Tutorials

Recht, Ben; Johari, Ramesh

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https://hdl.handle.net/2142/130247 Copy

Description

Title

Tutorials

Author(s)

• Recht, Ben
• Johari, Ramesh

Issue Date

2025-09-17

Keyword(s)

• Front matter
• Tutorials

Abstract

TUTORIAL 1 (RECHT): “Statistics When n Equals 1”: Statistical decision-making draws general inferences about people from studies of populations, but such population inferences tell us little about what to do with any particular person. In this tutorial, I’ll try to answer the apparently oxymoronic question of what it means to do statistics when n equals 1. Throughout, I aim to highlight the role of mathematical and qualitative theory in our understanding, treating, and optimizing individual outcomes. I’ll first present a review of the basics of statistical decision making based on actuarial methods and randomized trials from the perspective of signal processing. From this statistical foundation, I’ll turn to individuals. With a focus on clinical practice, I’ll review the systems-level view of health based on Walter Cannon’s notion of homeostasis. Cannon conceived of the body as a control system—a complex dynamical system actively working to maintain itself in a stable state despite adversarial engagement with an uncertain and hazardous environment. I’ll present Cannon’s concepts through a contemporary lens, drawing on ideas from feedback control that illuminate the necessary architectures for homeostasis. Identifying these patterns can guide positive interventions that can steer dysregulated systems back to stable behavior. That is, a homeostatic view can help us envision experimentation where an individual is simultaneously the treatment and the control group. TUTORIAL 2 (JOHARI): “Experimentation, Interference, and Capacity Constraints: Recent Results and Future Directions”: Two-sided marketplace platforms often run experiments to test the effect of an intervention before launching it platform-wide. However, estimates of the treatment effect obtained in these experiments can be biased, due to interference arising from marketplace competition: e.g., when buyers are randomized to treatment and control, they compete for the same limited supply. The resulting biases can impact the platform’s ability to make data-driven decisions. In this tutorial, we survey recent results on this problem. A central theme of the tutorial will be to illustrate that the “state” of the system as measured by available capacity (i.e., inventory) provides a natural modeling device to study the impact of interference. This observation allows us to naturally study experimental design and interference using the tools of stochastic modeling. The talk will use this approach to describe the impact of interference on estimation bias and subsequent decision-making; examples and applications; some proposed solutions; and open directions for future work.

Publisher

Allerton Conference on Communication, Control, and Computing

Series/Report Name or Number

2025 61st Allerton Conference on Communication, Control, and Computing Proceedings

ISSN

2836-4503

Type of Resource

Text

Genre of Resource

Other

Language

eng

Handle URL

https://hdl.handle.net/2142/130247&&

Copyright and License Information

Copyright 2025 is held by Benjamin Recht and Ramesh Johari.

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