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When Do Curricula Work?

5 December 2020

Papers citing "When Do Curricula Work?"

33 / 83 papers shown

Title
What Can Transformers Learn In-Context? A Case Study of Simple Function Classes Shivam Garg Dimitris Tsipras Percy Liang Gregory Valiant 197 514 0 01 Aug 2022
Rank-based Decomposable Losses in Machine Learning: A Survey Shu Hu Xin Wang Siwei Lyu 108 32 0 18 Jul 2022
Angular Gap: Reducing the Uncertainty of Image Difficulty through Model Calibration Bohua Peng Mobarakol Islam Mei Tu UQCV 75 9 0 18 Jul 2022
Grounding Aleatoric Uncertainty for Unsupervised Environment Design Minqi Jiang Michael Dennis Jack Parker-Holder Andrei Lupu Heinrich Küttler Edward Grefenstette Tim Rocktaschel Jakob N. Foerster 110 15 0 11 Jul 2022
A Study on the Predictability of Sample Learning Consistency Alain Raymond-Sáez J. Hurtado Alvaro Soto 36 0 0 07 Jul 2022
Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks Mansheej Paul Brett W. Larsen Surya Ganguli Jonathan Frankle Gintare Karolina Dziugaite 69 24 0 02 Jun 2022
Efficient Scheduling of Data Augmentation for Deep Reinforcement Learning Byungchan Ko Jungseul Ok OnRL 142 5 0 01 Jun 2022
The Effect of Task Ordering in Continual Learning Samuel J. Bell Neil D. Lawrence CLL 93 17 0 26 May 2022
Goldilocks-curriculum Domain Randomization and Fractal Perlin Noise with Application to Sim2Real Pneumonia Lesion Detection Takahiro Suzuki S. Hanaoka Issei Sato OOD MedIm 71 1 0 29 Apr 2022
Better Language Model with Hypernym Class Prediction Richard He Bai Tong Wang Alessandro Sordoni Peng Shi 147 16 0 21 Mar 2022
Cyclical Curriculum Learning Himmet Toprak Kesgin M. Amasyalı ODL 77 9 0 11 Feb 2022
PT4AL: Using Self-Supervised Pretext Tasks for Active Learning J. S. K. Yi Min-seok Seo Jongchan Park Dong-Geol Choi SSL VLM 73 41 0 19 Jan 2022
Interpretable Low-Resource Legal Decision Making R. Bhambhoria Hui Liu Samuel Dahan Xiao-Dan Zhu ELM AILaw 73 10 0 01 Jan 2022
Do Data-based Curricula Work? Maxim K. Surkov Vladislav D. Mosin Ivan P. Yamshchikov 80 4 0 13 Dec 2021
ACPL: Anti-curriculum Pseudo-labelling for Semi-supervised Medical Image Classification Fengbei Liu Yu Tian Yuanhong Chen Yuyuan Liu Vasileios Belagiannis G. Carneiro 131 83 0 25 Nov 2021
SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise Chen Feng Georgios Tzimiropoulos Ioannis Patras NoLa 94 18 0 22 Nov 2021
Which Samples Should be Learned First: Easy or Hard? Xiaoling Zhou Ou Wu 80 17 0 11 Oct 2021
DCUR: Data Curriculum for Teaching via Samples with Reinforcement Learning Daniel Seita Abhinav Gopal Zhao Mandi John F. Canny OffRL OnRL 49 0 0 15 Sep 2021
Learning From Long-Tailed Data With Noisy Labels Shyamgopal Karthik Jérôme Revaud Boris Chidlovskii SSL NoLa 88 27 0 25 Aug 2021
Improving Self-supervised Learning with Hardness-aware Dynamic Curriculum Learning: An Application to Digital Pathology C. Srinidhi Anne L. Martel 113 22 0 16 Aug 2021
Uniform Sampling over Episode Difficulty Sébastien M. R. Arnold Guneet Singh Dhillon Avinash Ravichandran Stefano Soatto 67 14 0 03 Aug 2021
Self-Paced Contrastive Learning for Semi-supervised Medical Image Segmentation with Meta-labels Jizong Peng Ping Wang Chrisitian Desrosiers M. Pedersoli SSL 91 65 0 29 Jul 2021
Compensation Learning Rujing Yao Ou Wu 60 2 0 26 Jul 2021
Progressive Class-based Expansion Learning For Image Classification Hui Wang Hanbin Zhao Xi Li 49 0 0 28 Jun 2021
Friendly Training: Neural Networks Can Adapt Data To Make Learning Easier Simone Marullo Matteo Tiezzi Marco Gori S. Melacci OOD 35 3 0 21 Jun 2021
Deep Learning Through the Lens of Example Difficulty R. Baldock Hartmut Maennel Behnam Neyshabur 107 163 0 17 Jun 2021
An Analytical Theory of Curriculum Learning in Teacher-Student Networks Luca Saglietti Stefano Sarao Mannelli Andrew M. Saxe 59 27 0 15 Jun 2021
Gradual Domain Adaptation in the Wild:When Intermediate Distributions are Absent Samira Abnar Rianne van den Berg Golnaz Ghiasi Mostafa Dehghani Nal Kalchbrenner Hanie Sedghi OOD CLL TTA 93 22 0 10 Jun 2021
Curriculum Design for Teaching via Demonstrations: Theory and Applications Gaurav Yengera R. Devidze Parameswaran Kamalaruban Adish Singla 179 7 0 08 Jun 2021
Statistical Measures For Defining Curriculum Scoring Function Vinu Sankar Sadasivan A. Dasgupta 84 2 0 27 Feb 2021
Self-Diagnosing GAN: Diagnosing Underrepresented Samples in Generative Adversarial Networks J. Lee Haeri Kim Youngkyu Hong Hye Won Chung 123 23 0 24 Feb 2021
A Too-Good-to-be-True Prior to Reduce Shortcut Reliance Nikolay Dagaev Brett D. Roads Xiaoliang Luo Daniel N. Barry Kaustubh R. Patil Bradley C. Love 99 9 0 12 Feb 2021
$Curriculum learning for improved femur fracture classification: scheduling data with prior knowledge and uncertainty$ Curriculum learning for improved femur fracture classification: scheduling data with prior knowledge and uncertainty Amelia Jiménez-Sánchez Diana Mateus S. Kirchhoff C. Kirchhoff P. Biberthaler Nassir Navab M. A. G. Ballester Gemma Piella 52 19 0 31 Jul 2020