Hard Example

"Hard examples," in machine learning, refer to data points that are difficult for models to classify or predict accurately, leading to errors like false negatives in object detection or inaccurate estimations in regression tasks. Current research focuses on identifying and addressing these hard examples through various techniques, including specialized loss functions (like Focal Loss and its adaptations), attention mechanisms (as seen in transformer-based models), and algorithms that prioritize learning from these challenging instances. This research is crucial for improving model robustness and generalization, with significant implications for applications like autonomous driving, natural language processing, and other fields relying on accurate and reliable machine learning models.

Papers

August 8, 2023

FocalFormer3D : Focusing on Hard Instance for 3D Object Detection
Yilun Chen, Zhiding Yu, Yukang Chen, Shiyi Lan, Animashree Anandkumar, Jiaya Jia, Jose Alvarez
3D Object Detection 3D Detector Hard Example

November 14, 2022

Are Hard Examples also Harder to Explain? A Study with Human and Model-Generated Explanations
Swarnadeep Saha, Peter Hase, Nazneen Rajani, Mohit Bansal
Natural Language Processing High Explainability Study Feature Human Generated Natural Language Explanation Human Explanation Hard Example

October 20, 2022

Tighter PAC-Bayes Generalisation Bounds by Leveraging Example Difficulty
Felix Biggs, Benjamin Guedj
Excess Risk PAC Bayesian Generalization Bound Hard Example

September 19, 2022

Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty
Thomas George, Guillaume Lajoie, Aristide Baratin
Deep Neural Network Deep Network Task Scheduling Spurious Correlation Feature Learning Lazy Search Reverse Graph Linearization Lazy Training Hard Example

July 15, 2022

Adversarial Focal Loss: Asking Your Discriminator for Hard Examples
Chen Liu, Xiaomeng Dong, Michael Potter, Hsi-Ming Chang, Ravi Soni
Loss Function Keypoint Detection Focal Loss Bi Discriminator Hard Example

July 7, 2022

A Study on the Predictability of Sample Learning Consistency
Alain Raymond-Saez, Julio Hurtado, Alvaro Soto
Study Feature Curriculum Learning Predictability Problem Hard Example C Score

April 15, 2022

SSR-HEF: Crowd Counting with Multi-Scale Semantic Refining and Hard Example Focusing
Jiwei Chen, Kewei Wang, Wen Su, Zengfu Wang
Deep Learning Crowd Counting Selective Focus Density Map Multi Scale Semantic Hard Example GR SAF Algorithm

March 16, 2022

Example Perplexity
Nevin L. Zhang, Weiyan Xie, Zhi Lin, Guanfang Dong, Xiao-Hui Li, Caleb Chen Cao, Yunpeng Wang
Deep Neural Network Hard Example