Promises and Pitfalls of Threshold-based Auto-labeling

22 November 2022

Papers citing "Promises and Pitfalls of Threshold-based Auto-labeling"

5 / 5 papers shown

Title
Pearls from Pebbles: Improved Confidence Functions for Auto-labeling Harit Vishwakarma Reid Chen Chen Sui Jiet Tay Satya Sai Srinath Namburi Frederic Sala Ramya Korlakai Vinayak 40 2 0 24 Apr 2024
Active Statistical Inference Tijana Zrnic Emmanuel J. Candès 26 10 0 05 Mar 2024
Exponential Savings in Agnostic Active Learning through Abstention Nikita Puchkin Nikita Zhivotovskiy 24 20 0 31 Jan 2021
Improving model calibration with accuracy versus uncertainty optimization R. Krishnan Omesh Tickoo UQCV 188 157 0 14 Dec 2020
Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization Yingfan Wang Haiyang Huang Cynthia Rudin Yaron Shaposhnik 159 301 0 08 Dec 2020