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- All HBS Web
(1,174)
- People (13)
- News (393)
- Research (407)
- Events (8)
- Multimedia (12)
- Faculty Publications (90)
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- 2021
- Working Paper
Deep Learning for Two-Sided Matching
By: Sai Srivatsa Ravindranatha, Zhe Feng, Shira Li, Jonathan Ma, Scott Duke Kominers and David Parkes
We initiate the use of a multi-layer neural network to model two-sided matching and to explore the design space between strategy-proofness and stability. It is well known that both properties cannot be achieved simultaneously but the efficient frontier in this design... View Details
Keywords: Strategy-proofness; Deep Learning; Two-Sided Platforms; Marketplace Matching; Balance and Stability
Srivatsa Ravindranatha, Sai, Zhe Feng, Shira Li, Jonathan Ma, Scott Duke Kominers, and David Parkes. "Deep Learning for Two-Sided Matching." Working Paper, July 2021.
- 2025
- Working Paper
Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning
Reinforcement learning (RL) offers potential for optimizing sequences of customer interactions by modeling the relationships
between customer states, company actions, and long-term value. However, its practical implementation often faces significant
challenges.... View Details
Keywords: Dynamic Policy; Deep Reinforcement Learning; Representation Learning; Dynamic Difficulty Adjustment; Latent Variable Models; Customer Relationship Management; Customer Value and Value Chain; Foreign Direct Investment; Analytics and Data Science
Ma, Liangzong, Ta-Wei Huang, Eva Ascarza, and Ayelet Israeli. "Dynamic Personalization with Multiple Customer Signals: Multi-Response State Representation in Reinforcement Learning." Harvard Business School Working Paper, No. 25-037, February 2025.
- Article
Development of a Deep Learning Algorithm for Periapical Disease Detection in Dental Radiographs
By: Michael G. Endres, Florian Hillen, Marios Salloumis, Ahmad R. Sedaghat, Stefan M. Niehues, Olivia Quatela, Henning Hanken, Ralf Smeets, Benedicta Beck-Broichsitter, Carsten Rendenbach, Karim R. Lakhani, Max Helland and Robert A. Gaudin
Periapical radiolucencies, which can be detected on panoramic radiographs, are one of the most common radiographic findings in dentistry and have a differential diagnosis including infections, granuloma, cysts, and tumors. In this study, we seek to investigate the... View Details
Keywords: Artificial Intelligence; Diagnosis; Computer-assisted; Image Interpretation; Machine Learning; Radiography; Panoramic Radiograph; AI and Machine Learning
Endres, Michael G., Florian Hillen, Marios Salloumis, Ahmad R. Sedaghat, Stefan M. Niehues, Olivia Quatela, Henning Hanken, Ralf Smeets, Benedicta Beck-Broichsitter, Carsten Rendenbach, Karim R. Lakhani, Max Helland, and Robert A. Gaudin. "Development of a Deep Learning Algorithm for Periapical Disease Detection in Dental Radiographs." Diagnostics 10, no. 6 (June 2020).
- February 2021
- Article
Topic Classification of Electric Vehicle Consumer Experiences with Transformer-Based Deep Learning
By: Sooji Ha, Daniel J Marchetto, Sameer Dharur and Omar Isaac Asensio
The transportation sector is a major contributor to greenhouse gas (GHG) emissions and is a driver of adverse health effects globally. Increasingly, government policies have promoted the adoption of electric vehicles (EVs) as a solution to mitigate GHG emissions.... View Details
Keywords: Natural Language Processing; Analytics and Data Science; Environmental Sustainability; Infrastructure; Transportation; Policy
Ha, Sooji, Daniel J Marchetto, Sameer Dharur, and Omar Isaac Asensio. "Topic Classification of Electric Vehicle Consumer Experiences with Transformer-Based Deep Learning." Art. 100195. Patterns 2, no. 2 (February 2021).
- 12 Dec 2014
- Conference Presentation
Aspect Specific Sentiment Analysis Using Hierarchical Deep Learning
By: Himabindu Lakkaraju, Richard Socher and Chris Manning
Lakkaraju, Himabindu, Richard Socher, and Chris Manning. "Aspect Specific Sentiment Analysis Using Hierarchical Deep Learning." Paper presented at the 28th Annual Conference on Neural Information Processing Systems (NIPS), Workshop on Deep Learning and Representation Learning, Montreal, Canada, December 12, 2014.
- September 2006
- Article
Learning in Noisy Games: Partial Reinforcement and the Sustainability of Cooperation
By: Yoella Bereby-Meyer and Alvin E. Roth
Bereby-Meyer, Yoella, and Alvin E. Roth. "Learning in Noisy Games: Partial Reinforcement and the Sustainability of Cooperation." American Economic Review 96, no. 4 (September 2006): 1029–1042.
- September 2006
- Article
The Speed of Learning in Noisy Games: Partial Reinforcement and the Sustainability of Cooperation
By: Yoella Bereby-Meyer and Alvin E. Roth
In an experiment, players ability to learn to cooperate in the repeated prisoners dilemma was substantially diminished when the payoffs were noisy, even though players could monitor one anothers past actions perfectly. In contrast, in one-time play against a succession... View Details
Bereby-Meyer, Yoella, and Alvin E. Roth. "The Speed of Learning in Noisy Games: Partial Reinforcement and the Sustainability of Cooperation." American Economic Review 96, no. 4 (September 2006): 1029–1042.
- March 2022 (Revised January 2025)
- Technical Note
Prediction & Machine Learning
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional... View Details
Keywords: Machine Learning; Data Science; Learning; Analytics and Data Science; Performance Evaluation; AI and Machine Learning
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Prediction & Machine Learning." Harvard Business School Technical Note 622-101, March 2022. (Revised January 2025.)
- 01 Jun 2018
- News
Digging Deep
operations, creating 400,000 direct manufacturing jobs since 2010. PwC predicts that in the years ahead “manufacturers in all industries will find themselves in a race to efficiently produce products at the point of demand.” BCG encourages companies to rethink their... View Details
Keywords: Julia Hanna
- 04 Sep 2019
- News
Deep Dive
The Pressure Drop anchored above the Mariana Trench in May. (photo by Tamara Stubbs) A potentially new species of sea squirt discovered in the Indian Ocean’s Java Trench in April (courtesy Five Deeps Expedition) Victor Vescovo has always... View Details
- 1999
- Chapter
On the Role of Reinforcement Learning in Experimental Games: The Cognitive Game Theory Approach
By: Ido Erev and A. E. Roth
- 2020
- Working Paper
Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach
By: Eva Ascarza
The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can... View Details
Keywords: Customer Management; Targeting; Deep Exponential Families; Probabilistic Machine Learning; Cold Start Problem; Customer Relationship Management; Customer Value and Value Chain; Consumer Behavior; Analytics and Data Science; Mathematical Methods; Retail Industry
Padilla, Nicolas, and Eva Ascarza. "Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach." Harvard Business School Working Paper, No. 19-091, February 2019. (Revised May 2020. Accepted at the Journal of Marketing Research.)
- September 1998
- Article
Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria
By: Ido Erev and A. E. Roth
Erev, Ido, and A. E. Roth. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria." American Economic Review 88, no. 4 (September 1998): 848–881.
- October 2021
- Article
Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach
By: Nicolas Padilla and Eva Ascarza
The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can... View Details
Keywords: Customer Management; Targeting; Deep Exponential Families; Probabilistic Machine Learning; Cold Start Problem; Customer Relationship Management; Programs; Consumer Behavior; Analysis
Padilla, Nicolas, and Eva Ascarza. "Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach." Journal of Marketing Research (JMR) 58, no. 5 (October 2021): 981–1006.
- 2006
- Conference Paper
Modeling Repeated Play of the Prisoners' Dilemma with Reinforcement Learning over an Enriched Strategy Set
By: A. E. Roth and Ido Erev
- 05 May 2008
- Research & Ideas
Connecting with Consumers Using Deep Metaphors
language of thought and expression. It is a language that marketers must learn to speak if they are to understand and connect meaningfully with their customers. Q: How did you become fascinated by deep... View Details
- May 1999
- Article
The Effect of Adding a Constant to All Payoffs: Experimental Investigation, and a Reinforcement Learning Model with Self-Adjusting Speed of Learning
By: Ido Erev, Yoella Bereby-Meyer and Alvin E. Roth
Erev, Ido, Yoella Bereby-Meyer, and Alvin E. Roth. "The Effect of Adding a Constant to All Payoffs: Experimental Investigation, and a Reinforcement Learning Model with Self-Adjusting Speed of Learning." Journal of Economic Behavior & Organization 39, no. 1 (May 1999): 111–128.
- February 2025
- Article
Deep Responsibility, SDGs, and Asia: A Historical Perspective
By: Geoffrey Jones
Although it was only in 2015 the 17 SDGs were adopted by UN Member States, many of the underlying ideas can be found in the strategies of some businesses going back to the nineteenth century. Asia was the home of many of the most advanced concepts of business... View Details
Keywords: ESG; Multinational Corporation; Sustainability; Corporate Social Responsibility and Impact; Multinational Firms and Management; Corporate Governance; Leadership; Asia
Jones, Geoffrey. "Deep Responsibility, SDGs, and Asia: A Historical Perspective." Asian Business & Management 24, no. 1 (February 2025): 25–32.
- 01 Jun 2008
- News
Immersion Program Digs Deep
or kitchen and bathroom finishings. The global nature of the student group created additional opportunities for learning through different perspectives, Abrami notes. Rytis Vitkauskas (MBA ’08), a native of Lithuania, says he signed up... View Details
- December 2023
- Article
Self-Orienting in Human and Machine Learning
By: Julian De Freitas, Ahmet Uğuralp, Zeliha Uğuralp, Laurie Paul, Joshua B. Tenenbaum and T. Ullman
A current proposal for a computational notion of self is a representation of one’s body in a specific time and place, which includes the recognition of that representation as the agent. This turns self-representation into a process of self-orientation, a challenging... View Details
De Freitas, Julian, Ahmet Uğuralp, Zeliha Uğuralp, Laurie Paul, Joshua B. Tenenbaum, and T. Ullman. "Self-Orienting in Human and Machine Learning." Nature Human Behaviour 7, no. 12 (December 2023): 2126–2139.