Short pages

Showing below up to 100 results in range #1 to #100.

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]