Short pages

Showing below up to 250 results in range #1 to #250.

1. (hist) ‎tRIAL for that odd behaviour ‎[0 bytes]
2. (hist) ‎Curiosity-driven Exploration by Self-supervised Prediction ‎[0 bytes]
3. (hist) ‎STAT946F17/ Dance Dance Convolution ‎[0 bytes]
4. (hist) ‎Influenza Forecasting Framework based on Gaussian processes Summary ‎[4 bytes]
5. (hist) ‎stat946w18/Hierarchical Representations for Efficient Architecture Search ‎[11 bytes]
6. (hist) ‎stat946f15/Deep neural networks for acoustic modeling in speech recognition ‎[16 bytes]
7. (hist) ‎Improving neural networks by preventing co-adaption of feature detectors 2020 Fall ‎[16 bytes]
8. (hist) ‎video-Based Face Recognition Using Adaptive Hidden Markov Models ‎[17 bytes]
9. (hist) ‎ModelFramework.jpg ‎[27 bytes]
10. (hist) ‎maximum Variance Unfolding (June 2 2009) ‎[34 bytes]
11. (hist) ‎monte Carlo methods ‎[36 bytes]
12. (hist) ‎time-series-using-GAN ‎[44 bytes]
13. (hist) ‎sandbox to test w2l ‎[54 bytes]
14. (hist) ‎stat946w18/ ‎[72 bytes]
15. (hist) ‎ALBERT ‎[76 bytes]
16. (hist) ‎wikicoursenote:Manual of Style ‎[82 bytes]
17. (hist) ‎Don't Just Blame Over-parametrization Summary ‎[89 bytes]
18. (hist) ‎mark Your Contribution here ‎[107 bytes]
19. (hist) ‎mark your contribution here ‎[107 bytes]
20. (hist) ‎stat946-Fall 2010 ‎[112 bytes]
21. (hist) ‎stat946F20/GradientLess Descent ‎[137 bytes]
22. (hist) ‎stat946f15 ‎[198 bytes]
23. (hist) ‎link to my paper ‎[204 bytes]
24. (hist) ‎stat946f17 ‎[215 bytes]
25. (hist) ‎13Stat946papers ‎[234 bytes]
26. (hist) ‎test1 ‎[255 bytes]
27. (hist) ‎infoboxtest ‎[260 bytes]
28. (hist) ‎Proposal for STAT946 (Deep Learning) final projects Fall 2017 ‎[331 bytes]
29. (hist) ‎deepGenerativeModels ‎[466 bytes]
30. (hist) ‎f11stat946EditorSignUp ‎[501 bytes]
31. (hist) ‎wikicoursenote:cleanup ‎[551 bytes]
32. (hist) ‎Bsodjahi ‎[759 bytes]
33. (hist) ‎Deep Transfer Learning with Joint Adaptation Networks ‎[760 bytes]
34. (hist) ‎statf10841Scribe ‎[814 bytes]
35. (hist) ‎learning2reasoning ‎[852 bytes]
36. (hist) ‎schedule ‎[918 bytes]
37. (hist) ‎f11Stat946papers ‎[941 bytes]
38. (hist) ‎singular Value Decomposition(SVD) ‎[1,085 bytes]
39. (hist) ‎proof of Theorem 1 ‎[1,140 bytes]
40. (hist) ‎f11Stat841EditorSignUp ‎[1,220 bytes]
41. (hist) ‎schedule of Project Presentations ‎[1,236 bytes]
42. (hist) ‎f14Stat842EditorSignUp ‎[1,238 bytes]
43. (hist) ‎schedule946 ‎[1,494 bytes]
44. (hist) ‎Meta-Learning-For-Domain Generalization ‎[1,514 bytes]
45. (hist) ‎statf09841Scribe ‎[1,515 bytes]
46. (hist) ‎Imagination Augmented Agents for Deep Reinforcement Learning ‎[1,575 bytes]
47. (hist) ‎deflation Method for Penalized Matrix Decomposition Sparse PCA ‎[1,621 bytes]
48. (hist) ‎f11Stat841presentation ‎[1,695 bytes]
49. (hist) ‎signupformStat341F11 ‎[1,775 bytes]
50. (hist) ‎paper Summaries ‎[2,022 bytes]
51. (hist) ‎Pre-Training-Tasks-For-Embedding-Based-Large-Scale-Retrieval ‎[2,068 bytes]
52. (hist) ‎importance Sampling June 2 2009 ‎[2,099 bytes]
53. (hist) ‎is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction ‎[2,146 bytes]
54. (hist) ‎proof of Lemma 1 ‎[2,150 bytes]
55. (hist) ‎proof ‎[3,086 bytes]
56. (hist) ‎f11Stat946presentation ‎[3,162 bytes]
57. (hist) ‎contributions on Video-Based Face Recognition Using Adaptive Hidden Markov Models ‎[3,211 bytes]
58. (hist) ‎a Dynamic Bayesian Network Click Model for web search ranking ‎[3,492 bytes]
59. (hist) ‎Traffic Sign Recognition System (TSRS): SVM and Convolutional Neural Network ‎[3,643 bytes]
60. (hist) ‎measuring and testing dependence by correlation of distances ‎[3,675 bytes]
61. (hist) ‎Hash Embeddings for Efficient Word Representations ‎[3,841 bytes]
62. (hist) ‎sign up for your presentation ‎[4,160 bytes]
63. (hist) ‎Batch Normalization Summary ‎[4,283 bytes]
64. (hist) ‎markov Chain Definitions ‎[4,619 bytes]
65. (hist) ‎stat940F21 ‎[4,782 bytes]
66. (hist) ‎stat441w18/summary 1 ‎[4,834 bytes]
67. (hist) ‎binomial Probability Monte Carlo Sampling June 2 2009 ‎[4,964 bytes]
68. (hist) ‎main Page ‎[5,022 bytes]
69. (hist) ‎copyofstat341 ‎[5,050 bytes]
70. (hist) ‎Task Understanding from Confushing Multitask Data ‎[5,085 bytes]
71. (hist) ‎monte Carlo Integration ‎[5,183 bytes]
72. (hist) ‎stat441w18 ‎[5,299 bytes]
73. (hist) ‎acceptance-Rejection Sampling ‎[5,779 bytes]
74. (hist) ‎bayesian and Frequentist Schools of Thought ‎[5,797 bytes]
75. (hist) ‎stat441F18 ‎[6,075 bytes]
76. (hist) ‎Batch Normalization ‎[6,084 bytes]
77. (hist) ‎a Deeper Look into Importance Sampling ‎[6,315 bytes]
78. (hist) ‎s13Stat946proposal ‎[6,364 bytes]
79. (hist) ‎the Indian Buffet Process: An Introduction and Review ‎[6,413 bytes]
80. (hist) ‎importance Sampling and Markov Chain Monte Carlo (MCMC) ‎[6,450 bytes]
81. (hist) ‎genetics ‎[6,457 bytes]
82. (hist) ‎Deep Learning for Extreme Multi-label Text Classification ‎[6,578 bytes]
83. (hist) ‎metric and Kernel Learning Using a Linear Transformation ‎[6,583 bytes]
84. (hist) ‎Deep Residual Learning for Image Recognition Summary ‎[6,589 bytes]
85. (hist) ‎kernel Dimension Reduction in Regression ‎[6,640 bytes]
86. (hist) ‎nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization ‎[6,730 bytes]
87. (hist) ‎again on Markov Chain ‎[6,938 bytes]
88. (hist) ‎Convolutional neural network for diagnosis of viral pneumonia and COVID-19 alike diseases ‎[6,985 bytes]
89. (hist) ‎Convolutional Neural Networks for Sentence Classification ‎[7,012 bytes]
90. (hist) ‎techniques for Normal and Gamma Sampling ‎[7,262 bytes]
91. (hist) ‎large-Scale Supervised Sparse Principal Component Analysis ‎[7,419 bytes]
92. (hist) ‎importance Sampling and Monte Carlo Simulation ‎[7,462 bytes]
93. (hist) ‎proposal for STAT946 (Deep Learning) final projects Fall 2015 ‎[7,533 bytes]
94. (hist) ‎Wide and Deep Learning for Recommender Systems ‎[7,762 bytes]
95. (hist) ‎measuring statistical dependence with Hilbert-Schmidt norms ‎[7,804 bytes]
96. (hist) ‎U-Time:A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging Summary ‎[8,051 bytes]
97. (hist) ‎contributions on Context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis ‎[8,071 bytes]
98. (hist) ‎Bayesian Network as a Decision Tool for Predicting ALS Disease ‎[8,088 bytes]
99. (hist) ‎hierarchical Dirichlet Processes ‎[8,178 bytes]
100. (hist) ‎on the Number of Linear Regions of Deep Neural Networks ‎[8,398 bytes]
101. (hist) ‎generating Random Numbers ‎[8,400 bytes]
102. (hist) ‎deep Learning of the tissue-regulated splicing code ‎[8,523 bytes]
103. (hist) ‎Unsupervised Machine Translation Using Monolingual Corpora Only ‎[8,547 bytes]
104. (hist) ‎stat441F21 ‎[8,574 bytes]
105. (hist) ‎Dynamic Routing Between Capsulesl ‎[8,625 bytes]
106. (hist) ‎a Rank Minimization Heuristic with Application to Minimum Order System Approximation ‎[8,679 bytes]
107. (hist) ‎adaptive dimension reduction for clustering high dimensional data ‎[8,820 bytes]
108. (hist) ‎decentralised Data Fusion: A Graphical Model Approach (Summary) ‎[8,861 bytes]
109. (hist) ‎STAT946F20/BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding ‎[8,936 bytes]
110. (hist) ‎deep Sparse Rectifier Neural Networks ‎[8,983 bytes]
111. (hist) ‎cardinality Restricted Boltzmann Machines ‎[9,174 bytes]
112. (hist) ‎parametric Local Metric Learning for Nearest Neighbor Classification ‎[9,358 bytes]
113. (hist) ‎Research on Multiple Classification Based on Improved SVM Algorithm for Balanced Binary Decision Tree ‎[9,395 bytes]
114. (hist) ‎Robust Probabilistic Modeling with Bayesian Data Reweighting ‎[9,400 bytes]
115. (hist) ‎positive Semidefinite Metric Learning Using Boosting-like Algorithms ‎[9,507 bytes]
116. (hist) ‎stat946w18 ‎[9,537 bytes]
117. (hist) ‎Don't Just Blame Over-parametrization ‎[9,544 bytes]
118. (hist) ‎Going Deeper with Convolutions ‎[9,580 bytes]
119. (hist) ‎strategies for Training Large Scale Neural Network Language Models ‎[9,641 bytes]
120. (hist) ‎semi-supervised Learning with Deep Generative Models ‎[9,651 bytes]
121. (hist) ‎video-based face recognition using Adaptive HMM ‎[9,786 bytes]
122. (hist) ‎Another look at distance-weighted discrimination ‎[9,801 bytes]
123. (hist) ‎test ‎[9,812 bytes]
124. (hist) ‎This Looks Like That: Deep Learning for Interpretable Image Recognition ‎[9,951 bytes]
125. (hist) ‎f17Stat946PaperSignUp ‎[9,982 bytes]
126. (hist) ‎Depthwise Convolution Is All You Need for Learning Multiple Visual Domains ‎[10,043 bytes]
127. (hist) ‎kernel Spectral Clustering for Community Detection in Complex Networks ‎[10,246 bytes]
128. (hist) ‎context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis ‎[10,381 bytes]
129. (hist) ‎stat841F18/ ‎[10,578 bytes]
130. (hist) ‎Learning The Difference That Makes A Difference With Counterfactually-Augmented Data ‎[10,629 bytes]
131. (hist) ‎hamming Distance Metric Learning ‎[10,708 bytes]
132. (hist) ‎Representations of Words and Phrases and their Compositionality ‎[10,739 bytes]
133. (hist) ‎Poison Frogs Neural Networks ‎[10,842 bytes]
134. (hist) ‎deep Convolutional Neural Networks For LVCSR ‎[10,860 bytes]
135. (hist) ‎mULTIPLE OBJECT RECOGNITION WITH VISUAL ATTENTION ‎[10,935 bytes]
136. (hist) ‎a Dynamic Bayesian Network Click Model for Web Search Ranking ‎[10,982 bytes]
137. (hist) ‎Augmix: New Data Augmentation method to increase the robustness of the algorithm ‎[11,257 bytes]
138. (hist) ‎A Knowledge-Grounded Neural Conversation Model ‎[11,272 bytes]
139. (hist) ‎A Game Theoretic Approach to Class-wise Selective Rationalization ‎[11,317 bytes]
140. (hist) ‎very Deep Convoloutional Networks for Large-Scale Image Recognition ‎[11,457 bytes]
141. (hist) ‎GradientLess Descent ‎[11,517 bytes]
142. (hist) ‎f15Stat946PaperSignUp ‎[11,589 bytes]
143. (hist) ‎maximum-Margin Matrix Factorization ‎[11,779 bytes]
144. (hist) ‎deep Generative Stochastic Networks Trainable by Backprop ‎[11,830 bytes]
145. (hist) ‎nonparametric Latent Feature Models for Link Prediction ‎[11,861 bytes]
146. (hist) ‎learning Phrase Representations ‎[11,920 bytes]
147. (hist) ‎graph Laplacian Regularization for Larg-Scale Semidefinite Programming ‎[11,952 bytes]
148. (hist) ‎neural Turing Machines ‎[11,991 bytes]
149. (hist) ‎CRITICAL ANALYSIS OF SELF-SUPERVISION ‎[11,995 bytes]
150. (hist) ‎stat441w18/Saliency-based Sequential Image Attention with Multiset Prediction ‎[12,037 bytes]
151. (hist) ‎self-Taught Learning ‎[12,049 bytes]
152. (hist) ‎F21-STAT 441/841 CM 763-Proposal ‎[12,049 bytes]
153. (hist) ‎a fast learning algorithm for deep belief nets ‎[12,051 bytes]
154. (hist) ‎Learning Combinatorial Optimzation ‎[12,086 bytes]
155. (hist) ‎joint training of a convolutional network and a graphical model for human pose estimation ‎[12,149 bytes]
156. (hist) ‎show, Attend and Tell: Neural Image Caption Generation with Visual Attention ‎[12,161 bytes]
157. (hist) ‎learning Convolutional Feature Hierarchies for Visual Recognition ‎[12,276 bytes]
158. (hist) ‎Predicting Hurricane Trajectories Using a Recurrent Neural Network ‎[12,277 bytes]
159. (hist) ‎scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers Machines ‎[12,303 bytes]
160. (hist) ‎Automatic Bank Fraud Detection Using Support Vector Machines ‎[12,303 bytes]
161. (hist) ‎The Detection of Black Ice Accidents Using CNNs ‎[12,531 bytes]
162. (hist) ‎Memory-Based Parameter Adaptation ‎[12,660 bytes]
163. (hist) ‎summary ‎[12,663 bytes]
164. (hist) ‎an HDP-HMM for Systems with State Persistence ‎[12,699 bytes]
165. (hist) ‎On The Convergence Of ADAM And Beyond ‎[12,957 bytes]
166. (hist) ‎paper 13 ‎[12,976 bytes]
167. (hist) ‎Do Vision Transformers See Like CNN ‎[13,013 bytes]
168. (hist) ‎imageNet Classification with Deep Convolutional Neural Networks ‎[13,183 bytes]
169. (hist) ‎natural language processing (almost) from scratch. ‎[13,194 bytes]
170. (hist) ‎Gradient Episodic Memory for Continual Learning ‎[13,341 bytes]
171. (hist) ‎stat946w18/Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolutional Layers ‎[13,361 bytes]
172. (hist) ‎Streaming Bayesian Inference for Crowdsourced Classification ‎[13,491 bytes]
173. (hist) ‎the loss surfaces of multilayer networks (Choromanska et al.) ‎[13,493 bytes]
174. (hist) ‎Robust Imitation Learning from Noisy Demonstrations ‎[13,516 bytes]
175. (hist) ‎sparse PCA ‎[13,535 bytes]
176. (hist) ‎The Curious Case of Degeneration ‎[13,571 bytes]
177. (hist) ‎compressive Sensing (Candes) ‎[13,587 bytes]
178. (hist) ‎dropout ‎[13,614 bytes]
179. (hist) ‎stat441w18/A New Method of Region Embedding for Text Classification ‎[13,622 bytes]
180. (hist) ‎F21-STAT 940-Proposal ‎[13,656 bytes]
181. (hist) ‎DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION ‎[13,738 bytes]
182. (hist) ‎dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces ‎[13,891 bytes]
183. (hist) ‎stat946F18 ‎[13,896 bytes]
184. (hist) ‎stat946w18/Predicting Floor-Level for 911 Calls with Neural Networks and Smartphone Sensor Data ‎[13,936 bytes]
185. (hist) ‎ALBERT: A Lite BERT for Self-supervised Learning of Language Representations ‎[13,956 bytes]
186. (hist) ‎f11Stat946ass ‎[13,980 bytes]
187. (hist) ‎neural Machine Translation: Jointly Learning to Align and Translate ‎[14,061 bytes]
188. (hist) ‎residual Component Analysis: Generalizing PCA for more flexible inference in linear-Gaussian models ‎[14,327 bytes]
189. (hist) ‎matrix Completion with Noise ‎[14,449 bytes]
190. (hist) ‎STAT946F17/ Learning Important Features Through Propagating Activation Differences ‎[14,579 bytes]
191. (hist) ‎on using very large target vocabulary for neural machine translation ‎[14,589 bytes]
192. (hist) ‎stat441w18/mastering-chess-and-shogi-self-play ‎[14,596 bytes]
193. (hist) ‎Meta-Learning For Domain Generalization ‎[14,600 bytes]
194. (hist) ‎extracting and Composing Robust Features with Denoising Autoencoders ‎[14,613 bytes]
195. (hist) ‎Roberta ‎[14,722 bytes]
196. (hist) ‎Dynamic Routing Between Capsules ‎[14,778 bytes]
197. (hist) ‎Towards Deep Learning Models Resistant to Adversarial Attacks ‎[14,812 bytes]
198. (hist) ‎visualizing Similarity Data with a Mixture of Maps ‎[14,886 bytes]
199. (hist) ‎Breaking Certified Defenses: Semantic Adversarial Examples With Spoofed Robustness Certificates ‎[14,911 bytes]
200. (hist) ‎XGBoost: A Scalable Tree Boosting System ‎[15,042 bytes]
201. (hist) ‎contributions on Quantifying Cancer Progression with Conjunctive Bayesian Networks ‎[15,193 bytes]
202. (hist) ‎quantifying cancer progression with conjunctive Bayesian networks. ‎[15,204 bytes]
203. (hist) ‎goingDeeperWithConvolutions ‎[15,240 bytes]
204. (hist) ‎continuous space language models ‎[15,275 bytes]
205. (hist) ‎question Answering with Subgraph Embeddings ‎[15,293 bytes]
206. (hist) ‎quantifying cancer progression with conjunctive Bayesian networks ‎[15,306 bytes]
207. (hist) ‎Semantic Relation Classification——via Convolution Neural Network ‎[15,324 bytes]
208. (hist) ‎Wavelet Pooling CNN ‎[15,345 bytes]
209. (hist) ‎orthogonal gradient descent for continual learning ‎[15,363 bytes]
210. (hist) ‎maximum likelihood estimation of intrinsic dimension ‎[15,392 bytes]
211. (hist) ‎Model Agnostic Learning of Semantic Features ‎[15,514 bytes]
212. (hist) ‎independent Component Analysis: algorithms and applications ‎[15,526 bytes]
213. (hist) ‎statf09841Proposal ‎[15,646 bytes]
214. (hist) ‎stat441w18/e-gan ‎[15,651 bytes]
215. (hist) ‎Co-Teaching ‎[15,712 bytes]
216. (hist) ‎rOBPCA: A New Approach to Robust Principal Component Analysis ‎[15,775 bytes]
217. (hist) ‎From Variational to Deterministic Autoencoders ‎[15,837 bytes]
218. (hist) ‎Extreme Multi-label Text Classification ‎[15,848 bytes]
219. (hist) ‎proposal for STAT946 projects ‎[15,862 bytes]
220. (hist) ‎neighbourhood Components Analysis ‎[15,899 bytes]
221. (hist) ‎a fair comparison of graph neural networks for graph classification ‎[15,982 bytes]
222. (hist) ‎Patch Based Convolutional Neural Network for Whole Slide Tissue Image Classification ‎[16,111 bytes]
223. (hist) ‎the Wake-Sleep Algorithm for Unsupervised Neural Networks ‎[16,139 bytes]
224. (hist) ‎kernelized Sorting ‎[16,226 bytes]
225. (hist) ‎parsing natural scenes and natural language with recursive neural networks ‎[16,235 bytes]
226. (hist) ‎Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness ‎[16,296 bytes]
227. (hist) ‎stat946w18/Spectral normalization for generative adversial network ‎[16,342 bytes]
228. (hist) ‎STAT946F17/ Automated Curriculum Learning for Neural Networks ‎[16,391 bytes]
229. (hist) ‎inductive Kernel Low-rank Decomposition with Priors: A Generalized Nystrom Method ‎[16,450 bytes]
230. (hist) ‎SuperGLUE ‎[16,457 bytes]
231. (hist) ‎DeepVO Towards end to end visual odometry with deep RNN ‎[16,676 bytes]
232. (hist) ‎stat946w18/Implicit Causal Models for Genome-wide Association Studies ‎[16,805 bytes]
233. (hist) ‎Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition ‎[16,892 bytes]
234. (hist) ‎When Does Self-Supervision Improve Few-Shot Learning? ‎[16,936 bytes]
235. (hist) ‎CatBoost: unbiased boosting with categorical features ‎[17,013 bytes]
236. (hist) ‎kernelized Locality-Sensitive Hashing ‎[17,115 bytes]
237. (hist) ‎Dense Passage Retrieval for Open-Domain Question Answering ‎[17,125 bytes]
238. (hist) ‎BERTScore: Evaluating Text Generation with BERT ‎[17,132 bytes]
239. (hist) ‎discLDA: Discriminative Learning for Dimensionality Reduction and Classification ‎[17,184 bytes]
240. (hist) ‎deep Neural Nets as a Method for Quantitative Structure–Activity Relationships ‎[17,219 bytes]
241. (hist) ‎F18-STAT946-Proposal ‎[17,305 bytes]
242. (hist) ‎Influenza Forecasting Framework based on Gaussian Processes ‎[17,358 bytes]
243. (hist) ‎proposal for STAT946 projects Fall 2010 ‎[17,366 bytes]
244. (hist) ‎stat946w18/Synthetic and natural noise both break neural machine translation ‎[17,403 bytes]
245. (hist) ‎multi-Task Feature Learning ‎[17,528 bytes]
246. (hist) ‎graphical models for structured classification, with an application to interpreting images of protein subcellular location patterns ‎[17,604 bytes]
247. (hist) ‎Pixels to Graphs by Associative Embedding ‎[17,615 bytes]
248. (hist) ‎Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments ‎[17,715 bytes]
249. (hist) ‎THE LOGICAL EXPRESSIVENESS OF GRAPH NEURAL NETWORKS ‎[17,773 bytes]
250. (hist) ‎One pixel attack for fooling deep neural networks ‎[17,832 bytes]