Multi-task Learning - Publications - Faculty & Research

2024
Working Paper

Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization

By: Ta-Wei Huang, Eva Ascarza and Ayelet Israeli

This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details

Keywords: Heterogeneous Treatment Effect; Multi-task Learning; Representation Learning; Personalization; Promotion; Deep Learning; Field Experiments; Customer Focus and Relationships; Customization and Personalization

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Students on the Job Market - Doctoral

interventions. Unlike traditional multi-task learning methods that build separate models for each intervention, IRL uses a unified prediction model across past experiments to enhance generalizability. We... View Details

04 Nov 2010
What Do You Think?

Why Do We Chase Stars?

the time to learn their new company's management processes." Stephen Basikoti put it this way: "The fact that some transplanted leaders do not succeed does not negate the fact that management performance is portable; it simply... View Details

Keywords: by Jim Heskett

04 May 2020
Blog Post

6 Things You Should Know About the HBS/HKS Joint Degree

(MBA/MPP 2017) and Taniel Chan (MBA/MPP 2017) are invested in understanding how social change can be driven through public-private partnerships. Being the tremendous multi-taskers they are, they’re also eager to help prospective students... View Details

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Departments | Employment

accomplish our goals and juggle many activities at once. Attributes of Successful Staff Members Flexibility Ability to multi-task and appropriately prioritize Eagerness to learn Customer Orientation Good... View Details

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