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2011.md

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2011

  • Adaptive Deconvolutional Networks for Mid and High Level Feature Learning.[[pdf](docs/2011/Adaptive Deconvolutional Networks for Mid and High Level Feature Learning.pdf)] [url]
  • Asymptotic efficiency of deterministic estimators for discrete energy-based models Ratio matching and pseudolikelihood.[[pdf](docs/2011/Asymptotic efficiency of deterministic estimators for discrete energy-based models Ratio matching and pseudolikelihood.pdf)] [url]
  • Building high-level features using large scale unsupervised learning. [arxiv]
  • Contractive Auto-Encoders-Explicit Invariance During Feature Extraction.[[pdf](docs/2011/Contractive Auto-Encoders-Explicit Invariance During Feature Extraction.pdf)] [url]
  • Cross-domain activity recognition via transfer learning. [url]
  • Heterogeneous Transfer Learning for Image Classification. [url] ⭐
  • Kinship Verification through Transfer Learning. [url]
  • Learning Deep Energy Models.[[pdf](docs/2011/Learning Deep Energy Models.pdf)] [url]
  • Learning image representations from the pixel level via hierarchical sparse coding.[[pdf](docs/2011/Learning image representations from the pixel level via hierarchical sparse coding.pdf)] [url]
  • Natural Language Processing (almost) from Scratch.[[pdf](docs/2011/Natural Language Processing (almost) from Scratch(2011).pdf)] [url] ⭐
  • On Autoencoders and Score Matching for Energy Based Models.[[pdf](docs/2011/On Autoencoders and Score Matching for Energy Based Models.pdf)] [url]
  • On Optimization Methods for Deep Learning.[[pdf](docs/2011/On Optimization Methods for Deep Learning.pdf)] [url]
  • On the Expressive Power of Deep Architectures.[[pdf](docs/2011/On the Expressive Power of Deep Architectures.pdf)] [url]
  • Spike-and-Slab Sparse Coding for Unsupervised Feature Discovery.[[pdf](docs/2011/Spike-and-Slab Sparse Coding for Unsupervised Feature Discovery.pdf)] [url]
  • Unsupervised Learning of Hierarchical Representations with Convolutional Deep Belief Networks.[[pdf]](docs/2011/Unsupervised Learning of Hierarchical Representations with Convolutional Deep Belief Networks.pdf) [url]]
  • Unsupervised Models of Images by Spike-and-Slab RBMs.[[pdf](docs/2011/Unsupervised Models of Images by Spike-and-Slab RBMs.pdf)] [url]

Attention

  • Learning where to Attend with Deep Architectures for Image Tracking. [arxiv]

Transfer learning

  • Domain Adaptation for Large-Scale Sentiment Classification - A Deep Learning Approach. [pdf] ⭐
  • Heterogeneous domain adaptation using manifold alignment. [pdf]
  • Heterogeneous Transfer Learning for Image Classification. [pdf] [code]
  • Learning from multiple outlooks. [pdf]
  • Multi-source domain adaptation and its application to early detection of fatigue. [pdf] ⭐
  • What you saw is not what you get: Domain adaptation using asymmetric kernel transforms. [pdf]