Explanipedia

Predicting Language Models' Success at Zero-Shot Probabilistic Prediction Open

Kevin Ren, Santiago Cortes-Gomez, Carlos Andrés Carmona Patiño, Ananya Joshi, Ruiqi Lyu , et al. · 2025

Recent work has investigated the capabilities of large language models (LLMs) as zero-shot models for generating individual-level characteristics (e.g., to serve as risk models or augment survey datasets). However, when should a user have …

Soda taxes versus cup sizes when the retailer practices nonlinear pricing: An experiment Open

José G. Nuño‐Ledesma, Steven Y. Wu, Joseph Valdes Balagtas · 2025

Taxation and portion cap rules are alternative policies available to regulate the consumption of sugary drinks. We examine their impacts on consumer surplus and choice availability in an experimental market where sellers can practice secon…

Leveraging Model Guidance to Extract Training Data from Personalized Diffusion Models Open

Xiaoyu Wu, Jiaru Zhang, Steven Y. Wu · 2024

Diffusion Models (DMs) have become powerful image generation tools, especially for few-shot fine-tuning where a pretrained DM is fine-tuned on a small image set to capture specific styles or objects. Many people upload these personalized c…

Utility-Directed Conformal Prediction: A Decision-Aware Framework for Actionable Uncertainty Quantification Open

Santiago Cortes-Gomez, Carlos Andrés Carmona Patiño, Yewon Byun, Steven Y. Wu, Eric Horvitz , et al. · 2024

Interest has been growing in decision-focused machine learning methods which train models to account for how their predictions are used in downstream optimization problems. Doing so can often improve performance on subsequent decision prob…

Oracle-Efficient Differentially Private Learning with Public Data Open

Adam Block, Mark Bun, Rathin Desai, Abhishek Shetty, Steven Y. Wu · 2024

Due to statistical lower bounds on the learnability of many function classes under privacy constraints, there has been recent interest in leveraging public data to improve the performance of private learning algorithms. In this model, algo…

Taxing <span>sugar‐sweetened</span> beverages: A nonlinear pricing approach Open

José G. Nuño‐Ledesma, Steven Y. Wu, Joseph Valdes Balagtas · 2023

Taxation is frequently implemented to discourage the consumption of sugary beverages. Despite their popularity, little is known about the impacts of taxes when sellers practice price discrimination. To address this issue, we use a standard…

Biocompatibility and Biological Effects of Surface-Modified Conjugated Polymer Nanoparticles Open

Wanni Guo, Mingjian Chen, Yuxin Yang, Guili Ge, Le Tang , et al. · 2023

Semiconductiong polymer nanoparticles (Pdots) have a wide range of applications in biomedical fields including biomolecular probes, tumor imaging, and therapy. However, there are few systematic studies on the biological effects and biocomp…

How does a change in outside options affect relational contracting outcomes? Experimental evidence and implications for agricultural contracting Open

Jacob Brindley, James M. MacDonald, Steven Y. Wu · 2023

We use experiments, guided by theory, to examine how an exogenous decrease in the value of an agent's outside option (e.g., a proxy for a reduction in alternative contracting opportunities) affects relational contracting across two institu…

Nonlinear Pricing Under Regulation: Comparing Cap Rules and Taxes in the Laboratory Open

José G. Nuño Ledesma, Steven Y. Wu, Joseph Valdes Balagtas · 2022

Se reporta un experimento que contrasta los impactos de un impuesto y un límite de cantidad en un mercado con un solo producto y dos consumidores con preferencias privadas. Se discuten los efectos sobre la canasta de elección y el excedent…

A Sandbox Tool to Bias(Stress)-Test Fairness Algorithms Open

Nil-Jana Akpinar, Manish Nagireddy, Logan Stapleton, Hao-Fei Cheng, Haiyi Zhu , et al. · 2022

Motivated by the growing importance of reducing unfairness in ML predictions, Fair-ML researchers have presented an extensive suite of algorithmic 'fairness-enhancing' remedies. Most existing algorithms, however, are agnostic to the source…

The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective Open

Satyapriya Krishna, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari , et al. · 2022

As various post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to develop a deeper understanding of whether and when the explanations output by these methods …

Correction to: Putting relational contract theory to the test: experimental evidence Open

Nisvan Erkal, Steven Y. Wu, Brian E. Roe · 2021

A correction to this paper has been published: https://doi.org/10.1007/s10683-021-09712-z

Determinants of Relational Contract Performance: Experimental Evidence Open

Steven Y. Wu · 2021

This study examines the determinants of relational contractual performance using data from a series of laboratory experiments. There is currently limited empirical evidence on the determinants of contractual performance, which includes con…

New Oracle-Efficient Algorithms for Private Synthetic Data Release Open

Giuseppe Vietri, Steven Y. Wu, Mark Bun, Thomas Steinke, Grace Tian · 2020

We present three new algorithms for constructing differentially private synthetic data---a sanitized version of a sensitive dataset that approximately preserves the answers to a large collection of statistical queries. All three algorithms…

Accuracy First: Selecting a Differential Privacy Level for Accuracy-Constrained ERM Open

Steven Y. Wu, Aaron Roth, Katrina Ligett, Bo Waggoner, Seth Neel · 2019

Traditional approaches to differential privacy assume a fixed privacy requirement ε for a computation, and attempt to maximize the accuracy of the computation subject to the privacy constraint. As differential privacy is increasingly deplo…

Oracle Efficient Private Non-Convex Optimization Open

Seth Neel, Aaron Roth, Giuseppe Vietri, Steven Y. Wu · 2019

One of the most effective algorithms for differentially private learning and optimization is objective perturbation. This technique augments a given optimization problem (e.g. deriving from an ERM problem) with a random linear term, and th…

An Analysis of Beverage Size Restrictions Open

Brian A. Bourquard, Steven Y. Wu · 2019

Due to high levels of obesity, various government interventions have been proposed to curb the consumption of sugar‐sweetened beverages (SSBs). The New York City “soda ban,” which proposed to limit the size of SSBs is among the most well‐k…

An Analysis of Beverage Size Restrictions Open

Brian Bourquard, Steven Y. Wu · 2019

An Analysis of Beverage Size Restrictions Open

Brian A. Bourquard, Steven Y. Wu · 2019

Due to high levels of obesity, various government interventions have been proposed to curb the consumption of sugar-sweetened beverages (SSBs). The New York City "soda-ban," which proposed to limit the size of SSBs is among the most well-k…

Modeling offensive player movement in professional basketball Open

Steven Y. Wu, Luke Bornn · 2017

The 2013 arrival of SportVU player tracking data in all NBA arenas introduced an overwhelming amount of on-court information - information which the league is still learning how to maximize for insights into player performance and basketba…

Modeling offensive player movement in professional basketball Open

Steven Y. Wu, Luke Bornn · 2017

The 2013 arrival of SportVU player tracking data in all NBA arenas introduced an overwhelming amount of on-court information - information which the league is still learning how to maximize for insights into player performance and basketba…

Strategic Uncertainty and Counter-Party Risk (Keynote) Open

Steven Y. Wu · 2017

An Economic Analysis of Beverage Size Restrictions Open

Brian A. Bourquard, Steven Y. Wu · 2016

We model the potential efficiency and distributional consequences of a government beverage-size restriction that is designed to curb or reduce consumption of sugar-sweetened beverages. Unsurprisingly, we find that a credibly implemented re…

Effects of “Fat Taxes” on Package Sizes, and Welfare Distribution Open

Joseph Valdes Balagtas, José G. Nuño‐Ledesma, Steven Y. Wu · 2016

We analytically study the pricing strategies a food retailer can execute under taxation when there is adverse selection. The questions are: how does the implementation of a tax regime affect the seller's ability to screen the market, and w…

Producer Protection Legislation and Termination Damages in the Presence of Contracting Frictions Open

Steven Y. Wu · 2015

This study models producer protection legislation that would grant growers the right to claim damages (PPLD) if their contracts are prematurely terminated. In the absence of contracting frictions that prevent contractors from redesigning c…

Economics of Agricultural Contract Grower Protection Legislation Open

Steven Y. Wu, James M. MacDonald · 2015

Contract production has been controversial in the livestock, meat, and poultry sectors, with many farm activists alleging that the market power held by large processors combined with the use of contracts can be exploitive of growers. For e…

Steven Y. Wu YOU? Author Swipe