Papers
Adversarial Defense by Stratified Convolutional Sparse Coding
Bo Sun, Nian-Hsuan Tsai, Fangchen Liu et al.
Additive Adversarial Learning for Unbiased Authentication
Jian Liang, Yuren Cao, Chenbin Zhang et al.
Robustness Verification of Classification Deep Neural Networks via Linear Programming
Wang Lin, Zhengfeng Yang, Xin Chen et al.
Regularizing Activation Distribution for Training Binarized Deep Networks
Ruizhou Ding, Ting-Wu Chin, Zeye Liu et al.
ChamNet: Towards Efficient Network Design Through Platform-Aware Model Adaptation
Xiaoliang Dai, Peizhao Zhang, Bichen Wu et al.
Sim-Real Joint Reinforcement Transfer for 3D Indoor Navigation
Fengda Zhu, Linchao Zhu, Yi Yang
End-To-End Efficient Representation Learning via Cascading Combinatorial Optimization
Yeonwoo Jeong, Yoonsung Kim, Hyun Oh Song
Model-Blind Video Denoising via Frame-To-Frame Training
Thibaud Ehret, Axel Davy, Jean-Michel Morel et al.
PEPSI : Fast Image Inpainting With Parallel Decoding Network
Min-cheol Sagong, Yong-goo Shin, Seung-wook Kim et al.
Trust Region Based Adversarial Attack on Neural Networks
Zhewei Yao, Amir Gholami, Peng Xu et al.
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations
Saeid Asgari Taghanaki, Kumar Abhishek, Shekoofeh Azizi et al.
AIRD: Adversarial Learning Framework for Image Repurposing Detection
Ayush Jaiswal, Yue Wu, Wael AbdAlmageed et al.
Learning to Remember: A Synaptic Plasticity Driven Framework for Continual Learning
Oleksiy Ostapenko, Mihai Puscas, Tassilo Klein et al.
Semi-Supervised Learning With Graph Learning-Convolutional Networks
Bo Jiang, Ziyan Zhang, Doudou Lin et al.
Building Efficient Deep Neural Networks With Unitary Group Convolutions
Ritchie Zhao, Yuwei Hu, Jordan Dotzel et al.
Characterizing and Avoiding Negative Transfer
Zirui Wang, Zihang Dai, Barnabas Poczos et al.
Coloring With Limited Data: Few-Shot Colorization via Memory Augmented Networks
Seungjoo Yoo, Hyojin Bahng, Sunghyo Chung et al.
Detecting Overfitting of Deep Generative Networks via Latent Recovery
Ryan Webster, Julien Rabin, Loic Simon et al.
Importance Estimation for Neural Network Pruning
Pavlo Molchanov, Arun Mallya, Stephen Tyree et al.
Task-Free Continual Learning
Rahaf Aljundi, Klaas Kelchtermans, Tinne Tuytelaars
Learning From Noisy Labels by Regularized Estimation of Annotator Confusion
Ryutaro Tanno, Ardavan Saeedi, Swami Sankaranarayanan et al.
Rob-GAN: Generator, Discriminator, and Adversarial Attacker
Xuanqing Liu, Cho-Jui Hsieh
Defending Against Adversarial Attacks by Randomized Diversification
Olga Taran, Shideh Rezaeifar, Taras Holotyak et al.
SeerNet: Predicting Convolutional Neural Network Feature-Map Sparsity Through Low-Bit Quantization
Shijie Cao, Lingxiao Ma, Wencong Xiao et al.