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Show Results For
- All HBS Web
(17,375)
- People (16)
- News (4,436)
- Research (8,900)
- Events (88)
- Multimedia (85)
- Faculty Publications (7,322)
- 04 May 2017
- News
Going the Distance
adding an African proverb he quotes often. "If you want to go fast, go alone. I if you want to go far, go together." Become comfortable being uncomfortable. “High adventure requires that you make decisions without all the information you... View Details
Keywords: Jill Radsken
- August 2013
- Technical Note
Raising the Level of Abstraction
By: Willy Shih
This technical note discusses abstraction as a way of generalizing a process or component for wider application. By hiding complexity inside a module, abstraction enables system designers to think at a higher level. This lowers entry barriers to using (and reusing) a... View Details
Keywords: Abstraction; Modularity; Commercialization; Information Technology; Information Infrastructure; Information Technology; Applications and Software; Digital Platforms; United States; Asia; Europe
Shih, Willy. "Raising the Level of Abstraction." Harvard Business School Technical Note 614-019, August 2013.
- April 2022
- Teaching Note
Transforming BlackBerry: From Smartphones to Software
By: Ranjay Gulati and Eppa Rixey
Teaching Note for HBS Case No. 421-052. View Details
- 01 Sep 2017
- News
@Soldiers Field
In June, 90 young leaders from nine US cities convened for three days of case discussions focused on cross-sector collaborative efforts to improve workforce skills, education, infrastructure, and entrepreneurship in their home region. This is the third year that... View Details
- 14 Jan 2010
- Working Paper Summaries
Optimal Auction Design and Equilibrium Selection in Sponsored Search Auctions
Keywords: by Benjamin G. Edelman & Michael Schwarz
- Teaching Interest
Technology and Operations Management - MBA Required Curriculum
This course enables students to develop the skills and concepts needed to ensure the ongoing contribution of a firm's... View Details
- June 2024 (Revised August 2024)
- Technical Note
Web3 Business Model Design for Entrepreneurs
By: Shikhar Ghosh and Liang Wu
Ghosh, Shikhar, and Liang Wu. "Web3 Business Model Design for Entrepreneurs." Harvard Business School Technical Note 824-177, June 2024. (Revised August 2024.)
- 2024
- Conference Paper
Quantifying Uncertainty in Natural Language Explanations of Large Language Models
By: Himabindu Lakkaraju, Sree Harsha Tanneru and Chirag Agarwal
Large Language Models (LLMs) are increasingly used as powerful tools for several
high-stakes natural language processing (NLP) applications. Recent prompting
works claim to elicit intermediate reasoning steps and key tokens that serve as
proxy explanations for LLM... View Details
Lakkaraju, Himabindu, Sree Harsha Tanneru, and Chirag Agarwal. "Quantifying Uncertainty in Natural Language Explanations of Large Language Models." Paper presented at the Society for Artificial Intelligence and Statistics, 2024.
- 15 Apr 2023
- Conference Presentation
Autonomous Systems
By: Hise O. Gibson, Rob Wittman, Brandon Tseng, Nini Hamrick and Tim Booher
Autonomous systems have been on the front lines and front pages in the war in Ukraine, yet there are many unanswered questions regarding their future role and capabilities. Currently, these systems are employed in myriad use cases in logistics, intelligence, and... View Details
- 2023
- Article
Evaluating Explainability for Graph Neural Networks
By: Chirag Agarwal, Owen Queen, Himabindu Lakkaraju and Marinka Zitnik
As explanations are increasingly used to understand the behavior of graph neural networks (GNNs), evaluating the quality and reliability of GNN explanations is crucial. However, assessing the quality of GNN explanations is challenging as existing graph datasets have no... View Details
Keywords: Analytics and Data Science
Agarwal, Chirag, Owen Queen, Himabindu Lakkaraju, and Marinka Zitnik. "Evaluating Explainability for Graph Neural Networks." Art. 114. Scientific Data 10 (2023).
- 2022
- Article
Efficiently Training Low-Curvature Neural Networks
By: Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju and Francois Fleuret
Standard deep neural networks often have excess non-linearity, making them susceptible to issues such as low adversarial robustness and gradient instability. Common methods to address these downstream issues, such as adversarial training, are expensive and often... View Details
Keywords: AI and Machine Learning
Srinivas, Suraj, Kyle Matoba, Himabindu Lakkaraju, and Francois Fleuret. "Efficiently Training Low-Curvature Neural Networks." Advances in Neural Information Processing Systems (NeurIPS) (2022).
- Article
Adaptive Machine Unlearning
By: Varun Gupta, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi and Chris Waites
Data deletion algorithms aim to remove the influence of deleted data points from trained models at a cheaper computational cost than fully retraining those models. However, for sequences of deletions, most prior work in the non-convex setting gives valid guarantees... View Details
Gupta, Varun, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, and Chris Waites. "Adaptive Machine Unlearning." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- 2021
- Article
ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation
By: Chuang Gan, Jeremy Schwartz, Seth Alter, Damian Mrowca, Martin Schrimpf, James Traer, Julian De Freitas, Jonas Kubilius, Abhishek Bhandwaldar, Nick Haber, Megumi Sano, Kuno Kim, Elias Wang, Michael Lingelbach, Aidan Curtis, Kevin Feigelis, Daniel M. Bear, Dan Gutfreund, David Cox, Antonio Torralba, James J. DiCarlo, Joshua B. Tenenbaum, Josh H. McDermott and Daniel L.K. Yamins
We introduce ThreeDWorld (TDW), a platform for interactive multi-modal physical simulation. TDW enables simulation of high-fidelity sensory data and physical interactions between mobile agents and objects in rich 3D environments. Unique properties include: real-time... View Details
Keywords: Artificial Intelligence; Platform; Interactive Physical Simulation; Virtual Environment; Multi-modal; AI and Machine Learning
Gan, Chuang, Jeremy Schwartz, Seth Alter, Damian Mrowca, Martin Schrimpf, James Traer, Julian De Freitas, Jonas Kubilius, Abhishek Bhandwaldar, Nick Haber, Megumi Sano, Kuno Kim, Elias Wang, Michael Lingelbach, Aidan Curtis, Kevin Feigelis, Daniel M. Bear, Dan Gutfreund, David Cox, Antonio Torralba, James J. DiCarlo, Joshua B. Tenenbaum, Josh H. McDermott, and Daniel L.K. Yamins. "ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 35th (2021).
- 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).
- January 2021
- Article
Machine Learning for Pattern Discovery in Management Research
By: Prithwiraj Choudhury, Ryan Allen and Michael G. Endres
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used for exploratory inductive or abductive research, or for post-hoc analysis of regression results to detect... View Details
Keywords: Machine Learning; Supervised Machine Learning; Induction; Abduction; Exploratory Data Analysis; Pattern Discovery; Decision Trees; Random Forests; Neural Networks; ROC Curve; Confusion Matrix; Partial Dependence Plots; AI and Machine Learning
Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres. "Machine Learning for Pattern Discovery in Management Research." Strategic Management Journal 42, no. 1 (January 2021): 30–57.
- December 2018 (Revised March 2021)
- Background Note
Modern Automation (A): Artificial Intelligence
By: William R. Kerr and James Palano
This primer is meant to be a field guide to the late 2010s' surge in business use of "Artificial Intelligence" (AI), or enterprise software based in machine learning. First, it provides an overview of the key trends—digitization, connectivity, the continuation of... View Details
Keywords: Artificial Intelligence; Digitization; Connectivity; Computing; Future Of Work; Automation; AI and Machine Learning
Kerr, William R., and James Palano. "Modern Automation (A): Artificial Intelligence." Harvard Business School Background Note 819-084, December 2018. (Revised March 2021.)
- July 2015 (Revised August 2015)
- Teaching Note
Resuscitating Monitter
By: Benjamin Edelman and Wei Sun
Supplements 915027. View Details
- July 1995 (Revised September 1995)
- Background Note
Technology for Teams
By: Lynda M. Applegate and Geoffrey Bock
The importance of groups in organizations has long been recognized but, until recently, groups were always "tacked onto" organizations that were designed around individuals. It was not just the logic of classical organizational theory that perpetuated this focus on the... View Details
Applegate, Lynda M., and Geoffrey Bock. "Technology for Teams." Harvard Business School Background Note 196-008, July 1995. (Revised September 1995.)
- June 1995 (Revised August 1995)
- Background Note
Managing IT in the 1990s: Communications Technology
By: Lynda M. Applegate and Geoffrey Bock
Provides an overview of the basic technologies that comprise the communications infrastructure of a firm. Network architecture, wide area networks, local area networks, communication media, network protocols, and basic principles of data transmission over networks are... View Details
Applegate, Lynda M., and Geoffrey Bock. "Managing IT in the 1990s: Communications Technology." Harvard Business School Background Note 195-270, June 1995. (Revised August 1995.)
- December 1994
- Background Note
Note on Estimating the Value of the "IT Asset" Part II
By: Richard L. Nolan
Nolan, Richard L. Note on Estimating the Value of the "IT Asset" Part II. Harvard Business School Background Note 195-199, December 1994.