; Institutional Investing; Behavior; Change; Learning
Nguyen, Trung. "Once Bitten, Twice Shy: Learning from Corporate Fraud and Corporate Governance Spillovers." Harvard Business School Working Paper, No. 21-135, June 2021.
- 2020
- Working Paper
Of Learning and Forgetting: Centrism, Populism, and the Legitimacy Crisis of Globalization
By: Rawi Abdelal
Every order is a bargain with disappointments and trade-offs. Thus is every order an unstable equilibrium. The first era of globalization, circa 1870–1914, created both international prosperity and domestic instability. That instability was fully realized during the... View Details
Keywords: Centrism; Populism; Globalization; History; Balance and Stability; Economic Systems; Government and Politics; Learning
Abdelal, Rawi. "Of Learning and Forgetting: Centrism, Populism, and the Legitimacy Crisis of Globalization." Harvard Business School Working Paper, No. 21-008, July 2020.
- 2015
- Article
A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes
By: Himabindu Lakkaraju, Everaldo Aguiar, Carl Shan, David Miller, Nasir Bhanpuri, Rayid Ghani and Kecia Addison
Lakkaraju, Himabindu, Everaldo Aguiar, Carl Shan, David Miller, Nasir Bhanpuri, Rayid Ghani, and Kecia Addison. "A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes." Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining 21st (2015).
- 12 Nov 2001
- Research & Ideas
Can Religion and Business Learn From Each Other?
learn from business? I think there's a lot of room for cross-learning here. One of the things I think the religious community can learn from the business community is that the realm of business is not as... View Details
Keywords: by Martha Lagace
- February 2010
- Article
Friend or Foe? Cooperation and Learning in High-Stakes Games
By: Felix Oberholzer-Gee, Joel Waldfogel and Matthew White
Oberholzer-Gee, Felix, Joel Waldfogel, and Matthew White. "Friend or Foe? Cooperation and Learning in High-Stakes Games." Review of Economics and Statistics 92, no. 1 (February 2010): 179–187.
- Article
Learning from Potentially Biased Statistics: Household Inflation Perceptions and Expectations in Argentina
By: Alberto Cavallo, Guillermo Cruces and Ricardo Perez-Truglia
When forming expectations, households may be influenced by perceived bias in the information they receive. In this paper, we study how individuals learn from potentially biased statistics using data from both a natural experiment and a survey experiment during a... View Details
Keywords: Inflation Expectations; Bayesian Estimation; Inflation and Deflation; Information; Household; Behavior; Argentina
Cavallo, Alberto, Guillermo Cruces, and Ricardo Perez-Truglia. "Learning from Potentially Biased Statistics: Household Inflation Perceptions and Expectations in Argentina." Brookings Papers on Economic Activity (Spring 2016): 59–108.
- 2024
- Working Paper
Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization
This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
Keywords: Heterogeneous Treatment Effect; Multi-task Learning; Representation Learning; Personalization; Promotion; Deep Learning; Field Experiments; Customer Focus and Relationships; Customization and Personalization
Huang, Ta-Wei, Eva Ascarza, and Ayelet Israeli. "Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization." Harvard Business School Working Paper, No. 24-076, June 2024.