Detecting and Correcting for Label Shift with Black Box Predictors

12 February 2018

Papers citing "Detecting and Correcting for Label Shift with Black Box Predictors"

8 / 8 papers shown

Title
Understand the Effect of Importance Weighting in Deep Learning on Dataset Shift Thien Nhan Vo Thanh Xuan Truong 41 0 0 06 May 2025
Adapting to Online Distribution Shifts in Deep Learning: A Black-Box Approach Dheeraj Baby Boran Han Shuai Zhang Cuixiong Hu Yuyang Wang Yu Wang OOD 66 1 0 09 Apr 2025
Structural Alignment Improves Graph Test-Time Adaptation Hans Hao-Hsun Hsu Shikun Liu Han Zhao Pan Li OOD TTA 177 0 0 25 Feb 2025
Fractal Calibration for long-tailed object detection Konstantinos Panagiotis Alexandridis Ismail Elezi Jiankang Deng Anh H. Nguyen Shan Luo 353 0 0 15 Oct 2024
In-Situ Fine-Tuning of Wildlife Models in IoT-Enabled Camera Traps for Efficient Adaptation Mohammad Mehdi Rastikerdar Jin Huang Hui Guan Deepak Ganesan 76 0 0 12 Sep 2024
Positive and Unlabeled Data: Model, Estimation, Inference, and Classification Siyan Liu Chi-Kuang Yeh Xin Zhang Qinglong Tian Pengfei Li 41 0 0 13 Jul 2024
Learning the Distribution Map in Reverse Causal Performative Prediction Daniele Bracale Subha Maity Moulinath Banerjee Yuekai Sun 68 3 0 24 May 2024
On Causal and Anticausal Learning Bernhard Schölkopf Dominik Janzing J. Peters Eleni Sgouritsa Kun Zhang Joris Mooij CML 59 604 0 27 Jun 2012