User contributions for SophiaH
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1 November 2017
- 14:4014:40, 1 November 2017 diff hist +117 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →LightRNN Example
- 14:3814:38, 1 November 2017 diff hist 0 N File:Table3YH.PNG No edit summary current
- 14:3614:36, 1 November 2017 diff hist 0 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →Part III: Bootstrap for Word Allocation
- 13:1913:19, 1 November 2017 diff hist +1 Convolutional Sequence to Sequence Learning →Position Embeddings
- 12:2312:23, 1 November 2017 diff hist +200 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →References
- 12:2212:22, 1 November 2017 diff hist +614 Understanding the Effective Receptive Field in Deep Convolutional Neural Networks →Why is RF important?
- 11:5811:58, 1 November 2017 diff hist +563 meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting →Related Work
- 11:4511:45, 1 November 2017 diff hist −3 meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting →Introduction
29 October 2017
- 18:2718:27, 29 October 2017 diff hist −6 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →Natural Language Processing (NLP) Using Recurrent Neural Network (RNN)
28 October 2017
- 11:3611:36, 28 October 2017 diff hist +561 Learning the Number of Neurons in Deep Networks →Model Training and Model Selection
- 11:2211:22, 28 October 2017 diff hist +2 Learning the Number of Neurons in Deep Networks →Model Training and Model Selection
- 11:1611:16, 28 October 2017 diff hist +15 Learning the Number of Neurons in Deep Networks →Conclusion
- 11:1311:13, 28 October 2017 diff hist +12 Learning the Number of Neurons in Deep Networks →Introduction
- 11:0511:05, 28 October 2017 diff hist +5 STAT946F17/ Learning Important Features Through Propagating Activation Differences →Numerical results
- 11:0211:02, 28 October 2017 diff hist +8 STAT946F17/ Learning Important Features Through Propagating Activation Differences →Introduction
- 11:0111:01, 28 October 2017 diff hist +2 STAT946F17/ Learning Important Features Through Propagating Activation Differences →Introduction
- 10:5810:58, 28 October 2017 diff hist +2 STAT946F17/ Learning a Probabilistic Latent Space of Object Shapes via 3D GAN →Evaluation current
- 10:5410:54, 28 October 2017 diff hist +9 STAT946F17/ Learning a Probabilistic Latent Space of Object Shapes via 3D GAN →3D-VAE-GANs
- 10:4510:45, 28 October 2017 diff hist +681 When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary →Lasso Regression and Model Selection:
- 10:2710:27, 28 October 2017 diff hist +328 When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary →Ridge Regression and Overfitting:
27 October 2017
- 18:4418:44, 27 October 2017 diff hist +1,102 Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition →Methodology
- 11:4611:46, 27 October 2017 diff hist +1,652 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →Remarks
- 11:4311:43, 27 October 2017 diff hist +1,786 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →Remarks
- 11:4211:42, 27 October 2017 diff hist 0 N File:Table5YH.PNG No edit summary current
- 11:4111:41, 27 October 2017 diff hist 0 N File:Table2YH.PNG No edit summary current
- 11:4111:41, 27 October 2017 diff hist 0 N File:Table1YH.PNG No edit summary current
- 11:4011:40, 27 October 2017 diff hist +17 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →LightRNN Example
- 11:3911:39, 27 October 2017 diff hist +4,244 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →LightRNN Example
- 11:2811:28, 27 October 2017 diff hist +3,405 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →Part III: Bootstrap for Word Allocation
- 11:2511:25, 27 October 2017 diff hist +1 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →Part II: How 2C Shared Embedding is Used in LightRNN
- 11:2211:22, 27 October 2017 diff hist +2,863 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →Part II: How 2C Shared Embedding is Used in LightRNN
- 11:2011:20, 27 October 2017 diff hist +3,228 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →LightRNN Structure
- 11:1811:18, 27 October 2017 diff hist +2,014 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →Natural Language Processing (NLP) Using Recurrent Neural Network (RNN)
- 11:1611:16, 27 October 2017 diff hist −296 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →Introduction
26 October 2017
- 18:5218:52, 26 October 2017 diff hist −3 When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary →Conclusion
- 18:4818:48, 26 October 2017 diff hist −1 When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary →Combining AD Datasets from Multiple Sites
- 18:4718:47, 26 October 2017 diff hist 0 When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary →SMS Lasso L2 Consistency
- 18:4618:46, 26 October 2017 diff hist +4 When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary →Experiments
- 18:4518:45, 26 October 2017 diff hist +1 When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary →Power and Type I Error
- 18:4418:44, 26 October 2017 diff hist +2 When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary →Experiments
- 18:3818:38, 26 October 2017 diff hist +18 When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary →Sparse Multi-Site Lasso and High Dimensional Pooling
20 October 2017
- 17:5717:57, 20 October 2017 diff hist +2,453 STAT946F17/ Learning a Probabilistic Latent Space of Object Shapes via 3D GAN →Related Work
19 October 2017
- 21:2321:23, 19 October 2017 diff hist +2,109 Learning What and Where to Draw →Generative Adversarial Networks
13 October 2017
- 23:1123:11, 13 October 2017 diff hist −1 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →Critique
9 October 2017
- 18:0118:01, 9 October 2017 diff hist +14 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks No edit summary
- 18:0018:00, 9 October 2017 diff hist +61 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks No edit summary
- 16:1016:10, 9 October 2017 diff hist +303 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →Part I: 2-Component Shared Embedding
- 12:2712:27, 9 October 2017 diff hist 0 N File:LightRNN.PNG No edit summary current
- 11:4911:49, 9 October 2017 diff hist −113 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →Part I: 2-Component Shared Embedding
- 11:4811:48, 9 October 2017 diff hist +112 LightRNN: Memory and Computation-Efficient Recurrent Neural Networks →Part I: 2-Component Shared Embedding