Uncategorized pages

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. Bsodjahi
27. CRITICAL ANALYSIS OF SELF-SUPERVISION
28. CapsuleNets
29. CatBoost: unbiased boosting with categorical features
30. Co-Teaching
31. Conditional Image Synthesis with Auxiliary Classifier GANs
32. Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
33. Convolutional Neural Networks for Sentence Classification
34. Convolutional Sequence to Sequence Learning
35. Convolutional neural network for diagnosis of viral pneumonia and COVID-19 alike diseases
36. Countering Adversarial Images Using Input Transformations
37. Curiosity-driven Exploration by Self-supervised Prediction
38. DCN plus: Mixed Objective And Deep Residual Coattention for Question Answering
39. DETECTING STATISTICAL INTERACTIONS FROM NEURAL NETWORK WEIGHTS
40. DON'T DECAY THE LEARNING RATE , INCREASE THE BATCH SIZE
41. DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION
42. DeepVO Towards end to end visual odometry with deep RNN
43. Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition
44. Deep Double Descent Where Bigger Models and More Data Hurt
45. Deep Exploration via Bootstrapped DQN
46. Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms
47. Deep Learning for Extreme Multi-label Text Classification
48. Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling
49. Deep Residual Learning for Image Recognition
50. Deep Residual Learning for Image Recognition Summary
51. Deep Transfer Learning with Joint Adaptation Networks
52. Dense Passage Retrieval for Open-Domain Question Answering
53. Depthwise Convolution Is All You Need for Learning Multiple Visual Domains
54. Describtion of Text Mining
55. Dialog-based Language Learning
56. Do Deep Neural Networks Suffer from Crowding
57. Do Vision Transformers See Like CNN
58. Don't Just Blame Over-parametrization
59. Don't Just Blame Over-parametrization Summary
60. Dynamic Routing Between Capsules
61. Dynamic Routing Between Capsules STAT946
62. Dynamic Routing Between Capsulesl
63. Efficient kNN Classification with Different Numbers of Nearest Neighbors
64. End-to-End Differentiable Adversarial Imitation Learning
65. End to end Active Object Tracking via Reinforcement Learning
66. Evaluating Machine Accuracy on ImageNet
67. Extreme Multi-label Text Classification
68. F18-STAT841-Proposal
69. F18-STAT946-Proposal
70. F21-STAT 441/841 CM 763-Proposal
71. F21-STAT 940-Proposal
72. Fairness Without Demographics in Repeated Loss Minimization
73. FeUdal Networks for Hierarchical Reinforcement Learning
74. Fix your classifier: the marginal value of training the last weight layer
75. From Variational to Deterministic Autoencoders
76. Functional regularisation for continual learning with gaussian processes
77. Generating Image Descriptions
78. Going Deeper with Convolutions
79. GradientLess Descent
80. Gradient Episodic Memory for Continual Learning
81. Graph Structure of Neural Networks
82. Hash Embeddings for Efficient Word Representations
83. Hierarchical Question-Image Co-Attention for Visual Question Answering
84. Hierarchical Representations for Efficient Architecture Search
85. IPBoost
86. Imagination-Augmented Agents for Deep Reinforcement Learning
87. Imagination Augmented Agents for Deep Reinforcement Learning
88. Improving neural networks by preventing co-adaption of feature detectors
89. Improving neural networks by preventing co-adaption of feature detectors 2020 Fall
90. Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition
91. Influenza Forecasting Framework based on Gaussian Processes
92. Influenza Forecasting Framework based on Gaussian processes Summary
93. Label-Free Supervision of Neural Networks with Physics and Domain Knowledge
94. Learning Combinatorial Optimzation
95. Learning The Difference That Makes A Difference With Counterfactually-Augmented Data
96. Learning What and Where to Draw
97. Learning the Number of Neurons in Deep Networks
98. Learning to Navigate in Cities Without a Map
99. Learning to Teach
100. LightRNN: Memory and Computation-Efficient Recurrent Neural Networks