User contributions for Alcateri
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17 December 2015
- 21:5721:57, 17 December 2015 diff hist +439 proposal for STAT946 (Deep Learning) final projects Fall 2015 No edit summary
14 December 2015
- 14:4714:47, 14 December 2015 diff hist +623 generating text with recurrent neural networks →Discussion: Cleaned up the discussion and added a new idea about combining character and word level models.
- 14:3414:34, 14 December 2015 diff hist +1 m generating text with recurrent neural networks →Introduction
- 14:1214:12, 14 December 2015 diff hist +145 m neural Turing Machines →Neural Turing Machines: Cleaned up referencing and some wording
- 14:0814:08, 14 December 2015 diff hist +189 neural Turing Machines Added references section and cleaned up referencing in second paragraph
13 December 2015
- 01:1101:11, 13 December 2015 diff hist +339 m learning Phrase Representations →Experiments: - Added some specifics to the experimental results
12 December 2015
- 23:3123:31, 12 December 2015 diff hist +1,656 extracting and Composing Robust Features with Denoising Autoencoders →Analysis of the Denoising Autoencoder: - Included section on Stochastic Operator Perspective
- 22:5022:50, 12 December 2015 diff hist +35 m extracting and Composing Robust Features with Denoising Autoencoders →The Denoising Autoencoder: - Cleaned up the wording and mathematical notation in this section
- 20:0520:05, 12 December 2015 diff hist +2,040 the loss surfaces of multilayer networks (Choromanska et al.) Adding a "Prior Work" section, along with showing the references.
2 December 2015
- 16:1316:13, 2 December 2015 diff hist +564 on the difficulty of training recurrent neural networks →Background
- 16:0116:01, 2 December 2015 diff hist +40 on the difficulty of training recurrent neural networks →Background
23 November 2015
- 13:4013:40, 23 November 2015 diff hist +922 learning Fast Approximations of Sparse Coding →Coordinate Descent: Added CoD algorithm and comment about similarity to ISTA
20 November 2015
- 00:2100:21, 20 November 2015 diff hist +2,310 show, Attend and Tell: Neural Image Caption Generation with Visual Attention Adding Related Work section
18 November 2015
- 21:4321:43, 18 November 2015 diff hist +653 the Manifold Tangent Classifier →Discussion
- 19:1619:16, 18 November 2015 diff hist +20,731 N the Manifold Tangent Classifier Created page with "== Introduction == The goal in many machine learning problems is to extract information from data with minimal prior knowledge<ref name = "main"> Rifai, S., Dauphin, Y. N., Vinc..."
- 18:1618:16, 18 November 2015 diff hist +44 N File:Figure 1 MTC.png Visualization of the learned tangents of CAE current
16 November 2015
- 13:3913:39, 16 November 2015 diff hist +44 f15Stat946PaperSignUp →Set B
12 November 2015
- 12:5412:54, 12 November 2015 diff hist +2,673 deep neural networks for acoustic modeling in speech recognition →Generative Pretraining
- 10:2510:25, 12 November 2015 diff hist +622 deep neural networks for acoustic modeling in speech recognition →Generative Pretraining: - Introduction of Generative Pretraining
11 November 2015
- 23:2423:24, 11 November 2015 diff hist +31 deep neural networks for acoustic modeling in speech recognition No edit summary
30 October 2015
- 11:1511:15, 30 October 2015 diff hist −2 human-level control through deep reinforcement learning →The Bellman Equation in the Loss Framework
- 11:1011:10, 30 October 2015 diff hist +3 human-level control through deep reinforcement learning →Data & Preprocessing
- 11:0511:05, 30 October 2015 diff hist −34 human-level control through deep reinforcement learning →Introduction
- 11:0511:05, 30 October 2015 diff hist −75 human-level control through deep reinforcement learning →Introduction
- 11:0411:04, 30 October 2015 diff hist −10 human-level control through deep reinforcement learning →Introduction
- 11:0311:03, 30 October 2015 diff hist +769 human-level control through deep reinforcement learning No edit summary
- 10:5010:50, 30 October 2015 diff hist −8 human-level control through deep reinforcement learning →Results
- 10:5010:50, 30 October 2015 diff hist +238 human-level control through deep reinforcement learning →Results with model components removed
- 08:5208:52, 30 October 2015 diff hist +65 human-level control through deep reinforcement learning →Results with model components removed
- 08:4908:49, 30 October 2015 diff hist −4 human-level control through deep reinforcement learning →Results with model components removed
- 08:4808:48, 30 October 2015 diff hist +737 human-level control through deep reinforcement learning No edit summary
- 00:0400:04, 30 October 2015 diff hist +212 human-level control through deep reinforcement learning No edit summary
- 00:0000:00, 30 October 2015 diff hist +56 N File:Performance.JPG Performance of DQN vs. Human Tester and Existing Results current
29 October 2015
- 23:5923:59, 29 October 2015 diff hist +873 human-level control through deep reinforcement learning No edit summary
- 23:4723:47, 29 October 2015 diff hist +359 human-level control through deep reinforcement learning No edit summary
- 23:1123:11, 29 October 2015 diff hist +56 N File:QLearning Alg.JPG The algorithm for deep Q-learning with Experience Replay current
- 23:1023:10, 29 October 2015 diff hist +1,529 human-level control through deep reinforcement learning No edit summary
- 22:3622:36, 29 October 2015 diff hist +682 human-level control through deep reinforcement learning →Training
- 21:5121:51, 29 October 2015 diff hist +156 human-level control through deep reinforcement learning No edit summary
- 21:4921:49, 29 October 2015 diff hist +2 human-level control through deep reinforcement learning →Training Details
- 21:4821:48, 29 October 2015 diff hist −3 human-level control through deep reinforcement learning →Training Details
- 21:4721:47, 29 October 2015 diff hist −13 human-level control through deep reinforcement learning →Training Details
- 21:3121:31, 29 October 2015 diff hist −27 human-level control through deep reinforcement learning No edit summary
- 21:2921:29, 29 October 2015 diff hist +1,540 human-level control through deep reinforcement learning No edit summary
- 21:0221:02, 29 October 2015 diff hist +66 N File:Network Architecture.JPG A visualization of the deep convolutional network that estimates Q current
- 19:2219:22, 29 October 2015 diff hist +902 human-level control through deep reinforcement learning No edit summary
- 18:4218:42, 29 October 2015 diff hist +1 human-level control through deep reinforcement learning No edit summary
- 18:4118:41, 29 October 2015 diff hist +1,559 human-level control through deep reinforcement learning →Methodology
- 12:3412:34, 29 October 2015 diff hist +5,637 N human-level control through deep reinforcement learning Created page with "== Introduction == Reinforcement learning is "the study of how animals and artificial systems can learn to optimize their behaviour in the face of rewards and punishments" <ref>..."
23 October 2015
- 12:1512:15, 23 October 2015 diff hist +47 parsing natural scenes and natural language with recursive neural networks →Recursive Neural Networks for Structure Prediction: Improved readability of math expressions by inserting "\,"