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Showing below up to 50 results in range #141 to #190.

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  1. (hist) ‎meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting ‎[20,964 bytes]
  2. (hist) ‎One-Shot Imitation Learning ‎[20,785 bytes]
  3. (hist) ‎Training And Inference with Integers in Deep Neural Networks ‎[20,739 bytes]
  4. (hist) ‎learning a Nonlinear Embedding by Preserving Class Neighborhood Structure ‎[20,705 bytes]
  5. (hist) ‎Fairness Without Demographics in Repeated Loss Minimization ‎[20,361 bytes]
  6. (hist) ‎F18-STAT841-Proposal ‎[20,352 bytes]
  7. (hist) ‎Self-Supervised Learning of Pretext-Invariant Representations ‎[20,351 bytes]
  8. (hist) ‎Reinforcement Learning of Theorem Proving ‎[20,271 bytes]
  9. (hist) ‎a Direct Formulation For Sparse PCA Using Semidefinite Programming ‎[20,257 bytes]
  10. (hist) ‎deflation Methods for Sparse PCA ‎[20,218 bytes]
  11. (hist) ‎Robust Imitation of Diverse Behaviors ‎[20,150 bytes]
  12. (hist) ‎Mask RCNN ‎[20,099 bytes]
  13. (hist) ‎learning Long-Range Vision for Autonomous Off-Road Driving ‎[20,000 bytes]
  14. (hist) ‎visualizing Data using t-SNE ‎[19,850 bytes]
  15. (hist) ‎overfeat: integrated recognition, localization and detection using convolutional networks ‎[19,798 bytes]
  16. (hist) ‎stat441F18/YOLO ‎[19,690 bytes]
  17. (hist) ‎Do Deep Neural Networks Suffer from Crowding ‎[19,524 bytes]
  18. (hist) ‎PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space ‎[19,470 bytes]
  19. (hist) ‎Deep Residual Learning for Image Recognition ‎[19,366 bytes]
  20. (hist) ‎Deep Double Descent Where Bigger Models and More Data Hurt ‎[19,133 bytes]
  21. (hist) ‎stat946w18/AmbientGAN: Generative Models from Lossy Measurements ‎[19,101 bytes]
  22. (hist) ‎distributed Representations of Words and Phrases and their Compositionality ‎[19,031 bytes]
  23. (hist) ‎Understanding Image Motion with Group Representations ‎[18,990 bytes]
  24. (hist) ‎Predicting Floor Level For 911 Calls with Neural Network and Smartphone Sensor Data ‎[18,868 bytes]
  25. (hist) ‎learning Hierarchical Features for Scene Labeling ‎[18,813 bytes]
  26. (hist) ‎Learning What and Where to Draw ‎[18,801 bytes]
  27. (hist) ‎markov Random Fields for Super-Resolution ‎[18,723 bytes]
  28. (hist) ‎stat441F18/TCNLM ‎[18,699 bytes]
  29. (hist) ‎A universal SNP and small-indel variant caller using deep neural networks ‎[18,624 bytes]
  30. (hist) ‎Multi-scale Dense Networks for Resource Efficient Image Classification ‎[18,397 bytes]
  31. (hist) ‎generating text with recurrent neural networks ‎[18,394 bytes]
  32. (hist) ‎IPBoost ‎[18,321 bytes]
  33. (hist) ‎probabilistic Matrix Factorization ‎[18,287 bytes]
  34. (hist) ‎compressive Sensing ‎[18,248 bytes]
  35. (hist) ‎Synthesizing Programs for Images usingReinforced Adversarial Learning ‎[18,187 bytes]
  36. (hist) ‎Neural Audio Synthesis of Musical Notes with WaveNet autoencoders ‎[18,174 bytes]
  37. (hist) ‎stat946w18/IMPROVING GANS USING OPTIMAL TRANSPORT ‎[18,063 bytes]
  38. (hist) ‎incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains(Summary) ‎[18,023 bytes]
  39. (hist) ‎Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence ‎[17,860 bytes]
  40. (hist) ‎on the difficulty of training recurrent neural networks ‎[17,840 bytes]
  41. (hist) ‎One pixel attack for fooling deep neural networks ‎[17,832 bytes]
  42. (hist) ‎THE LOGICAL EXPRESSIVENESS OF GRAPH NEURAL NETWORKS ‎[17,773 bytes]
  43. (hist) ‎Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments ‎[17,715 bytes]
  44. (hist) ‎Pixels to Graphs by Associative Embedding ‎[17,615 bytes]
  45. (hist) ‎graphical models for structured classification, with an application to interpreting images of protein subcellular location patterns ‎[17,604 bytes]
  46. (hist) ‎multi-Task Feature Learning ‎[17,528 bytes]
  47. (hist) ‎stat946w18/Synthetic and natural noise both break neural machine translation ‎[17,403 bytes]
  48. (hist) ‎proposal for STAT946 projects Fall 2010 ‎[17,366 bytes]
  49. (hist) ‎Influenza Forecasting Framework based on Gaussian Processes ‎[17,358 bytes]
  50. (hist) ‎F18-STAT946-Proposal ‎[17,305 bytes]

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