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Show Results For
- All HBS Web
(14,862)
- People (36)
- News (4,344)
- Research (8,642)
- Events (107)
- Multimedia (366)
- Faculty Publications (7,247)
- 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
Post Hoc Explanations of Language Models Can Improve Language Models
By: Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh and Himabindu Lakkaraju
Large Language Models (LLMs) have demonstrated remarkable capabilities in performing complex tasks. Moreover, recent research has shown that incorporating human-annotated rationales (e.g., Chain-of-Thought prompting) during in-context learning can significantly enhance... View Details
Krishna, Satyapriya, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, and Himabindu Lakkaraju. "Post Hoc Explanations of Language Models Can Improve Language Models." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 2023
- Working Paper
Distributionally Robust Causal Inference with Observational Data
By: Dimitris Bertsimas, Kosuke Imai and Michael Lingzhi Li
We consider the estimation of average treatment effects in observational studies and propose a new framework of robust causal inference with unobserved confounders. Our approach is based on distributionally robust optimization and proceeds in two steps. We first... View Details
Bertsimas, Dimitris, Kosuke Imai, and Michael Lingzhi Li. "Distributionally Robust Causal Inference with Observational Data." Working Paper, February 2023.
- 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).
- January 2021
- Supplement
E-Commerce Analytics for CPG Firms (B): Optimizing Assortment for a New Retailer
By: Ayelet Israeli and Fedor (Ted) Lisitsyn
The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for... View Details
Keywords: Data Analysis; Data Analytics; CPG; Consumer Packaged Goods (CPG); Online Channel; Retail; Retail Analytics; Retailing Industry; Data; Data Sharing; Ecommerce; Assortment Optimization; Assortment Planning; Analytics and Data Science; Retention; Retail Industry; Consumer Products Industry; United States
- February 2017 (Revised May 2017)
- Case
Rapid7
By: Mitchell Weiss, Paul Gompers and Silpa Kovvali
That Corey Thomas, vice president at Boston-based Rapid7, Inc., was about to enter his investor’s boardroom to negotiate a potential acquisition of Metasploit, LLC, was already an unlikely achievement of sorts. After all, Rapid7 was a venture-backed, corporate... View Details
- 2011
- Case
The Secrets to Managing Business Analytics Projects
By: Thomas H. Davenport, Stijn Viaene and Annabel Van den Bunder
Managers have used business analytics to inform their decision making for years. And while few companies would qualify as being what management innovation and strategy expert Thomas H. Davenport has dubbed "analytic competitors," more and more businesses are moving in... View Details
Davenport, Thomas H., Stijn Viaene, and Annabel Van den Bunder. "The Secrets to Managing Business Analytics Projects." 2011.
- Article
Computer-Aided Deliberation: Model Management and Group Decision Support
By: J. F. Nunamaker, L. M. Applegate and Benn R Konsynski
Nunamaker, J. F., L. M. Applegate, and Benn R Konsynski. "Computer-Aided Deliberation: Model Management and Group Decision Support." Operations Research 36, no. 6 (November–December 1988).
- 10 Dec 2021
- News
New NYC Law Restricts Hiring Based on Artificial Intelligence
- 05 Nov 2021
- News
How to Tap the Talent Automated HR Platforms Miss
- 03 Feb 2015
- News
Brad McGee: Making A Difference
- 01 Sep 2014
- News
In My Humble Opinion: Terry Virts (GMP 11, 2011)
INTO THE BLUE: Virts, poised for a space-walk training session in the Neutral Buoyancy Laboratory near Johnson Space Center. (Photos by NASA) An astronaut with NASA since 2000, Terry Virts (GMP 11, 2011) piloted the space shuttle Endeavour for a 14-day mission to the... View Details
Keywords: Julia Hanna
- 28 May 2014
- News
Leveling the Playing Field for all Learners
Sal Khan (MBA 2003) is the founder and CEO of Khan Academy. In this video, he talks about new partnerships his organization is forming to bring the tools and advantages of online learning to wider audiences. “I’m the founder and executive director of the Khan Academy,... View Details
- 14 Dec 2013
- News
IT Start-Up Eases Health Plan Hiccups
- 2023
- Article
Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten
By: Himabindu Lakkaraju, Satyapriya Krishna and Jiaqi Ma
The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for an... View Details
Keywords: Analytics and Data Science; AI and Machine Learning; Decision Making; Governing Rules, Regulations, and Reforms
Lakkaraju, Himabindu, Satyapriya Krishna, and Jiaqi Ma. "Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 17808–17826.
- October 2024 (Revised November 2024)
- Case
SWEN Blue Ocean: Impact Investing Goes to Sea
By: Vikram S Gandhi and David Allen
In August 2023, SWEN Blue Ocean, a €170 million impact fund that invested in startups contributing to ocean sustainability, faced a critical investment decision. Part of SWEN Capital Partners, an €8 billion, Paris-based private equity fund, Blue Ocean was co-founded in... View Details
Keywords: Communication Technology; Environmental Sustainability; Green Technology; Venture Capital; Private Equity; Investment Funds; Science-Based Business; Technological Innovation; Financial Services Industry; France; Paris; Italy
Gandhi, Vikram S., and David Allen. "SWEN Blue Ocean: Impact Investing Goes to Sea." Harvard Business School Case 325-013, October 2024. (Revised November 2024.)