Research

Papers for “imagenet”

Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.

Title	Authors	Year	Source
An Investigation into Neural Net Optimization via Hessian Eigenvalue Density	Behrooz Ghorbani, Shankar Krishnan, Ying Xiao	2019	arxiv 1901.10159
Infinite Mixture Prototypes for Few-Shot Learning	Kelsey R. Allen, Evan Shelhamer, Hanul Shin	2019	arxiv 1902.04552
Semantic Redundancies in Image-Classification Datasets: The 10% You Don't Need	Vighnesh Birodkar, Hossein Mobahi, Samy Bengio	2019	arxiv 1901.11409
Universal Deep Neural Network Compression	Yoojin Choi, Mostafa El-Khamy, Jungwon Lee	2018	arxiv 1802.02271
2017 Robotic Instrument Segmentation Challenge	Max Allan, Alex Shvets, Thomas Kurmann	2019	arxiv 1902.06426
Discriminator Rejection Sampling	Samaneh Azadi, Catherine Olsson, Trevor Darrell	2018	arxiv 1810.06758
Structured Pruning for Efficient ConvNets via Incremental Regularization	Huan Wang, Qiming Zhang, Yuehai Wang	2018	arxiv 1804.09461
Foothill: A Quasiconvex Regularization for Edge Computing of Deep Neural Networks	Mouloud Belbahri, Eyyüb Sari, Sajad Darabi	2019	arxiv 1901.06414
Diversity with Cooperation: Ensemble Methods for Few-Shot Classification	Nikita Dvornik, Cordelia Schmid, Julien Mairal	2019	arxiv 1903.11341
Learning to Discover Novel Visual Categories via Deep Transfer Clustering	Kai Han, Andrea Vedaldi, Andrew Zisserman	2019	arxiv 1908.09884
Split Batch Normalization: Improving Semi-Supervised Learning under Domain Shift	Micha\l Zając, Konrad Zolna, Stanis\law Jastrzębski	2019	arxiv 1904.03515
Hierarchical Autoregressive Image Models with Auxiliary Decoders	Jeffrey De Fauw, Sander Dieleman, Karen Simonyan	2019	arxiv 1903.04933
VIABLE: Fast Adaptation via Backpropagating Learned Loss	Leo Feng, Luisa Zintgraf, Bei Peng	2019	arxiv 1911.13159
Repetitive Reprediction Deep Decipher for Semi-Supervised Learning	Guo-Hua Wang, Jianxin Wu	2019	arxiv 1908.04345
Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models	Giannis Daras, Augustus Odena, Han Zhang	2019	arxiv 1911.12287
BETANAS: BalancEd TrAining and selective drop for Neural Architecture Search	Muyuan Fang, Qiang Wang, Zhao Zhong	2019	arxiv 1912.11191
Campfire: Compressible, Regularization-Free, Structured Sparse Training for Hardware Accelerators	Noah Gamboa, Kais Kudrolli, Anand Dhoot	2020	arxiv 2001.03253
On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation	Nicolas Brosse, Carlos Riquelme, Alice Martin	2020	arxiv 2001.08049
Parameter Hub: a Rack-Scale Parameter Server for Distributed Deep Neural Network Training	Liang Luo, Jacob Nelson, Luis Ceze	2018	arxiv 1805.07891
Circumventing Outliers of AutoAugment with Knowledge Distillation	Longhui Wei, An Xiao, Lingxi Xie	2020	arxiv 2003.11342

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