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Small-GAN: Speeding Up GAN Training Using Core-sets

Small-GAN: Speeding Up GAN Training Using Core-sets

29 October 2019
Samarth Sinha
Hang Zhang
Anirudh Goyal
Yoshua Bengio
Hugo Larochelle
Augustus Odena
    GAN
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Papers citing "Small-GAN: Speeding Up GAN Training Using Core-sets"

12 / 12 papers shown
Title
Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models
Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models
Yulei Qin
Yuncheng Yang
Pengcheng Guo
Gang Li
Hang Shao
Yuchen Shi
Zihan Xu
Yun Gu
Ke Li
Xing Sun
ALM
90
12
0
31 Dec 2024
ATOM: Attention Mixer for Efficient Dataset Distillation
ATOM: Attention Mixer for Efficient Dataset Distillation
Samir Khaki
A. Sajedi
Kai Wang
Lucy Z. Liu
Y. Lawryshyn
Konstantinos N. Plataniotis
47
3
0
02 May 2024
Training Quantum Boltzmann Machines with Coresets
Training Quantum Boltzmann Machines with Coresets
Joshua Viszlai
T. Tomesh
P. Gokhale
Eric R. Anschuetz
Frederic T. Chong
16
0
0
26 Jul 2023
FMGNN: Fused Manifold Graph Neural Network
FMGNN: Fused Manifold Graph Neural Network
Cheng Deng
Fan Xu
Jiaxing Ding
Luoyi Fu
Weinan Zhang
Xinbing Wang
30
3
0
03 Apr 2023
Obstacle Aware Sampling for Path Planning
Obstacle Aware Sampling for Path Planning
M. Tukan
Alaa Maalouf
Dan Feldman
Roi Poranne
18
8
0
08 Mar 2022
Adversarial Robustness of Streaming Algorithms through Importance
  Sampling
Adversarial Robustness of Streaming Algorithms through Importance Sampling
Vladimir Braverman
Avinatan Hassidim
Yossi Matias
Mariano Schain
Sandeep Silwal
Samson Zhou
AAML
OOD
22
38
0
28 Jun 2021
One Backward from Ten Forward, Subsampling for Large-Scale Deep Learning
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
18
5
0
27 Apr 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs,
  Normalizing Flows, Energy-Based and Autoregressive Models
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models
Sam Bond-Taylor
Adam Leach
Yang Long
Chris G. Willcocks
VLM
TPM
36
478
0
08 Mar 2021
AlphaGAN: Fully Differentiable Architecture Search for Generative
  Adversarial Networks
AlphaGAN: Fully Differentiable Architecture Search for Generative Adversarial Networks
Yuesong Tian
Li Shen
Li Shen
Guinan Su
Zhifeng Li
Wei Liu
GAN
21
32
0
16 Jun 2020
Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs
Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs
Sangwoo Mo
Minsu Cho
Jinwoo Shin
19
212
0
25 Feb 2020
Improved Consistency Regularization for GANs
Improved Consistency Regularization for GANs
Zhengli Zhao
Sameer Singh
Honglak Lee
Zizhao Zhang
Augustus Odena
Han Zhang
16
152
0
11 Feb 2020
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
281
2,888
0
15 Sep 2016
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