About
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.
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Uploaded videos:
Opening Remarks
Opening
May 27, 2016
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4166 Views
Keynote Talks
Deep Robotic Learning
May 27, 2016
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12839 Views
Should Model Architecture Reflect Linguistic Structure?
May 27, 2016
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7930 Views
Guaranteed Non-convex Learning Algorithms through Tensor Factorization
May 27, 2016
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4796 Views
Beyond Backpropagation: Uncertainty Propagation
May 27, 2016
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5655 Views
Incorporating Structure in Deep Learning
May 27, 2016
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13524 Views
Best Paper Awards
Neural Programmer-Interpreters
May 27, 2016
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5880 Views
Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantiz...
May 27, 2016
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20025 Views
Lectures
Regularizing RNNs by Stabilizing Activations
May 27, 2016
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2829 Views
BlackOut: Speeding up Recurrent Neural Network Language Models With Very Large V...
May 27, 2016
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2117 Views
The Goldilocks Principle: Reading Children's Books with Explicit Memory Represen...
May 27, 2016
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2573 Views
Towards Universal Paraphrastic Sentence Embeddings
May 27, 2016
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2333 Views
Convergent Learning: Do different neural networks learn the same representations...
May 27, 2016
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10111 Views
Net2Net: Accelerating Learning via Knowledge Transfer
May 27, 2016
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4114 Views
Variational Gaussian Process
May 27, 2016
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3157 Views
The Variational Fair Autoencoder
May 27, 2016
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2611 Views
A note on the evaluation of generative models
May 27, 2016
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2749 Views
Neural Networks with Few Multiplications
May 27, 2016
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2329 Views
Order-Embeddings of Images and Language
May 27, 2016
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4025 Views
Generating Images from Captions with Attention
May 27, 2016
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2584 Views
Density Modeling of Images using a Generalized Normalization Transformation
Jun 15, 2016
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4191 Views