User contributions for Amirlk
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18 December 2015
- 01:1501:15, 18 December 2015 diff hist +31 proposal for STAT946 (Deep Learning) final projects Fall 2015 No edit summary
11 December 2015
- 16:4216:42, 11 December 2015 diff hist +193 continuous space language models →Conclusion
- 16:4016:40, 11 December 2015 diff hist +246 continuous space language models →Conclusion
- 16:3916:39, 11 December 2015 diff hist +356 continuous space language models →Conclusion
- 16:3616:36, 11 December 2015 diff hist +274 continuous space language models →Conclusion
- 16:3416:34, 11 December 2015 diff hist +16 continuous space language models No edit summary
- 16:2116:21, 11 December 2015 diff hist −2 scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers Machines →Model
- 16:2016:20, 11 December 2015 diff hist +302 scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers Machines →Model
- 16:1916:19, 11 December 2015 diff hist +53 scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers Machines →Model
- 16:1916:19, 11 December 2015 diff hist +299 scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers Machines →Model
- 13:5613:56, 11 December 2015 diff hist +172 deep Learning of the tissue-regulated splicing code →Training the model
- 13:4613:46, 11 December 2015 diff hist +383 deep Learning of the tissue-regulated splicing code →Training the model
- 13:4313:43, 11 December 2015 diff hist +58 deep Learning of the tissue-regulated splicing code →Training the model
- 01:0901:09, 11 December 2015 diff hist +371 joint training of a convolutional network and a graphical model for human pose estimation →Higher-Level Spatial-Model
- 01:0401:04, 11 December 2015 diff hist +292 joint training of a convolutional network and a graphical model for human pose estimation →Higher-Level Spatial-Model
- 00:5500:55, 11 December 2015 diff hist +213 joint training of a convolutional network and a graphical model for human pose estimation →Unified Model
8 December 2015
- 23:1623:16, 8 December 2015 diff hist −1 from Machine Learning to Machine Reasoning →Probabilistic Models
- 23:1523:15, 8 December 2015 diff hist +168 from Machine Learning to Machine Reasoning →Probabilistic Models
- 23:1123:11, 8 December 2015 diff hist +242 from Machine Learning to Machine Reasoning →Probabilistic Models
- 23:0923:09, 8 December 2015 diff hist +214 from Machine Learning to Machine Reasoning →Probabilistic Models
2 December 2015
- 22:4922:49, 2 December 2015 diff hist −24 proposal for STAT946 (Deep Learning) final projects Fall 2015 No edit summary
28 November 2015
- 17:4617:46, 28 November 2015 diff hist +111 proposal for STAT946 (Deep Learning) final projects Fall 2015 No edit summary
26 November 2015
- 20:2920:29, 26 November 2015 diff hist +913 memory Networks →Extensions to the Basic Implementation
- 20:1820:18, 26 November 2015 diff hist +343 memory Networks →Extensions to the Basic Implementation
- 20:1620:16, 26 November 2015 diff hist +139 memory Networks →Extensions to the Basic Implementation
- 19:1019:10, 26 November 2015 diff hist +6 f15Stat946PaperSignUp →Set A
- 19:0919:09, 26 November 2015 diff hist +13 f15Stat946PaperSignUp →Set A
- 19:0819:08, 26 November 2015 diff hist +63 f15Stat946PaperSignUp →Set A
- 19:0119:01, 26 November 2015 diff hist −125 strategies for Training Large Scale Neural Network Language Models →References
- 19:0119:01, 26 November 2015 diff hist +227 strategies for Training Large Scale Neural Network Language Models →Recurrent Neural Network Models
- 18:5818:58, 26 November 2015 diff hist −151 strategies for Training Large Scale Neural Network Language Models →References
- 18:5618:56, 26 November 2015 diff hist +228 strategies for Training Large Scale Neural Network Language Models →Recurrent Neural Network Models
- 18:5318:53, 26 November 2015 diff hist +477 strategies for Training Large Scale Neural Network Language Models →Recurrent Neural Network Models
- 18:4818:48, 26 November 2015 diff hist +257 strategies for Training Large Scale Neural Network Language Models →Recurrent Neural Network Models
- 18:3918:39, 26 November 2015 diff hist +889 imageNet Classification with Deep Convolutional Neural Networks →Overall Architecture
- 17:3917:39, 26 November 2015 diff hist +258 imageNet Classification with Deep Convolutional Neural Networks →Local Response Normalization
- 17:3617:36, 26 November 2015 diff hist +63 imageNet Classification with Deep Convolutional Neural Networks →ReLU Nonlinearity
23 November 2015
- 16:0016:00, 23 November 2015 diff hist +354 learning Fast Approximations of Sparse Coding →Pre-existing Approximations: Iterative Shrinkage Algorithms
- 15:5915:59, 23 November 2015 diff hist +101 learning Fast Approximations of Sparse Coding →Pre-existing Approximations: Iterative Shrinkage Algorithms
- 15:3015:30, 23 November 2015 diff hist +343 deep Neural Nets as a Method for Quantitative Structure–Activity Relationships →Results
- 15:2915:29, 23 November 2015 diff hist +93 deep Neural Nets as a Method for Quantitative Structure–Activity Relationships →Results
- 15:2915:29, 23 November 2015 diff hist +169 deep Neural Nets as a Method for Quantitative Structure–Activity Relationships →Results
20 November 2015
- 18:4418:44, 20 November 2015 diff hist +93 f15Stat946PaperSignUp →Set A
- 00:0000:00, 20 November 2015 diff hist +290 genetics →Conclusion
19 November 2015
- 23:5823:58, 19 November 2015 diff hist +248 genetics →Rationale
- 23:4423:44, 19 November 2015 diff hist +638 dropout →Model
- 23:3623:36, 19 November 2015 diff hist +588 dropout →Model
- 23:2223:22, 19 November 2015 diff hist +177 show, Attend and Tell: Neural Image Caption Generation with Visual Attention →Attention: Two Variants
- 23:2023:20, 19 November 2015 diff hist +274 show, Attend and Tell: Neural Image Caption Generation with Visual Attention →Attention: Two Variants
- 23:1723:17, 19 November 2015 diff hist +162 show, Attend and Tell: Neural Image Caption Generation with Visual Attention →Attention: Two Variants
- 19:5619:56, 19 November 2015 diff hist −230 show, Attend and Tell: Neural Image Caption Generation with Visual Attention Undo revision 26667 by Amirlk (talk)
- 19:5419:54, 19 November 2015 diff hist +230 show, Attend and Tell: Neural Image Caption Generation with Visual Attention →Encoder: Convolutional Features
- 19:5219:52, 19 November 2015 diff hist 0 N File:Fr 1.PNG No edit summary current
- 17:4817:48, 19 November 2015 diff hist +539 natural language processing (almost) from scratch. →Network Design
- 17:3317:33, 19 November 2015 diff hist +231 natural language processing (almost) from scratch. →Semantic Role Labelling (SRL)
- 15:3615:36, 19 November 2015 diff hist +1 distributed Representations of Words and Phrases and their Compositionality No edit summary
- 15:3215:32, 19 November 2015 diff hist +29 distributed Representations of Words and Phrases and their Compositionality No edit summary
- 15:3115:31, 19 November 2015 diff hist +34 distributed Representations of Words and Phrases and their Compositionality →Empirical Results
- 15:2915:29, 19 November 2015 diff hist 0 distributed Representations of Words and Phrases and their Compositionality →Hierarchical Softmax
- 15:2815:28, 19 November 2015 diff hist +517 distributed Representations of Words and Phrases and their Compositionality →Hierarchical Softmax
- 15:2115:21, 19 November 2015 diff hist +465 distributed Representations of Words and Phrases and their Compositionality →Introduction
- 15:0815:08, 19 November 2015 diff hist +1,284 distributed Representations of Words and Phrases and their Compositionality →Conclusion
- 15:0015:00, 19 November 2015 diff hist +982 distributed Representations of Words and Phrases and their Compositionality →Comparison to Published Word Representations
- 15:0015:00, 19 November 2015 diff hist 0 N File:Tb 6.PNG No edit summary current
- 14:5414:54, 19 November 2015 diff hist +1,358 distributed Representations of Words and Phrases and their Compositionality →Additive Compositionality
- 14:5214:52, 19 November 2015 diff hist 0 N File:Tb 5.PNG No edit summary current
- 14:4814:48, 19 November 2015 diff hist +96 distributed Representations of Words and Phrases and their Compositionality No edit summary
- 14:4714:47, 19 November 2015 diff hist +1,874 distributed Representations of Words and Phrases and their Compositionality →Learning Phrases
- 14:4614:46, 19 November 2015 diff hist 0 N File:Tb 4.PNG No edit summary current
- 14:3814:38, 19 November 2015 diff hist 0 N File:Tb 3.PNG No edit summary current
- 02:2802:28, 19 November 2015 diff hist +3,475 distributed Representations of Words and Phrases and their Compositionality No edit summary
- 02:2402:24, 19 November 2015 diff hist 0 N File:Tb 2.PNG No edit summary current
- 02:1202:12, 19 November 2015 diff hist 0 N File:Tb 1.PNG No edit summary current
- 01:0801:08, 19 November 2015 diff hist +1,083 distributed Representations of Words and Phrases and their Compositionality No edit summary
- 00:5100:51, 19 November 2015 diff hist +3,466 distributed Representations of Words and Phrases and their Compositionality No edit summary
18 November 2015
- 23:4823:48, 18 November 2015 diff hist +1,489 N distributed Representations of Words and Phrases and their Compositionality Created page with "= Introduction = This paper presents several extensions of the Skip-gram model intriduced by Mikolov et al. [8]. Skip-gram model is an efficient method for learning highquality ..."
14 November 2015
- 21:4521:45, 14 November 2015 diff hist +664 neural Turing Machines →Location-based addressing
- 21:3821:38, 14 November 2015 diff hist +127 neural Turing Machines →Content-based addressing
- 21:3621:36, 14 November 2015 diff hist +103 neural Turing Machines →Content-based addressing
- 21:3321:33, 14 November 2015 diff hist +1 neural Turing Machines →Addressing Mechanisms
- 20:5420:54, 14 November 2015 diff hist +474 neural Turing Machines →Architecture
- 20:5220:52, 14 November 2015 diff hist 0 N File:Pre 11.PNG No edit summary current
13 November 2015
- 14:2514:25, 13 November 2015 diff hist +865 deep neural networks for acoustic modeling in speech recognition →Modeling Real-Valued Data
- 14:1714:17, 13 November 2015 diff hist +435 deep neural networks for acoustic modeling in speech recognition →Generative Pretraining
- 14:0514:05, 13 November 2015 diff hist +109 deep neural networks for acoustic modeling in speech recognition →Learning Procedure for RBMs
- 14:0014:00, 13 November 2015 diff hist −105 deep neural networks for acoustic modeling in speech recognition →Learning Procedure for RBMs
- 13:5113:51, 13 November 2015 diff hist +100 question Answering with Subgraph Embeddings →Inference
- 13:4413:44, 13 November 2015 diff hist −15 question Answering with Subgraph Embeddings →Inference
- 13:4413:44, 13 November 2015 diff hist +821 question Answering with Subgraph Embeddings →Inference
- 13:3113:31, 13 November 2015 diff hist +65 neural Machine Translation: Jointly Learning to Align and Translate →Encoding
- 13:3113:31, 13 November 2015 diff hist +229 neural Machine Translation: Jointly Learning to Align and Translate →Encoding
- 13:2613:26, 13 November 2015 diff hist 0 N File:Pre 10.PNG No edit summary current
9 November 2015
- 21:0221:02, 9 November 2015 diff hist +1 stat841 →Radial Basis Function (RBF) Networks - November 6, 2009
8 November 2015
- 16:1516:15, 8 November 2015 diff hist +128 f15Stat946PaperSignUp →Set B
- 16:0216:02, 8 November 2015 diff hist 0 f15Stat946PaperSignUp →Set B
- 16:0116:01, 8 November 2015 diff hist +3 f15Stat946PaperSignUp →Set B
- 16:0016:00, 8 November 2015 diff hist +190 f15Stat946PaperSignUp →Set B
6 November 2015
- 01:5601:56, 6 November 2015 diff hist +1,092 learning Hierarchical Features for Scene Labeling →Model
- 01:4201:42, 6 November 2015 diff hist +569 learning Hierarchical Features for Scene Labeling →Model
- 00:5800:58, 6 November 2015 diff hist +62 learning Hierarchical Features for Scene Labeling →Methodology
- 00:5200:52, 6 November 2015 diff hist +32 learning Hierarchical Features for Scene Labeling →Methodology
- 00:4300:43, 6 November 2015 diff hist +709 learning Hierarchical Features for Scene Labeling →Methodology
- 00:1800:18, 6 November 2015 diff hist +420 human-level control through deep reinforcement learning →The Bellman Equation in the Loss Framework
- 00:1100:11, 6 November 2015 diff hist +204 human-level control through deep reinforcement learning →The Bellman Equation in the Loss Framework
- 00:0000:00, 6 November 2015 diff hist +121 human-level control through deep reinforcement learning →The Bellman Equation in the Loss Framework
5 November 2015
- 23:5123:51, 5 November 2015 diff hist +154 human-level control through deep reinforcement learning →The Bellman Equation in the Loss Framework
- 23:3523:35, 5 November 2015 diff hist +342 human-level control through deep reinforcement learning →Problem Description
24 October 2015
- 20:4820:48, 24 October 2015 diff hist +571 proposal for STAT946 (Deep Learning) final projects Fall 2015 No edit summary
- 19:2519:25, 24 October 2015 diff hist +8 overfeat: integrated recognition, localization and detection using convolutional networks →Localization
- 19:2519:25, 24 October 2015 diff hist +3 overfeat: integrated recognition, localization and detection using convolutional networks →Localization
23 October 2015
- 13:5013:50, 23 October 2015 diff hist +439 parsing natural scenes and natural language with recursive neural networks →Learning
- 13:4313:43, 23 October 2015 diff hist +514 parsing natural scenes and natural language with recursive neural networks →Recursive Neural Networks for Structure Prediction
- 13:3813:38, 23 October 2015 diff hist 0 N File:Im 5.PNG No edit summary current
- 13:3213:32, 23 October 2015 diff hist +318 parsing natural scenes and natural language with recursive neural networks →Recursive Neural Networks for Structure Prediction
- 06:3206:32, 23 October 2015 diff hist +749 overfeat: integrated recognition, localization and detection using convolutional networks No edit summary
- 06:2806:28, 23 October 2015 diff hist −1 overfeat: integrated recognition, localization and detection using convolutional networks →Classification
- 06:2606:26, 23 October 2015 diff hist +1,282 overfeat: integrated recognition, localization and detection using convolutional networks →Introduction
- 06:1106:11, 23 October 2015 diff hist +6 overfeat: integrated recognition, localization and detection using convolutional networks →Localization
- 06:0106:01, 23 October 2015 diff hist +2,276 overfeat: integrated recognition, localization and detection using convolutional networks No edit summary
- 05:4605:46, 23 October 2015 diff hist +2,366 overfeat: integrated recognition, localization and detection using convolutional networks No edit summary
- 05:1005:10, 23 October 2015 diff hist +3 f15Stat946PaperSignUp →Set A
- 04:5604:56, 23 October 2015 diff hist +3,844 overfeat: integrated recognition, localization and detection using convolutional networks No edit summary
- 04:4604:46, 23 October 2015 diff hist 0 N File:Im 3.PNG No edit summary current
- 04:1304:13, 23 October 2015 diff hist 0 N File:Im 2.PNG No edit summary current
- 04:0004:00, 23 October 2015 diff hist +2,272 overfeat: integrated recognition, localization and detection using convolutional networks No edit summary
- 02:5402:54, 23 October 2015 diff hist 0 N File:Im 1.PNG No edit summary current
- 02:4502:45, 23 October 2015 diff hist 0 File:Eq 1.JPG uploaded a new version of "File:Eq 1.JPG" current
- 02:4502:45, 23 October 2015 diff hist +344 overfeat: integrated recognition, localization and detection using convolutional networks No edit summary
- 02:4302:43, 23 October 2015 diff hist 0 N File:Eq 1.JPG No edit summary
- 01:5801:58, 23 October 2015 diff hist +1,858 N overfeat: integrated recognition, localization and detection using convolutional networks Created page with "= Introduction = The main point of this paper is to show that training a convolutional network to simultaneously classify, locate and detect objects in images can boost the clas..."
22 October 2015
- 23:3323:33, 22 October 2015 diff hist +246 stat946f15/Sequence to sequence learning with neural networks →Long Short-Term Memory Recurrent Neural Network (LSTM)
- 22:5822:58, 22 October 2015 diff hist +221 stat946f15/Sequence to sequence learning with neural networks →Results
- 22:1822:18, 22 October 2015 diff hist +286 stat946f15/Sequence to sequence learning with neural networks →Introduction
- 22:1022:10, 22 October 2015 diff hist +21 stat946f15/Sequence to sequence learning with neural networks →Introduction
2 October 2015
- 12:2712:27, 2 October 2015 diff hist +252 f15Stat946PaperSignUp No edit summary