Filter Results
:
(33)
Show Results For
-
All HBS Web
(951)
- Faculty Publications (33)
Show Results For
-
All HBS Web
(951)
- Faculty Publications (33)
←
Page 2 of
33
Results
- 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).
- Article
Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error
By: Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan and Edward McFowland III
Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving...
View Details
Keywords:
Autoencoder Networks;
Pattern Detection;
Subset Scanning;
Computer Vision;
Statistical Methods And Machine Learning;
Machine Learning;
Deep Learning;
Data Mining;
Big Data;
Large-scale Systems;
Mathematical Methods;
Analytics and Data Science
Cintas, Celia, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan, and Edward McFowland III. "Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error." Proceedings of the International Joint Conference on Artificial Intelligence 29th (2020).
- July 2019
- Teaching Note
AT&T, Retraining, and the Workforce of Tomorrow
By: William R. Kerr and Carl Kreitzberg
A Teaching Note for the "AT&T, Retraining, and the Workforce of Tomorrow" case study (HBS#820-017). The case describes how AT&T designed and implemented a program to retrain 100,000 of its workers. The case first reviews the technological forces that compelled AT&T to...
View Details
Keywords:
AT&T;
Workforce;
Future Of Work;
Telecommunications;
Unions;
Technological Change;
Layoffs;
MOOCS;
Strategic Planning;
Employees;
Training;
Labor;
Learning;
Labor Unions;
Technology Adoption;
Talent and Talent Management;
Transformation;
Telecommunications Industry;
Communications Industry;
United States
- July 2019 (Revised November 2019)
- Case
Osaro: Picking the Best Path
By: William R. Kerr, James Palano and Bastiane Huang
The founder of Osaro saw the potential of deep reinforcement learning to allow robots to be applied to new applications. Osaro targeted warehousing, already a dynamic industry for robotics and automation, for its initial product—a system which would allow robotic arms...
View Details
Keywords:
Artificial Intelligence;
Machine Learning;
Robotics;
Robots;
Ecommerce;
Fulfillment;
Warehousing;
AI;
Startup;
Technology Commercialization;
Business Startups;
Entrepreneurship;
Logistics;
Order Taking and Fulfillment;
Information Technology;
Commercialization;
Learning;
Complexity;
Competition;
E-commerce
Kerr, William R., James Palano, and Bastiane Huang. "Osaro: Picking the Best Path." Harvard Business School Case 820-012, July 2019. (Revised November 2019.)
- 2020
- Working Paper
Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach
By: Eva Ascarza
The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can...
View Details
Keywords:
Customer Management;
Targeting;
Deep Exponential Families;
Probabilistic Machine Learning;
Cold Start Problem;
Customer Relationship Management;
Customer Value and Value Chain;
Consumer Behavior;
Analytics and Data Science;
Mathematical Methods;
Retail Industry
Padilla, Nicolas, and Eva Ascarza. "Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach." Harvard Business School Working Paper, No. 19-091, February 2019. (Revised May 2020. Accepted at the Journal of Marketing Research.)
- September 2018 (Revised December 2019)
- Case
Zebra Medical Vision
By: Shane Greenstein and Sarah Gulick
An Israeli startup founded in 2014, Zebra Medical Vision developed algorithms that produced diagnoses from X-rays, mammograms, and CT-scans. The algorithms used deep learning and digitized radiology scans to create software that could assist doctors in making...
View Details
Keywords:
Radiology;
Machine Learning;
X-ray;
CT Scan;
Medical Technology;
Probability;
FDA 510(k);
Diagnosis;
Business Startups;
Health Care and Treatment;
Information Technology;
Applications and Software;
Competitive Strategy;
Product Development;
Commercialization;
Decision Choices and Conditions;
Health Industry;
Medical Devices and Supplies Industry;
Technology Industry;
Israel
Greenstein, Shane, and Sarah Gulick. "Zebra Medical Vision." Harvard Business School Case 619-014, September 2018. (Revised December 2019.)
- 2017
- Mimeo
Science for Society: Science and Technology Based Social Entrepreneurship
By: Tarun Khanna, Shashank Shah and Kundan Madireddy
This publication is an outcome of the team's research, engagement and interactions with over 25 science and technology-based social enterprises in India. It provides details on the research process, insightful outcomes and innovative impact.
Throughout the... View Details
Throughout the... View Details
Keywords:
Social Entrepreneurship;
Science-Based Business;
Information Technology;
Business and Community Relations;
India
Khanna, Tarun, Shashank Shah, and Kundan Madireddy. "Science for Society: Science and Technology Based Social Entrepreneurship." Harvard University South Asia Institute, 2017. Mimeo. (This publication is an outcome of a grant from the Tata Trusts.)
- February 2015 (Revised September 2016)
- Teaching Note
Making stickK Stick: The Business of Behavioral Economics
By: Leslie K. John and Michael Norton
Email mking@hbs.edu for a courtesy copy.
This Teaching Note explains the theory of the case and teaching plan for the case: Making sticK Stick: The Business of Behavioral Economics (514019). The case focuses on a... View Details
This Teaching Note explains the theory of the case and teaching plan for the case: Making sticK Stick: The Business of Behavioral Economics (514019). The case focuses on a... View Details
Keywords:
Behavioral Economics;
Behavior Change;
B2B Vs. B2C;
Human Resource Management;
Marketing Of Innovations;
Health & Wellness;
Weight Loss;
Charitable Giving;
Marketing;
Consumer Behavior;
Entrepreneurship;
Internet and the Web;
Health;
Business Model;
Sales;
Human Resources;
Health Industry;
United States
John, Leslie K., and Michael Norton. "Making stickK Stick: The Business of Behavioral Economics." Harvard Business School Teaching Note 515-088, February 2015. (Revised September 2016.) (Email mking@hbs.edu for a courtesy copy.)
- 12 Dec 2014
- Conference Presentation
Aspect Specific Sentiment Analysis Using Hierarchical Deep Learning
By: Himabindu Lakkaraju, Richard Socher and Chris Manning
Lakkaraju, Himabindu, Richard Socher, and Chris Manning. "Aspect Specific Sentiment Analysis Using Hierarchical Deep Learning." Paper presented at the 28th Annual Conference on Neural Information Processing Systems (NIPS), Workshop on Deep Learning and Representation Learning, Montreal, Canada, December 12, 2014.
- 2014
- Book
Managerial Accounting: Making Decisions and Motivating Performance
By: Srikant M. Datar and Madhav Rajan
Managerial Accounting: Making Decisions and Motivating Performance enables future managers and business owners to attain the core skills they need to become integral members of their company’s decision-making teams. This new program from established authors...
View Details
Datar, Srikant M., and Madhav Rajan. Managerial Accounting: Making Decisions and Motivating Performance. Prentice Hall, 2014.
- April 2011
- Article
Why Leaders Don't Learn from Success
By: Francesca Gino and Gary P. Pisano
We argue that for a variety of psychological reasons, it is often much harder for leaders and organizations to learn from success than to learn from failure. Success creates three kinds of traps that often impede deep learning. The first is attribution error or the...
View Details
Keywords:
Learning;
Innovation and Management;
Leadership;
Failure;
Success;
Performance Evaluation;
Prejudice and Bias
Gino, Francesca, and Gary P. Pisano. "Why Leaders Don't Learn from Success." Harvard Business Review 89, no. 4 (April 2011): 68–74.
- Research Summary
Innovating in Energy: Learning from High-Potential Ventures
My work at HBS has always focused on high-potential ventures. Most recently, these have been professionally financed start-ups and buyouts in newly emerging energy and cleantech businesses. These ventures tend to be based on innovative insights into technology and... View Details
- Teaching Interest
Interpretability and Explainability in Machine Learning
As machine learning models are increasingly being employed to aid decision makers in high-stakes settings such as healthcare and criminal justice, it is important to ensure that the decision makers correctly understand and consequent trust the functionality of these... View Details