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Showing below up to 100 results in range #151 to #250.

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  1. (hist) ‎self-Taught Learning ‎[12,049 bytes]
  2. (hist) ‎F21-STAT 441/841 CM 763-Proposal ‎[12,049 bytes]
  3. (hist) ‎a fast learning algorithm for deep belief nets ‎[12,051 bytes]
  4. (hist) ‎Learning Combinatorial Optimzation ‎[12,086 bytes]
  5. (hist) ‎joint training of a convolutional network and a graphical model for human pose estimation ‎[12,149 bytes]
  6. (hist) ‎show, Attend and Tell: Neural Image Caption Generation with Visual Attention ‎[12,161 bytes]
  7. (hist) ‎learning Convolutional Feature Hierarchies for Visual Recognition ‎[12,276 bytes]
  8. (hist) ‎Predicting Hurricane Trajectories Using a Recurrent Neural Network ‎[12,277 bytes]
  9. (hist) ‎scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers Machines ‎[12,303 bytes]
  10. (hist) ‎Automatic Bank Fraud Detection Using Support Vector Machines ‎[12,303 bytes]
  11. (hist) ‎The Detection of Black Ice Accidents Using CNNs ‎[12,531 bytes]
  12. (hist) ‎Memory-Based Parameter Adaptation ‎[12,660 bytes]
  13. (hist) ‎summary ‎[12,663 bytes]
  14. (hist) ‎an HDP-HMM for Systems with State Persistence ‎[12,699 bytes]
  15. (hist) ‎On The Convergence Of ADAM And Beyond ‎[12,957 bytes]
  16. (hist) ‎paper 13 ‎[12,976 bytes]
  17. (hist) ‎Do Vision Transformers See Like CNN ‎[13,013 bytes]
  18. (hist) ‎imageNet Classification with Deep Convolutional Neural Networks ‎[13,183 bytes]
  19. (hist) ‎natural language processing (almost) from scratch. ‎[13,194 bytes]
  20. (hist) ‎Gradient Episodic Memory for Continual Learning ‎[13,341 bytes]
  21. (hist) ‎stat946w18/Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolutional Layers ‎[13,361 bytes]
  22. (hist) ‎Streaming Bayesian Inference for Crowdsourced Classification ‎[13,491 bytes]
  23. (hist) ‎the loss surfaces of multilayer networks (Choromanska et al.) ‎[13,493 bytes]
  24. (hist) ‎Robust Imitation Learning from Noisy Demonstrations ‎[13,516 bytes]
  25. (hist) ‎sparse PCA ‎[13,535 bytes]
  26. (hist) ‎The Curious Case of Degeneration ‎[13,571 bytes]
  27. (hist) ‎compressive Sensing (Candes) ‎[13,587 bytes]
  28. (hist) ‎dropout ‎[13,614 bytes]
  29. (hist) ‎stat441w18/A New Method of Region Embedding for Text Classification ‎[13,622 bytes]
  30. (hist) ‎F21-STAT 940-Proposal ‎[13,656 bytes]
  31. (hist) ‎DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION ‎[13,738 bytes]
  32. (hist) ‎dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces ‎[13,891 bytes]
  33. (hist) ‎stat946F18 ‎[13,896 bytes]
  34. (hist) ‎stat946w18/Predicting Floor-Level for 911 Calls with Neural Networks and Smartphone Sensor Data ‎[13,936 bytes]
  35. (hist) ‎ALBERT: A Lite BERT for Self-supervised Learning of Language Representations ‎[13,956 bytes]
  36. (hist) ‎f11Stat946ass ‎[13,980 bytes]
  37. (hist) ‎neural Machine Translation: Jointly Learning to Align and Translate ‎[14,061 bytes]
  38. (hist) ‎residual Component Analysis: Generalizing PCA for more flexible inference in linear-Gaussian models ‎[14,327 bytes]
  39. (hist) ‎matrix Completion with Noise ‎[14,449 bytes]
  40. (hist) ‎STAT946F17/ Learning Important Features Through Propagating Activation Differences ‎[14,579 bytes]
  41. (hist) ‎on using very large target vocabulary for neural machine translation ‎[14,589 bytes]
  42. (hist) ‎stat441w18/mastering-chess-and-shogi-self-play ‎[14,596 bytes]
  43. (hist) ‎Meta-Learning For Domain Generalization ‎[14,600 bytes]
  44. (hist) ‎extracting and Composing Robust Features with Denoising Autoencoders ‎[14,613 bytes]
  45. (hist) ‎Roberta ‎[14,722 bytes]
  46. (hist) ‎Dynamic Routing Between Capsules ‎[14,778 bytes]
  47. (hist) ‎Towards Deep Learning Models Resistant to Adversarial Attacks ‎[14,812 bytes]
  48. (hist) ‎visualizing Similarity Data with a Mixture of Maps ‎[14,886 bytes]
  49. (hist) ‎Breaking Certified Defenses: Semantic Adversarial Examples With Spoofed Robustness Certificates ‎[14,911 bytes]
  50. (hist) ‎XGBoost: A Scalable Tree Boosting System ‎[15,042 bytes]
  51. (hist) ‎contributions on Quantifying Cancer Progression with Conjunctive Bayesian Networks ‎[15,193 bytes]
  52. (hist) ‎quantifying cancer progression with conjunctive Bayesian networks. ‎[15,204 bytes]
  53. (hist) ‎goingDeeperWithConvolutions ‎[15,240 bytes]
  54. (hist) ‎continuous space language models ‎[15,275 bytes]
  55. (hist) ‎question Answering with Subgraph Embeddings ‎[15,293 bytes]
  56. (hist) ‎quantifying cancer progression with conjunctive Bayesian networks ‎[15,306 bytes]
  57. (hist) ‎Semantic Relation Classification——via Convolution Neural Network ‎[15,324 bytes]
  58. (hist) ‎Wavelet Pooling CNN ‎[15,345 bytes]
  59. (hist) ‎orthogonal gradient descent for continual learning ‎[15,363 bytes]
  60. (hist) ‎maximum likelihood estimation of intrinsic dimension ‎[15,392 bytes]
  61. (hist) ‎Model Agnostic Learning of Semantic Features ‎[15,514 bytes]
  62. (hist) ‎independent Component Analysis: algorithms and applications ‎[15,526 bytes]
  63. (hist) ‎statf09841Proposal ‎[15,646 bytes]
  64. (hist) ‎stat441w18/e-gan ‎[15,651 bytes]
  65. (hist) ‎Co-Teaching ‎[15,712 bytes]
  66. (hist) ‎rOBPCA: A New Approach to Robust Principal Component Analysis ‎[15,775 bytes]
  67. (hist) ‎From Variational to Deterministic Autoencoders ‎[15,837 bytes]
  68. (hist) ‎Extreme Multi-label Text Classification ‎[15,848 bytes]
  69. (hist) ‎proposal for STAT946 projects ‎[15,862 bytes]
  70. (hist) ‎neighbourhood Components Analysis ‎[15,899 bytes]
  71. (hist) ‎a fair comparison of graph neural networks for graph classification ‎[15,982 bytes]
  72. (hist) ‎Patch Based Convolutional Neural Network for Whole Slide Tissue Image Classification ‎[16,111 bytes]
  73. (hist) ‎the Wake-Sleep Algorithm for Unsupervised Neural Networks ‎[16,139 bytes]
  74. (hist) ‎kernelized Sorting ‎[16,226 bytes]
  75. (hist) ‎parsing natural scenes and natural language with recursive neural networks ‎[16,235 bytes]
  76. (hist) ‎Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness ‎[16,296 bytes]
  77. (hist) ‎stat946w18/Spectral normalization for generative adversial network ‎[16,342 bytes]
  78. (hist) ‎STAT946F17/ Automated Curriculum Learning for Neural Networks ‎[16,391 bytes]
  79. (hist) ‎inductive Kernel Low-rank Decomposition with Priors: A Generalized Nystrom Method ‎[16,450 bytes]
  80. (hist) ‎SuperGLUE ‎[16,457 bytes]
  81. (hist) ‎DeepVO Towards end to end visual odometry with deep RNN ‎[16,676 bytes]
  82. (hist) ‎stat946w18/Implicit Causal Models for Genome-wide Association Studies ‎[16,805 bytes]
  83. (hist) ‎Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition ‎[16,892 bytes]
  84. (hist) ‎When Does Self-Supervision Improve Few-Shot Learning? ‎[16,936 bytes]
  85. (hist) ‎CatBoost: unbiased boosting with categorical features ‎[17,013 bytes]
  86. (hist) ‎kernelized Locality-Sensitive Hashing ‎[17,115 bytes]
  87. (hist) ‎Dense Passage Retrieval for Open-Domain Question Answering ‎[17,125 bytes]
  88. (hist) ‎BERTScore: Evaluating Text Generation with BERT ‎[17,132 bytes]
  89. (hist) ‎discLDA: Discriminative Learning for Dimensionality Reduction and Classification ‎[17,184 bytes]
  90. (hist) ‎deep Neural Nets as a Method for Quantitative Structure–Activity Relationships ‎[17,219 bytes]
  91. (hist) ‎F18-STAT946-Proposal ‎[17,305 bytes]
  92. (hist) ‎Influenza Forecasting Framework based on Gaussian Processes ‎[17,358 bytes]
  93. (hist) ‎proposal for STAT946 projects Fall 2010 ‎[17,366 bytes]
  94. (hist) ‎stat946w18/Synthetic and natural noise both break neural machine translation ‎[17,403 bytes]
  95. (hist) ‎multi-Task Feature Learning ‎[17,528 bytes]
  96. (hist) ‎graphical models for structured classification, with an application to interpreting images of protein subcellular location patterns ‎[17,604 bytes]
  97. (hist) ‎Pixels to Graphs by Associative Embedding ‎[17,615 bytes]
  98. (hist) ‎Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments ‎[17,715 bytes]
  99. (hist) ‎THE LOGICAL EXPRESSIVENESS OF GRAPH NEURAL NETWORKS ‎[17,773 bytes]
  100. (hist) ‎One pixel attack for fooling deep neural networks ‎[17,832 bytes]

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