Deep Domain Confusion: Maximizing for Domain Invariance

arXiv:0706.3639v1 [cs.AI] 25 Jun 2007

arXiv:0706.3639v1 [cs.AI] 25 Jun 2007 Technical Report IDSIA-07-07 A Collection of Definitions of Intelligence Shane Legg IDSIA, Galleria …

  Intelligence, Collection

Deep Residual Learning for Image Recognition - …

Deep Residual Learning for Image Recognition Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun Microsoft Research fkahe, v-xiangz, v-shren, jiansung@microsoft.com

  Image, Learning, Residual, Recognition, Residual learning for image recognition

arXiv:1301.3781v3 [cs.CL] 7 Sep 2013

For all the following models, the training complexity is proportional to O = E T Q; (1) where E is number of the training epochs, T is the number of …

@google.com arXiv:1609.03499v2 [cs.SD] 19 Sep 2016

where 1 <x t <1 and = 255. This non-linear quantization produces a significantly better reconstruction than a simple linear quantization scheme. …

A Tutorial on UAVs for Wireless Networks: …

A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems Mohammad Mozaffari 1, ... to UAVs in wireless communications is the work in …

  Network, Communication, Wireless, Wireless communications, Wireless networks

Adversarial Generative Nets: Neural Network …

Adversarial Generative Nets: Neural Network Attacks on State-of-the-Art Face Recognition Mahmood Sharif, Sruti Bhagavatula, Lujo Bauer Carnegie Mellon University

  Network, Attacks, Nets, Adversarial generative nets, Adversarial, Generative, Neural network, Neural, Neural network attacks

Massive Exploration of Neural Machine Translation ...

Massive Exploration of Neural Machine Translation Architectures Denny Britzy, Anna Goldie, Minh-Thang Luong, Quoc Le fdennybritz,agoldie,thangluong,qvlg@google.com Google Brain

  Architecture, Machine, Exploration, Translation, Neural, Exploration of neural machine translation, Exploration of neural machine translation architectures

Mastering Chess and Shogi by Self-Play with a …

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm David Silver, 1Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, 1Matthew Lai, Arthur Guez, Marc Lanctot,1

Going deeper with convolutions - arXiv

Going deeper with convolutions Christian Szegedy Google Inc. Wei Liu University of North Carolina, Chapel Hill Yangqing Jia Google Inc. Pierre Sermanet

  With, Going, Going deeper with convolutions, Deeper, Convolutions

Andrew G. Howard Menglong Zhu Bo Chen Dmitry ...

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand Marco Andreetto Hartwig Adam

  Applications

Learning Transferable Features with Deep Adaptation Networks

Deep Adaptation Networks In unsupervised domain adaptation, we are given a source domainDs = {(xs i,y s i)} ns i=1 withns labeledexamples,and a target domain Dt = {xt j} nt j=1 with nt unlabeled exam-ples. The source domain and target domain are charac-terized by probability distributions p and q, respectively.

  Adaptation, Unsupervised

PSD: Principled Synthetic-to-Real Dehazing Guided by ...

2.2. Unsupervised Domain Adaptation Unsupervised domain adaptation aims to tackle domain shift between source and target domains, while images in the target domain are unlabeled. One major idea is to in-duce alignment between the source and target domains in feature space by optimizing for some measurements of dis-tributional discrepancy [23 ...

  Adaptation, Unsupervised, Unsupervised adaptation

Maximum Classifier Discrepancy for Unsupervised Domain ...

Maximum Classifier Discrepancy for Unsupervised Domain Adaptation Kuniaki Saito1, Kohei Watanabe1, Yoshitaka Ushiku1, and Tatsuya Harada1,2 1The University of Tokyo, 2RIKEN {k-saito,watanabe,ushiku,harada}@mi.t.u-tokyo.ac.jp Abstract In this work, we present a method for unsupervised do-

  Adaptation, Unsupervised

Internal Audit: Key risk areas 2021

circumvented when employees are unsupervised, as they are often overlooked and ignored to save time. Advancements of technology also increase the sophistication and frequency of cyber security attacks and frauds. Internal Audit can offer its view on the extent to which any relaxing or adaptation of controls has

  Internal, Audit, Adaptation, Internal audit, Unsupervised

Guidance on the Use of Antipsychotics

Lester UK Adaptation – Positive Cardiometabolic Health Resource 51 Appendix 7 Drugs known to prolong QT interval 54 Appendix 8 References ... who are unsupervised For non-adherent patients who are supervised Change to an alternative depot medication or other long-acting

  Adaptation, Unsupervised

WIPO Technology Trends 2019: Artificial Intelligence

“unsupervised learning” – learning without labelled data – remains a holy grail of AI. Even without this “holy grail,” AI is already creating massive economic value in the world today. In covering AI, the media tends to focus on images, speech and natural language processing because those types of data are very human.

  Technology, Trends, Wipo, Unsupervised, Wipo technology trends

AAAI-21 Accepted Paper List.1.29

! 4!! 228:!Rain!Streak!Removal!via!Dual!Graph!Convolutional!Network! Xueyang!Fu,!Qi!Qi,!Yurui!Zhu,!Xinghao!Ding,!Zheng*Jun!Zha!! 233:!RevMan:!Revenue*Aware!Multi*Task ...