Are All Training Examples Created Equal? An Empirical Study

30 November 2018

Papers citing "Are All Training Examples Created Equal? An Empirical Study"

12 / 12 papers shown

Title
On the Importance of Large Objects in CNN Based Object Detection Algorithms Ahmed Ben Saad Gabriele Facciolo Axel Davy ObjD 27 2 0 20 Nov 2023
Towards a statistical theory of data selection under weak supervision Germain Kolossov Andrea Montanari Pulkit Tandon 21 14 0 25 Sep 2023
Improving Data Quality with Training Dynamics of Gradient Boosting Decision Trees M. Ponti L. Oliveira Mathias Esteban Valentina Garcia J. Román Luis Argerich TDI 30 4 0 20 Oct 2022
How Low Can We Go? Pixel Annotation for Semantic Segmentation Daniel Kigli Ariel Shamir S. Avidan VLM 21 1 0 25 Jan 2022
One Backward from Ten Forward, Subsampling for Large-Scale Deep Learning Chaosheng Dong Xiaojie Jin Weihao Gao Yijia Wang Hongyi Zhang Xiang Wu Jianchao Yang Xiaobing Liu 28 5 0 27 Apr 2021
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics Swabha Swayamdipta Roy Schwartz Nicholas Lourie Yizhong Wang Hannaneh Hajishirzi Noah A. Smith Yejin Choi 44 429 0 22 Sep 2020
DEAL: Deep Evidential Active Learning for Image Classification Patrick Hemmer Niklas Kühl Jakob Schöffer 33 37 0 22 Jul 2020
Impact of base dataset design on few-shot image classification Othman Sbai Camille Couprie Mathieu Aubry VLM 15 22 0 17 Jul 2020
Adversarial Filters of Dataset Biases Ronan Le Bras Swabha Swayamdipta Chandra Bhagavatula Rowan Zellers Matthew E. Peters Ashish Sabharwal Yejin Choi 36 220 0 10 Feb 2020
Sampling Bias in Deep Active Classification: An Empirical Study Ameya Prabhu Charles Dognin M. Singh 16 64 0 20 Sep 2019
Imbalance Problems in Object Detection: A Review Kemal Oksuz Baris Can Cam Sinan Kalkan Emre Akbas ObjD 16 458 0 31 Aug 2019
Training Data Subset Search with Ensemble Active Learning Kashyap Chitta J. Álvarez Elmar Haussmann C. Farabet 22 13 0 29 May 2019