Regularized Deep Networks – ICLR 2017 Discoveries

This blog post gives an overview of papers related to using Regularization in Deep Learning submitted to ICLR 2017, see underneath for the list of papers. If you want to learn about Regularization in Deep Learning check out: www.deeplearningbook.org/contents/regularization.html

  1. Mode Regularized Generative Adversarial Networks – Authors: Tong Che, Yanran Li, Athul Jacob, Yoshua Bengio, Wenjie Li
  2. Representation Stability as a Regularizer for Neural Network Transfer Learning – Authors: Matthew Riemer, Elham Khabiri, Richard Goodwin
  3. Neural Causal Regularization under the Independence of Mechanisms Assumption – Authors: Mohammad Taha Bahadori, Krzysztof Chalupka, Edward Choi, Walter F. Stewart, Jimeng Sun
  4. Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations – Authors: David Krueger, Tegan Maharaj, Janos Kramar, Mohammad Pezeshki, Nicolas Ballas, Nan Rosemary Ke, Anirudh  Goyal, Yoshua Bengio, Aaron Courville, Christopher Pal
  5. Bridging Nonlinearities and Stochastic Regularizers with Gaussian Error Linear Units – Authors: Dan Hendrycks, Kevin Gimpel
  6. Regularizing CNNs with Locally Constrained Decorrelations – Authors: Pau Rodríguez, Jordi Gonzàlez, Guillem Cucurull, Josep M. Gonfaus, Xavier Roca
  7. Regularizing Neural Networks by Penalizing Confident Output Distributions – Authors: Gabriel Pereyra, George Tucker, Jan Chorowski, Lukasz Kaiser, Geoffrey Hinton
  8. Multitask Regularization for Semantic Vector Representation of Phrases – Authors: Xia Song, Saurabh Tiwary \& Rangan Majumdar
  9. (F)SPCD: Fast Regularization of PCD by Optimizing Stochastic ML Approximation under Gaussian Noise – Authors: Prima Sanjaya, Dae-Ki Kang
  10. Crossmap Dropout : A Generalization of Dropout Regularization in Convolution Level – Authors: Alvin Poernomo, Dae-Ki Kang
  11. Non-linear Dimensionality Regularizer for Solving Inverse Problems – Authors: Ravi Garg, Anders Eriksson, Ian Reid
  12. Support Regularized Sparse Coding and Its Fast Encoder – Authors: Yingzhen Yang, Jiahui Yu, Pushmeet Kohli, Jianchao Yang, Thomas S. Huang
  13. An Analysis of Feature Regularization for Low-shot Learning – Authors: Zhuoyuan Chen, Han Zhao, Xiao Liu, Wei Xu
  14. Dropout with Expectation-linear Regularization – Authors: Xuezhe Ma, Yingkai Gao, Zhiting Hu, Yaoliang Yu, Yuntian Deng, Eduard Hovy
  15. SoftTarget Regularization: An Effective Technique to Reduce Over-Fitting in Neural Networks – Authors: Armen Aghajanyan

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