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Publications

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  • All HBS Web  (5)
    • Research  (5)
  • Faculty Publications  (3)

Show Results For

  • All HBS Web  (5)
    • Research  (5)
  • Faculty Publications  (3)
Page 1 of 5 Results
  • Article

Oracle Efficient Private Non-Convex Optimization

By: Seth Neel, Aaron Leon Roth, Giuseppe Vietri and Zhiwei Steven Wu
One of the most effective algorithms for differentially private learning and optimization is objective perturbation. This technique augments a given optimization problem (e.g. deriving from an ERM problem) with a random linear term, and then exactly solves it.... View Details
Keywords: Machine Learning; Algorithms; Objective Perturbation; Mathematical Methods
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Neel, Seth, Aaron Leon Roth, Giuseppe Vietri, and Zhiwei Steven Wu. "Oracle Efficient Private Non-Convex Optimization." Proceedings of the International Conference on Machine Learning (ICML) 37th (2020).
  • Article

Robust and Stable Black Box Explanations

By: Himabindu Lakkaraju, Nino Arsov and Osbert Bastani
As machine learning black boxes are increasingly being deployed in real-world applications, there has been a growing interest in developing post hoc explanations that summarize the behaviors of these black boxes. However, existing algorithms for generating such... View Details
Keywords: Machine Learning; Black Box Models; Framework
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Lakkaraju, Himabindu, Nino Arsov, and Osbert Bastani. "Robust and Stable Black Box Explanations." Proceedings of the International Conference on Machine Learning (ICML) 37th (2020): 5628–5638. (Published in PMLR, Vol. 119.)
  • 2023
  • Article

Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse

By: Martin Pawelczyk, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci and Himabindu Lakkaraju
As machine learning models are increasingly being employed to make consequential decisions in real-world settings, it becomes critical to ensure that individuals who are adversely impacted (e.g., loan denied) by the predictions of these models are provided with a means... View Details
Keywords: AI and Machine Learning; Decision Choices and Conditions; Mathematical Methods
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Pawelczyk, Martin, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci, and Himabindu Lakkaraju. "Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse." Proceedings of the International Conference on Learning Representations (ICLR) (2023).
  • 14 Sep 2010
  • First Look

First Look: September 14, 2010

experience suggests it may take several years. Download the paper: http://www.hbs.edu/research/pdf/11-020.pdf   Working PapersWellsprings of Creation: How Perturbation Sustains Exploration in Mature Organizations Authors:David James... View Details
Keywords: Sean Silverthorne
  • 05 Aug 2008
  • First Look

First Look: August 5, 2008

  Working PapersWellsprings of Creation: Perturbation and the Paradox of the Highly Disciplined Organization Authors:David James Brunner, Bradley R. Staats, Michael L. Tushman, and David M. Upton Abstract Organizations face simultaneous... View Details
Keywords: Martha Lagace
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