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  • All HBS Web  (101)
    • Faculty Publications  (15)

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    • All HBS Web  (101)
      • Faculty Publications  (15)

      Explanation Methods Remove Explanation Methods →

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      • 2022
      • Article

      Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis.

      By: Martin Pawelczyk, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay and Himabindu Lakkaraju
      As machine learning (ML) models become more widely deployed in high-stakes applications, counterfactual explanations have emerged as key tools for providing actionable model explanations in practice. Despite the growing popularity of counterfactual explanations, a...  View Details
      Keywords: Machine Learning Models; Counterfactual Explanations; Adversarial Examples; Mathematical Methods
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      Pawelczyk, Martin, Chirag Agarwal, Shalmali Joshi, Sohini Upadhyay, and Himabindu Lakkaraju. "Exploring Counterfactual Explanations Through the Lens of Adversarial Examples: A Theoretical and Empirical Analysis." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 25th (2022).
      • 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
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      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

      Counterfactual Explanations Can Be Manipulated

      By: Dylan Slack, Sophie Hilgard, Himabindu Lakkaraju and Sameer Singh
      Counterfactual explanations are useful for both generating recourse and auditing fairness between groups. We seek to understand whether adversaries can manipulate counterfactual explanations in an algorithmic recourse setting: if counterfactual explanations indicate...  View Details
      Keywords: Machine Learning Models; Counterfactual Explanations
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      Slack, Dylan, Sophie Hilgard, Himabindu Lakkaraju, and Sameer Singh. "Counterfactual Explanations Can Be Manipulated." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
      • Article

      Reliable Post hoc Explanations: Modeling Uncertainty in Explainability

      By: Dylan Slack, Sophie Hilgard, Sameer Singh and Himabindu Lakkaraju
      As black box explanations are increasingly being employed to establish model credibility in high stakes settings, it is important to ensure that these explanations are accurate and reliable. However, prior work demonstrates that explanations generated by...  View Details
      Keywords: Black Box Explanations; Bayesian Modeling; Decision Making; Risk and Uncertainty; Information Technology
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      Slack, Dylan, Sophie Hilgard, Sameer Singh, and Himabindu Lakkaraju. "Reliable Post hoc Explanations: Modeling Uncertainty in Explainability." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
      • Article

      Learning Models for Actionable Recourse

      By: Alexis Ross, Himabindu Lakkaraju and Osbert Bastani
      As machine learning models are increasingly deployed in high-stakes domains such as legal and financial decision-making, there has been growing interest in post-hoc methods for generating counterfactual explanations. Such explanations provide individuals adversely...  View Details
      Keywords: Machine Learning Models; Recourse; Algorithm; Mathematical Methods
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      Ross, Alexis, Himabindu Lakkaraju, and Osbert Bastani. "Learning Models for Actionable Recourse." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
      • Article

      Towards the Unification and Robustness of Perturbation and Gradient Based Explanations

      By: Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu and Himabindu Lakkaraju
      As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a post hoc manner. In this work, we analyze two...  View Details
      Keywords: Machine Learning; Black Box Explanations; Decision Making; Forecasting and Prediction; Information Technology
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      Agarwal, Sushant, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, and Himabindu Lakkaraju. "Towards the Unification and Robustness of Perturbation and Gradient Based Explanations." Proceedings of the International Conference on Machine Learning (ICML) 38th (2021).
      • 2022
      • Working Paper

      Inattentive Inference

      By: Thomas Graeber
      This paper studies how people infer a state of the world from information structures that include additional, payoff-irrelevant states. For example, learning someone’s effort from their observable performance may require accounting for the otherwise irrelevant role of...  View Details
      Keywords: Belief Formation; Attention; Bounded Rationality; Values and Beliefs; Information; Mathematical Methods
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      Graeber, Thomas. "Inattentive Inference." Working Paper, January 2022. (R&R at Journal of the European Economic Association.)
      • 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
      Keywords: Predictive Models; Decision Making; Framework; Mathematical Methods
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      Rawal, Kaivalya, and Himabindu Lakkaraju. "Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses." Advances in Neural Information Processing Systems (NeurIPS) 33 (2020).
      • Article

      The Unprecedented Stock Market Reaction to COVID-19

      By: Scott Baker, Nicholas Bloom, Steven J. Davis, Kyle Kost, Marco Sammon and Tasaneeya Viratyosin
      No previous infectious disease outbreak, including the Spanish Flu, has impacted the stock market as forcefully as the COVID-19 pandemic. In fact, previous pandemics left only mild traces on the U.S. stock market. We use text-based methods to develop these points with...  View Details
      Keywords: COVID-19; Stock Market; Health Pandemics; Governance; Policy; Financial Markets
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      Baker, Scott, Nicholas Bloom, Steven J. Davis, Kyle Kost, Marco Sammon, and Tasaneeya Viratyosin. "The Unprecedented Stock Market Reaction to COVID-19." Review of Asset Pricing Studies 10, no. 4 (December 2020): 742–758.
      • June 2020
      • Article

      Parallel Play: Startups, Nascent Markets, and the Effective Design of a Business Model

      By: Rory McDonald and Kathleen Eisenhardt
      Prior research advances several explanations for entrepreneurial success in nascent markets but leaves a key imperative unexplored: the business model. By studying five ventures in the same nascent market, we develop a novel theoretical framework for understanding how...  View Details
      Keywords: Search; Legitimacy; Organizational Innovation; Organizational Learning; Mechanisms And Processes; Institutional Entrepreneurship; Qualitative Methods; Business Model Design; Business Model; Business Startups; Entrepreneurship; Emerging Markets; Adaptation; Competition; Strategy
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      McDonald, Rory, and Kathleen Eisenhardt. "Parallel Play: Startups, Nascent Markets, and the Effective Design of a Business Model." Administrative Science Quarterly 65, no. 2 (June 2020): 483–523.
      • Article

      History-informed Strategy Research: The Promise of History and Historical Research Methods in Advancing Strategy Scholarship

      By: Nicholas Argyres, Alfredo De Massis, Nicolai J. Foss, Federico Frattini, Geoffrey Jones and Brian Silverman
      Recent years have seen an increasing interest in the use of history and historical research methods in strategy research. This article discusses how and why history and historical research methods can enrich theoretical explanations of strategy phenomena. The article...  View Details
      Keywords: Methodology; Strategy; Business History; Research; History
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      Argyres, Nicholas, Alfredo De Massis, Nicolai J. Foss, Federico Frattini, Geoffrey Jones, and Brian Silverman. "History-informed Strategy Research: The Promise of History and Historical Research Methods in Advancing Strategy Scholarship." Strategic Management Journal 41, no. 3 (March 2020): 343–368.
      • May 2018
      • Article

      Selection and Market Reallocation: Productivity Gains from Multinational Production

      By: Laura Alfaro and Maggie X. Chen
      Assessing the productivity gains from multinational production has been a vital topic of economic research and policy debate. Positive aggregate productivity gains are often attributed to within-firm productivity improvement; however, an alternative, less emphasized...  View Details
      Keywords: Productivity Gains; Multinational Production; Selection; Market Reallocation; And Within-firm Productivity; Multinational Firms and Management; Production; Performance Productivity; Competition; Mathematical Methods
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      Alfaro, Laura, and Maggie X. Chen. "Selection and Market Reallocation: Productivity Gains from Multinational Production." American Economic Journal: Economic Policy 10, no. 2 (May 2018): 1–38. (Also NBER Working Paper 18207. See Harvard Business School Working Paper, No. 12–111, 2015 for longer version.)
      • July 2006
      • Article

      Bringing History (Back) into International Business

      By: G. Jones and Tarun Khanna
      We argue that the field of international business should evolve its rhetoric from the relatively uncontroversial idea that 'history matters' to exploring how it matters. We discuss four conceptual channels through which history matters, illustrating each with a major...  View Details
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      Jones, G., and Tarun Khanna. "Bringing History (Back) into International Business." Journal of International Business Studies 37, no. 4 (July 2006): 453–468.
      • November 1993 (Revised July 1994)
      • Background Note

      Adjusted Present Value Method for Capital Assets, The

      By: Steven R. Fenster and Stuart C. Gilson
      This case provides an explanation of the adjusted present value method for valuing capital assets. The authors believe this approach is generally simple and better for the complicated and changing capital structure found in restructuring.  View Details
      Keywords: Value; Capital; Assets
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      Fenster, Steven R., and Stuart C. Gilson. "Adjusted Present Value Method for Capital Assets, The ." Harvard Business School Background Note 294-047, November 1993. (Revised July 1994.)
      • July 1987 (Revised October 2009)
      • Background Note

      A Method For Valuing High-Risk, Long-Term Investments: The "Venture Capital Method"

      By: William A. Sahlman and Daniel R Scherlis
      Describes a method for valuing high-risk, long-term investments such as those confronting venture capitalists. The method entails forecasting a future value (e.g., five years from the present) and discounting that terminal value back to the present by applying a high...  View Details
      Keywords: Forecasting and Prediction; Entrepreneurship; Venture Capital; Investment; Risk Management; Valuation
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      Sahlman, William A., and Daniel R Scherlis. A Method For Valuing High-Risk, Long-Term Investments: The "Venture Capital Method". Harvard Business School Background Note 288-006, July 1987. (Revised October 2009.)
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