International Conference on Learning Representations (ICLR) 2016, San Juan

#ICLR2016 talks and video lectures  #MachineLearning #DeepLearning

  • Guaranteed Non-convex Learning Algorithms through Tensor Factorization Guaranteed Non-convex Learning Algorithms through Tensor Factorization
  • Incorporating Structure in Deep Learning Incorporating Structure in Deep Learning
  • We take a broad view of the field, and include in it topics such as deep learning and feature learning, metric learning, kernel learning, compositional models, non-linear structured prediction, and issues regarding non-convex optimization.
  • The rapidly developing field of representation learning is concerned with questions surrounding how we can best learn meaningful and useful representations of data.
  • Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization …

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@kdnuggets: “#ICLR2016 talks and video lectures #MachineLearning #DeepLearning”


ICLR is an annual conference sponsored by the Computational and Biological Learning Society. It is well understood that the performance of machine learning methods is heavily dependent on the choice of data representation (or features) on which they are applied. The rapidly developing field of representation learning is concerned with questions surrounding how we can best learn meaningful and useful representations of data. We take a broad view of the field, and include in it topics such as deep learning and feature learning, metric learning, kernel learning, compositional models, non-linear structured prediction, and issues regarding non-convex optimization. Despite the importance of representation learning to machine learning and to application areas such as vision, speech, audio and NLP, there was no venue for researchers who share a common interest in this topic. The goal of ICLR has been to help fill this void.


International Conference on Learning Representations (ICLR) 2016, San Juan