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Show Results For
- All HBS Web
(853)
- News (79)
- Research (640)
- Events (14)
- Multimedia (4)
- Faculty Publications (634)
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- January 1997
- Background Note
Simulation as a Decision Aid
By: Roy D. Shapiro
A brief introduction to simulation--what it is, why it's used, etc. Meant to set context for a first class on simulation. A rewritten version of an earlier note. View Details
Shapiro, Roy D. "Simulation as a Decision Aid." Harvard Business School Background Note 697-062, January 1997.
- 2022
- Article
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods.
By: Chirag Agarwal, Marinka Zitnik and Himabindu Lakkaraju
As Graph Neural Networks (GNNs) are increasingly employed in real-world applications, it becomes critical to ensure that the stakeholders understand the rationale behind their predictions. While several GNN explanation methods have been proposed recently, there has... View Details
Keywords: Graph Neural Networks; Explanation Methods; Mathematical Methods; Framework; Theory; Analysis
Agarwal, Chirag, Marinka Zitnik, and Himabindu Lakkaraju. "Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 25th (2022).
- Article
Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses
By: Kaivalya Rawal and Himabindu Lakkaraju
As predictive models are increasingly being deployed in high-stakes decision-making, there has been a lot of interest in developing algorithms which can provide recourses to affected individuals. While developing such tools is important, it is even more critical to... View Details
Rawal, Kaivalya, and Himabindu Lakkaraju. "Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses." Advances in Neural Information Processing Systems (NeurIPS) 33 (2020).
- October 2020
- Article
Comparative Statics for Size-Dependent Discounts in Matching Markets
By: David Delacretaz, Scott Duke Kominers and Alexandru Nichifor
We prove a natural comparative static for many-to-many matching markets in which agents’ choice functions exhibit size-dependent discounts: reducing the extent to which some agent discounts additional partners leads to improved outcomes for the agents on the other side... View Details
Keywords: Size-dependent Discounts; Path-independence; Respect For Improvements; Market Design; Mathematical Methods
Delacretaz, David, Scott Duke Kominers, and Alexandru Nichifor. "Comparative Statics for Size-Dependent Discounts in Matching Markets." Journal of Mathematical Economics 90 (October 2020): 127–131.
- September 2019
- Article
Optimizing Reserves in School Choice: A Dynamic Programming Approach
By: Franklyn Wang, Ravi Jagadeesan and Scott Duke Kominers
We introduce a new model of school choice with reserves in which a social planner is constrained by a limited supply of reserve seats and tries to find an optimal matching according to a social welfare function. We construct the optimal distribution of reserves via a... View Details
Wang, Franklyn, Ravi Jagadeesan, and Scott Duke Kominers. "Optimizing Reserves in School Choice: A Dynamic Programming Approach." Operations Research Letters 47, no. 5 (September 2019): 438–446.
- Article
Distributionally Robust Optimization and Its Tractable Approximations
By: Joel Goh and Melvyn Sim
In this paper we focus on a linear optimization problem with uncertainties, having expectations in the objective and in the set of constraints. We present a modular framework to obtain an approximate solution to the problem that is distributionally robust and more... View Details
Goh, Joel, and Melvyn Sim. "Distributionally Robust Optimization and Its Tractable Approximations." Operations Research 58, no. 4 (pt.1) (July–August 2010): 902–917.
- June 2007
- Tutorial
Congruence Model Tutorial
By: Christopher Marquis and Alison Comings
Utilizes Beer & Tushman's SMA: Microelectronic Products Division (A) case to explore O'Reilly and Tushman's congruence model. Participants learn about the model through a series of video presentations and become familar with the problems facing SMA through an... View Details
- spring 1973
- Article
A Stochastic Model for Auditing
By: Robert S. Kaplan
Kaplan, Robert S. "A Stochastic Model for Auditing." Journal of Accounting Research 11 (spring 1973): 38–46.
- September 1984
- Background Note
Marketing Research: An Overview of Research Methods
By: Robert J. Dolan
Broadly describes the scope of marketing research, and describes experiments, non-survey methods, and internal data. View Details
Dolan, Robert J. "Marketing Research: An Overview of Research Methods." Harvard Business School Background Note 585-039, September 1984.
- 2004
- Chapter
Paradoxes of Trust: Empirical and Theoretical Departures from a Traditional Model
By: J. Keith Murnighan, Deepak Malhotra and J. Mark Weber
Murnighan, J. Keith, Deepak Malhotra, and J. Mark Weber. "Paradoxes of Trust: Empirical and Theoretical Departures from a Traditional Model." In Trust and Distrust in Organizations: Dilemmas and Approaches, edited by Roderick Kramer and Karen Cook. New York: Russell Sage Foundation, 2004.
- 2023
- Working Paper
PRIMO: Private Regression in Multiple Outcomes
By: Seth Neel
We introduce a new differentially private regression setting we call Private Regression in Multiple Outcomes (PRIMO), inspired the common situation where a data analyst wants to perform a set of l regressions while preserving privacy, where the covariates... View Details
Neel, Seth. "PRIMO: Private Regression in Multiple Outcomes." Working Paper, March 2023.
- 2023
- Article
Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness
By: Suraj Srinivas, Sebastian Bordt and Himabindu Lakkaraju
One of the remarkable properties of robust computer vision models is that their input-gradients are often aligned with human perception, referred to in the literature as perceptually-aligned gradients (PAGs). Despite only being trained for classification, PAGs cause... View Details
Srinivas, Suraj, Sebastian Bordt, and Himabindu Lakkaraju. "Which Models Have Perceptually-Aligned Gradients? An Explanation via Off-Manifold Robustness." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- March 2020
- Article
Diagnosing Missing Always at Random in Multivariate Data
By: Iavor I. Bojinov, Natesh S. Pillai and Donald B. Rubin
Models for analyzing multivariate data sets with missing values require strong, often assessable, assumptions. The most common of these is that the mechanism that created the missing data is ignorable—a twofold assumption dependent on the mode of inference. The first... View Details
Keywords: Missing Data; Diagnostic Tools; Sensitivity Analysis; Hypothesis Testing; Missing At Random; Row Exchangeability; Analytics and Data Science; Mathematical Methods
Bojinov, Iavor I., Natesh S. Pillai, and Donald B. Rubin. "Diagnosing Missing Always at Random in Multivariate Data." Biometrika 107, no. 1 (March 2020): 246–253.
- June 2000
- Article
On the Regulatory Application of Efficiency Measures
The last decade has witnessed a change to more powerful incentive schemes and the adoption by a large number of regulators of some form of price cap regimes. The efficiency frontiers literature tackles the problem of measuring the X factor in a price cap regime... View Details
Ruzzier, Christian Alejandro. "On the Regulatory Application of Efficiency Measures." Utilities Policy 9, no. 2 (June 2000): 81–92. (with M. Rossi.)
- August 2001 (Revised July 2008)
- Technical Note
A Technical Note and Discussion on Real Estate Valuation (IBET): Back of the Envelope (BOE) on Bonhomme Place: A Case within a Case
By: Arthur I Segel
Discusses real estate valuation. Reviews "back of the envelope" valuation; real estate appraisal methods, including the income method; market comparables and replacement costs; and more complex computer modeling. Also discusses other variables that could influence... View Details
Segel, Arthur I. "A Technical Note and Discussion on Real Estate Valuation (IBET): Back of the Envelope (BOE) on Bonhomme Place: A Case within a Case." Harvard Business School Technical Note 802-025, August 2001. (Revised July 2008.)
- 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).
- June 2005 (Revised March 2006)
- Case
E Ink in 2005
By: David B. Yoffie and Barbara Mack
Explores the challenges of commercializing a bleeding-edge technology. After seven years, E Ink has spent more than $100 million to commercialize electronic ink. With business momentum picking up, but resources running out, the case examines the key trade-offs in... View Details
Keywords: Technological Innovation; Commercialization; Mathematical Methods; Consumer Products Industry; Technology Industry
Yoffie, David B., and Barbara Mack. "E Ink in 2005." Harvard Business School Case 705-506, June 2005. (Revised March 2006.)