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

1. "Why Should I Trust You?": Explaining the Predictions of Any Classifier
2. 13Stat946papers
3. ALBERT
4. ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
5. A Bayesian Perspective on Generalization and Stochastic Gradient Descent
6. A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques
7. A Game Theoretic Approach to Class-wise Selective Rationalization
8. A Knowledge-Grounded Neural Conversation Model
9. A Neural Representation of Sketch Drawings
10. A universal SNP and small-indel variant caller using deep neural networks
11. Adacompress: Adaptive compression for online computer vision services
12. Adversarial Attacks on Copyright Detection Systems
13. Adversarial Fisher Vectors for Unsupervised Representation Learning
14. Annotating Object Instances with a Polygon RNN
15. Another look at distance-weighted discrimination
16. Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin
17. Augmix: New Data Augmentation method to increase the robustness of the algorithm
18. Automatic Bank Fraud Detection Using Support Vector Machines
19. BERTScore: Evaluating Text Generation with BERT
20. Bag of Tricks for Efficient Text Classification
21. Batch Normalization
22. Batch Normalization Summary
23. Bayesian Network as a Decision Tool for Predicting ALS Disease
24. Being Bayesian about Categorical Probability
25. Breaking Certified Defenses: Semantic Adversarial Examples With Spoofed Robustness Certificates
26. Breaking the Softmax Bottleneck: A High-Rank RNN Language Model
27. Bsodjahi
28. CRITICAL ANALYSIS OF SELF-SUPERVISION
29. CapsuleNets
30. CatBoost: unbiased boosting with categorical features
31. Co-Teaching
32. Conditional Image Synthesis with Auxiliary Classifier GANs
33. Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
34. Convolutional Neural Networks for Sentence Classification
35. Convolutional Sequence to Sequence Learning
36. Convolutional neural network for diagnosis of viral pneumonia and COVID-19 alike diseases
37. Countering Adversarial Images Using Input Transformations
38. Curiosity-driven Exploration by Self-supervised Prediction
39. DCN plus: Mixed Objective And Deep Residual Coattention for Question Answering
40. DETECTING STATISTICAL INTERACTIONS FROM NEURAL NETWORK WEIGHTS
41. DON'T DECAY THE LEARNING RATE , INCREASE THE BATCH SIZE
42. DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION
43. DeepVO Towards end to end visual odometry with deep RNN
44. Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition
45. Deep Double Descent Where Bigger Models and More Data Hurt
46. Deep Exploration via Bootstrapped DQN
47. Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms
48. Deep Learning for Extreme Multi-label Text Classification
49. Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling
50. Deep Residual Learning for Image Recognition
51. Deep Residual Learning for Image Recognition Summary
52. Deep Transfer Learning with Joint Adaptation Networks
53. Dense Passage Retrieval for Open-Domain Question Answering
54. Depthwise Convolution Is All You Need for Learning Multiple Visual Domains
55. Describtion of Text Mining
56. Dialog-based Language Learning
57. Do Deep Neural Networks Suffer from Crowding
58. Do Vision Transformers See Like CNN
59. Don't Just Blame Over-parametrization
60. Don't Just Blame Over-parametrization Summary
61. Dynamic Routing Between Capsules
62. Dynamic Routing Between Capsules STAT946
63. Dynamic Routing Between Capsulesl
64. Efficient kNN Classification with Different Numbers of Nearest Neighbors
65. End-to-End Differentiable Adversarial Imitation Learning
66. End to end Active Object Tracking via Reinforcement Learning
67. Evaluating Machine Accuracy on ImageNet
68. Extreme Multi-label Text Classification
69. F18-STAT841-Proposal
70. F18-STAT946-Proposal
71. F21-STAT 441/841 CM 763-Proposal
72. F21-STAT 940-Proposal
73. Fairness Without Demographics in Repeated Loss Minimization
74. FeUdal Networks for Hierarchical Reinforcement Learning
75. Fix your classifier: the marginal value of training the last weight layer
76. From Variational to Deterministic Autoencoders
77. Functional regularisation for continual learning with gaussian processes
78. Generating Image Descriptions
79. Going Deeper with Convolutions
80. GradientLess Descent
81. Gradient Episodic Memory for Continual Learning
82. Graph Structure of Neural Networks
83. Hash Embeddings for Efficient Word Representations
84. Hierarchical Question-Image Co-Attention for Visual Question Answering
85. Hierarchical Representations for Efficient Architecture Search
86. IPBoost
87. Imagination-Augmented Agents for Deep Reinforcement Learning
88. Imagination Augmented Agents for Deep Reinforcement Learning
89. Improving neural networks by preventing co-adaption of feature detectors
90. Improving neural networks by preventing co-adaption of feature detectors 2020 Fall
91. Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition
92. Influenza Forecasting Framework based on Gaussian Processes
93. Influenza Forecasting Framework based on Gaussian processes Summary
94. Label-Free Supervision of Neural Networks with Physics and Domain Knowledge
95. Learning Combinatorial Optimzation
96. Learning The Difference That Makes A Difference With Counterfactually-Augmented Data
97. Learning What and Where to Draw
98. Learning the Number of Neurons in Deep Networks
99. Learning to Navigate in Cities Without a Map
100. Learning to Teach