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Show Results For
-
All HBS Web
(1,700)
- People (9)
- News (315)
- Research (1,021)
- Events (12)
- Multimedia (10)
- Faculty Publications (833)
- Aug 29 2019
- Testimonial
Exploring the Nature of Leadership
- Article
Fast Generalized Subset Scan for Anomalous Pattern Detection
By: Edward McFowland III, Skyler Speakman and Daniel B. Neill
We propose Fast Generalized Subset Scan (FGSS), a new method for detecting anomalous patterns in general categorical data sets. We frame the pattern detection problem as a search over subsets of data records and attributes, maximizing a nonparametric scan statistic...
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Keywords:
Pattern Detection;
Anomaly Detection;
Knowledge Discovery;
Bayesian Networks;
Scan Statistics;
Analytics and Data Science
McFowland III, Edward, Skyler Speakman, and Daniel B. Neill. "Fast Generalized Subset Scan for Anomalous Pattern Detection." Art. 12. Journal of Machine Learning Research 14 (2013): 1533–1561.
- 25 Aug 2017
- Blog Post
HBS Interns: Summer Takeovers
in technology at the Sephora Innovation Lab. Jenn researched the impacts of artificial intelligence on the retail industry and participated in idea hackathons to brainstorm creative new ways for the brand to innovate. Adam Behrens, View Details
Keywords:
All Industries
- November 28, 2017
- Editorial
Active Investing v.2.0
By: Gabriel Karageorgiou and George Serafeim
Keywords:
Investment;
Investing;
Technology;
Big Data;
Quantitative Analysis;
ESG;
ESG (Environmental, Social, Governance) Performance;
Sustainability;
Analytics and Data Science
Karageorgiou, Gabriel, and George Serafeim. "Active Investing v.2.0." Pensions & Investments (online) (November 28, 2017).
- Feb 21 2017
- Testimonial
Reaching the Next Level
- November 1996
- Article
Localized Autocorrelation Diagnostic Statistic for Sociological Models: Times-series, Network, and Spatial Datasets
By: C. I. Nass and Y. Moon
Nass, C. I., and Y. Moon. "Localized Autocorrelation Diagnostic Statistic for Sociological Models: Times-series, Network, and Spatial Datasets." Sociological Methods & Research 25, no. 2 (November 1996): 223–247.
- 01 Sep 2017
- News
@Soldiers Field
scuptures on loan to the School’s ongoing contemporary sculpture exhibition. The piece was inspired in part by an essay by Henry David Thoreau, who graduated from Harvard 180 summers ago. HBS will partner with Harvard’s SEAS and Department of Statistics to offer the...
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- Sep 07 2016
- Testimonial
Making an Impact on Your Organization
- Aug 25 2015
- Testimonial
Climbing the Mountain for a Clearer View
- June 2022 (Revised July 2022)
- Technical Note
Causal Inference
This note provides an overview of causal inference for an introductory data science course. First, the note discusses observational studies and confounding variables. Next the note describes how randomized experiments can be used to account for the effect of...
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Keywords:
Causal Inference;
Causality;
Experiment;
Experimental Design;
Data Science;
Analytics and Data Science
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Causal Inference." Harvard Business School Technical Note 622-111, June 2022. (Revised July 2022.)
- October 2017
- Case
Quantopian: A New Model for Active Management
Keywords:
Big Data;
Hedge Fund;
Crowdsourcing;
Investment Fund;
Quantitative Hedge Fun;
Algorithmic Data;
Analytics and Data Science
Fleiss, Sara, Adi Sunderam, Luis M. Viceira, and Caitlin Carmichael. "Quantopian: A New Model for Active Management." Harvard Business School Case 218-046, October 2017.
- Article
Selecting the Right Growth Metrics: Fewer but Better
Keywords:
Supply Chains;
Big Data;
Corporations;
Franchising;
Performance Metrics;
Analytics and Data Science
Schlesinger, Leonard A. "Selecting the Right Growth Metrics: Fewer but Better." Stanford Social Innovation Review (website) (April 21, 2017).
- Sep 23 2015
- Interview
Interview with Faculty Chair Frank Cespedes
- 06 Oct 2011
- What Do You Think?
How Will the ‘Moneyball Generation’ Influence Management?
Summing Up Should "Moneyball Analytics" Play a Greater Role in Preparation for Management? There was general agreement among respondents to this month's column that we will see a growing emphasis on analytics among managers as...
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Keywords:
by James Heskett
- 2022
- Article
Towards Robust Off-Policy Evaluation via Human Inputs
By: Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez and Himabindu Lakkaraju
Off-policy Evaluation (OPE) methods are crucial tools for evaluating policies in high-stakes domains such as healthcare, where direct deployment is often infeasible, unethical, or expensive. When deployment environments are expected to undergo changes (that is, dataset...
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Singh, Harvineet, Shalmali Joshi, Finale Doshi-Velez, and Himabindu Lakkaraju. "Towards Robust Off-Policy Evaluation via Human Inputs." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (2022): 686–699.
- 2021
- Working Paper
Time and the Value of Data
By: Ehsan Valavi, Joel Hestness, Newsha Ardalani and Marco Iansiti
Managers often believe that collecting more data will continually improve the accuracy of their machine learning models. However, we argue in this paper that when data lose relevance over time, it may be optimal to collect a limited amount of recent data instead of... View Details
Keywords:
Economics Of AI;
Machine Learning;
Non-stationarity;
Perishability;
Value Depreciation;
Analytics and Data Science;
Value
Valavi, Ehsan, Joel Hestness, Newsha Ardalani, and Marco Iansiti. "Time and the Value of Data." Harvard Business School Working Paper, No. 21-016, August 2020. (Revised November 2021.)
- 2020
- Working Paper
Machine Learning for Pattern Discovery in Management Research
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used as an observation for further inductive or abductive research, but should not be treated as the result of a...
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Keywords:
Machine Learning;
Theory Building;
Induction;
Decision Trees;
Random Forests;
K-nearest Neighbors;
Neural Network;
P-hacking;
Analytics and Data Science;
Analysis
Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres. "Machine Learning for Pattern Discovery in Management Research." Harvard Business School Working Paper, No. 19-032, September 2018. (Revised June 2020.)
- December 2016 (Revised December 2020)
- Course Overview Note
Big Data in Marketing
By: John Deighton and Mike Horia Teodorescu
Deighton, John, and Mike Horia Teodorescu. "Big Data in Marketing." Harvard Business School Course Overview Note 517-077, December 2016. (Revised December 2020.)
- March 1987
- Article
Using Survey Data to Test Standard Propositions Regarding Exchange Rate Expectations
By: J. Frankel and K. A. Froot
Keywords:
Currencies;
Exchange Rates;
Asset Pricing;
International Macroeconomics;
Monetary Policy;
Currency Controls;
Fixed Exchange Rates;
Floating Exchange Rates;
Currency Bands;
Currency Zones;
Currency Areas;
Rational Expectations;
Analytics and Data Science;
Finance
Frankel, J., and K. A. Froot. "Using Survey Data to Test Standard Propositions Regarding Exchange Rate Expectations." American Economic Review 77, no. 1 (March 1987): 133–153. (Revised from NBER Working Paper No. 1672.)
- February 1985 (Revised August 1985)
- Supplement
Computervision-Japan (C)
Presents sales data for 1983 and 1984.
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Moriarty, Rowland T., Jr. "Computervision-Japan (C)." Harvard Business School Supplement 585-157, February 1985. (Revised August 1985.)