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Learning to Predict Trustworthiness with Steep Slope Loss

Learning to Predict Trustworthiness with Steep Slope Loss

30 September 2021

Mohan S. Kankanhalli

Papers citing "Learning to Predict Trustworthiness with Steep Slope Loss"

12 / 12 papers shown

Title
Unveiling AI's Blind Spots: An Oracle for In-Domain, Out-of-Domain, and Adversarial Errors Shuangpeng Han Mengmi Zhang 367 0 0 03 Oct 2024
M2m: Imbalanced Classification via Major-to-minor Translation Jaehyung Kim Jongheon Jeong Jinwoo Shin 92 224 0 01 Apr 2020
Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss Kaidi Cao Colin Wei Adrien Gaidon Nikos Arechiga Tengyu Ma 127 1,602 0 18 Jun 2019
Functional Adversarial Attacks Cassidy Laidlaw Soheil Feizi AAML 72 185 0 29 May 2019
Dynamic Curriculum Learning for Imbalanced Data Classification Yiru Wang Weihao Gan Jie Yang Wei Wu Junjie Yan 70 222 0 21 Jan 2019
To Trust Or Not To Trust A Classifier Heinrich Jiang Been Kim Melody Y. Guan Maya R. Gupta UQCV 176 472 0 30 May 2018
Selective Classification for Deep Neural Networks Yonatan Geifman Ran El-Yaniv CVBM 95 527 0 23 May 2017
Large-Margin Softmax Loss for Convolutional Neural Networks Weiyang Liu Yandong Wen Zhiding Yu Meng Yang CVBM 81 1,456 0 07 Dec 2016
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 158 3,454 0 07 Oct 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 821 9,318 0 06 Jun 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 277 19,066 0 20 Dec 2014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images Anh Totti Nguyen J. Yosinski Jeff Clune AAML 169 3,271 0 05 Dec 2014

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