activity
20202025
most citedImproving Classifier Confidence using Lossy Label-Invariant Transformations

2 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Quantifying and Improving Adaptivity in Conformal Prediction through Input Transformations

Sooyong Jang, Insup Lee

Conformal prediction constructs a set of labels instead of a single point prediction, while providing a probabilistic coverage guarantee. Beyond the coverage guarantee, adaptivenes…

cs.LG2025

Conformal Constrained Policy Optimization for Cost-Effective LLM Agents

Wenwen Si, Sooyong Jang, Insup Lee +1

While large language models (LLMs) have recently made tremendous progress towards solving challenging AI problems, they have done so at increasingly steep computational and API cos…

eess.IV2024

Fundus Image-based Visual Acuity Assessment with PAC-Guarantees

Sooyong Jang, Kuk Jin Jang, Hyonyoung Choi +4

Timely detection and treatment are essential for maintaining eye health. Visual acuity (VA), which measures the clarity of vision at a distance, is a crucial metric for managing ey…

cs.LG2021★ 2 cited

Confidence Calibration with Bounded Error Using Transformations

Sooyong Jang, Radoslav Ivanov, Insup Lee +1

As machine learning techniques become widely adopted in new domains, especially in safety-critical systems such as autonomous vehicles, it is crucial to provide accurate output unc…

cs.LG2020★ 2 cited

Improving Classifier Confidence using Lossy Label-Invariant Transformations

Sooyong Jang, Insup Lee, James Weimer

Providing reliable model uncertainty estimates is imperative to enabling robust decision making by autonomous agents and humans alike. While recently there have been significant ad…