Uncategorized pages

Showing below up to 363 results in range #1 to #363.

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
101. Loss Function Search for Face Recognition
102. MULTI-VIEW DATA GENERATION WITHOUT VIEW SUPERVISION
103. Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
104. MarrNet: 3D Shape Reconstruction via 2.5D Sketches
105. Mask RCNN
106. Memory-Based Parameter Adaptation
107. Meta-Learning-For-Domain Generalization
108. Meta-Learning For Domain Generalization
109. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
110. ModelFramework.jpg
111. Model Agnostic Learning of Semantic Features
112. Modular Multitask Reinforcement Learning with Policy Sketches
113. Multi-scale Dense Networks for Resource Efficient Image Classification
114. Music Recommender System Based using CRNN
115. Neural Audio Synthesis of Musical Notes with WaveNet autoencoders
116. Neural ODEs
117. Neural Speed Reading via Skim-RNN
118. Obfuscated Gradients Give a False Sense of Security Circumventing Defenses to Adversarial Examples
119. On The Convergence Of ADAM And Beyond
120. One-Shot Imitation Learning
121. One-Shot Object Detection with Co-Attention and Co-Excitation
122. One pixel attack for fooling deep neural networks
123. Patch Based Convolutional Neural Network for Whole Slide Tissue Image Classification
124. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
125. Pixels to Graphs by Associative Embedding
126. Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence
127. PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
128. Poison Frogs Neural Networks
129. Pre-Training-Tasks-For-Embedding-Based-Large-Scale-Retrieval
130. Pre-Training Tasks For Embedding-Based Large-Scale Retrieval
131. Predicting Floor Level For 911 Calls with Neural Network and Smartphone Sensor Data
132. Predicting Hurricane Trajectories Using a Recurrent Neural Network
133. Proposal for STAT946 (Deep Learning) final projects Fall 2017
134. Reinforcement Learning of Theorem Proving
135. Representations of Words and Phrases and their Compositionality
136. Research Papers Classification System
137. Research on Multiple Classification Based on Improved SVM Algorithm for Balanced Binary Decision Tree
138. Roberta
139. Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias
140. Robust Imitation Learning from Noisy Demonstrations
141. Robust Imitation of Diverse Behaviors
142. Robust Probabilistic Modeling with Bayesian Data Reweighting
143. STAT946F17/Cognitive Psychology For Deep Neural Networks: A Shape Bias Case Study
144. STAT946F17/Conditional Image Generation with PixelCNN Decoders
145. STAT946F17/Decoding with Value Networks for Neural Machine Translation
146. STAT946F17/ Automated Curriculum Learning for Neural Networks
147. STAT946F17/ Coupled GAN
148. STAT946F17/ Dance Dance Convolution
149. STAT946F17/ Improved Variational Inference with Inverse Autoregressive Flow
150. STAT946F17/ Learning Important Features Through Propagating Activation Differences
151. STAT946F17/ Learning a Probabilistic Latent Space of Object Shapes via 3D GAN
152. STAT946F17/ Teaching Machines to Describe Images via Natural Language Feedback
153. STAT946F20/BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
154. Searching For Efficient Multi Scale Architectures For Dense Image Prediction
155. Self-Supervised Learning of Pretext-Invariant Representations
156. Semantic Relation Classification——via Convolution Neural Network
157. ShakeDrop Regularization
158. Speech2Face: Learning the Face Behind a Voice
159. Spherical CNNs
160. Streaming Bayesian Inference for Crowdsourced Classification
161. Summary - A Neural Representation of Sketch Drawings
162. Summary for survey of neural networked-based cancer prediction models from microarray data
163. Summary of A Probabilistic Approach to Neural Network Pruning
164. SuperGLUE
165. Superhuman AI for Multiplayer Poker
166. Surround Vehicle Motion Prediction
167. Synthesizing Programs for Images usingReinforced Adversarial Learning
168. THE LOGICAL EXPRESSIVENESS OF GRAPH NEURAL NETWORKS
169. Task Understanding from Confushing Multitask Data
170. Task Understanding from Confusing Multi-task Data
171. The Curious Case of Degeneration
172. The Detection of Black Ice Accidents Using CNNs
173. This Looks Like That: Deep Learning for Interpretable Image Recognition
174. Time-series Generative Adversarial Networks
175. Towards Deep Learning Models Resistant to Adversarial Attacks
176. Traffic Sign Recognition System (TSRS): SVM and Convolutional Neural Network
177. Training And Inference with Integers in Deep Neural Networks
178. U-Time:A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging Summary
179. Understanding Image Motion with Group Representations
180. Understanding the Effective Receptive Field in Deep Convolutional Neural Networks
181. Universal Style Transfer via Feature Transforms
182. Unsupervised Domain Adaptation with Residual Transfer Networks
183. Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness
184. Unsupervised Machine Translation Using Monolingual Corpora Only
185. Unsupervised Neural Machine Translation
186. Visual Reinforcement Learning with Imagined Goals
187. Wasserstein Auto-Encoders
188. Wasserstein Auto-encoders
189. Wavelet Pooling CNN
190. When Does Self-Supervision Improve Few-Shot Learning?
191. When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary
192. Wide and Deep Learning for Recommender Systems
193. Word translation without parallel data
194. XGBoost
195. XGBoost: A Scalable Tree Boosting System
196. Zero-Shot Visual Imitation
197. a Deeper Look into Importance Sampling
198. a Direct Formulation For Sparse PCA Using Semidefinite Programming
199. a Dynamic Bayesian Network Click Model for web search ranking
200. a Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis
201. a Rank Minimization Heuristic with Application to Minimum Order System Approximation
202. a fair comparison of graph neural networks for graph classification
203. a fast learning algorithm for deep belief nets
204. a neural representation of sketch drawings
205. adaptive dimension reduction for clustering high dimensional data
206. again on Markov Chain
207. bayesian and Frequentist Schools of Thought
208. binomial Probability Monte Carlo Sampling June 2 2009
209. compressive Sensing
210. conditional neural process
211. consistency of Trace Norm Minimization
212. context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
213. contributions on Context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
214. contributions on Quantifying Cancer Progression with Conjunctive Bayesian Networks
215. contributions on Video-Based Face Recognition Using Adaptive Hidden Markov Models
216. copyofstat341
217. decentralised Data Fusion: A Graphical Model Approach (Summary)
218. deepGenerativeModels
219. deep Convolutional Neural Networks For LVCSR
220. deep Learning of the tissue-regulated splicing code
221. deep neural networks for acoustic modeling in speech recognition
222. deflation Method for Penalized Matrix Decomposition Sparse PCA
223. deflation Methods for Sparse PCA
224. dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces
225. discLDA: Discriminative Learning for Dimensionality Reduction and Classification
226. distributed Representations of Words and Phrases and their Compositionality
227. f11Stat841EditorSignUp
228. f11Stat841presentation
229. f11Stat841proposal
230. f11Stat946papers
231. f11Stat946presentation
232. f11stat946EditorSignUp
233. f14Stat842EditorSignUp
234. f15Stat946PaperSignUp
235. f17Stat946PaperSignUp
236. generating Random Numbers
237. genetics
238. hamming Distance Metric Learning
239. hierarchical Dirichlet Processes
240. importance Sampling June 2 2009
241. importance Sampling and Markov Chain Monte Carlo (MCMC)
242. importance Sampling and Monte Carlo Simulation
243. incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains(Summary)
244. independent Component Analysis: algorithms and applications
245. is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction
246. kernel Dimension Reduction in Regression
247. kernel Spectral Clustering for Community Detection in Complex Networks
248. kernelized Locality-Sensitive Hashing
249. kernelized Sorting
250. learn what not to learn
251. learning2reasoning
252. learning Convolutional Feature Hierarchies for Visual Recognition
253. learning Fast Approximations of Sparse Coding
254. learning Spectral Clustering, With Application To Speech Separation
255. learning a Nonlinear Embedding by Preserving Class Neighborhood Structure
256. link to my paper
257. mULTIPLE OBJECT RECOGNITION WITH VISUAL ATTENTION
258. main Page
259. mark Your Contribution here
260. mark your contribution here
261. markov Chain Definitions
262. matrix Completion with Noise
263. maximum-Margin Matrix Factorization
264. maximum Variance Unfolding (June 2 2009)
265. maximum likelihood estimation of intrinsic dimension
266. meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting
267. measuring Statistical Dependence with Hilbert-Schmidt Norm
268. measuring and testing dependence by correlation of distances
269. monte Carlo Integration
270. monte Carlo methods
271. neighbourhood Components Analysis
272. neural Machine Translation: Jointly Learning to Align and Translate
273. nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization
274. nonparametric Latent Feature Models for Link Prediction
275. on using very large target vocabulary for neural machine translation
276. orthogonal gradient descent for continual learning
277. overfeat: integrated recognition, localization and detection using convolutional networks
278. paper 13
279. paper Summaries
280. policy optimization with demonstrations
281. proof
282. proof of Lemma 1
283. proof of Theorem 1
284. proposal Fall 2010
285. proposal for STAT946 (Deep Learning) final projects Fall 2015
286. proposal for STAT946 projects
287. proposal for STAT946 projects Fall 2010
288. quantifying cancer progression with conjunctive Bayesian networks.
289. rOBPCA: A New Approach to Robust Principal Component Analysis
290. regression on Manifold using Kernel Dimension Reduction
291. relevant Component Analysis
292. residual Component Analysis: Generalizing PCA for more flexible inference in linear-Gaussian models
293. s13Stat946proposal
294. sandbox to test w2l
295. scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers Machines
296. schedule
297. schedule946
298. schedule of Project Presentations
299. self-Taught Learning
300. show, Attend and Tell: Neural Image Caption Generation with Visual Attention
301. sign up for your presentation
302. signupformStat341F11
303. singular Value Decomposition(SVD)
304. sparse PCA
305. stat441F18
306. stat441F18/TCNLM
307. stat441F18/YOLO
308. stat441F21
309. stat441w18
310. stat441w18/A New Method of Region Embedding for Text Classification
311. stat441w18/Convolutional Neural Networks for Sentence Classification
312. stat441w18/Image Question Answering using CNN with Dynamic Parameter Prediction
313. stat441w18/Saliency-based Sequential Image Attention with Multiset Prediction
314. stat441w18/e-gan
315. stat441w18/mastering-chess-and-shogi-self-play
316. stat441w18/summary 1
317. stat841F18/
318. stat940F21
319. stat946-Fall 2010
320. stat946F18
321. stat946F18/Autoregressive Convolutional Neural Networks for Asynchronous Time Series
322. stat946F18/Beyond Word Importance Contextual Decomposition to Extract Interactions from LSTMs
323. stat946F18/differentiableplasticity
324. stat946F20/GradientLess Descent
325. stat946f15
326. stat946f15/Deep neural networks for acoustic modeling in speech recognition
327. stat946f17
328. stat946s13
329. stat946w18
330. stat946w18/
331. stat946w18/AmbientGAN: Generative Models from Lossy Measurements
332. stat946w18/Hierarchical Representations for Efficient Architecture Search
333. stat946w18/IMPROVING GANS USING OPTIMAL TRANSPORT
334. stat946w18/Implicit Causal Models for Genome-wide Association Studies
335. stat946w18/MaskRNN: Instance Level Video Object Segmentation
336. stat946w18/Predicting Floor-Level for 911 Calls with Neural Networks and Smartphone Sensor Data
337. stat946w18/Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolutional Layers
338. stat946w18/Self Normalizing Neural Networks
339. stat946w18/Spectral normalization for generative adversial network
340. stat946w18/Synthetic and natural noise both break neural machine translation
341. stat946w18/Tensorized LSTMs
342. stat946w18/Towards Image Understanding From Deep Compression Without Decoding
343. stat946w18/Unsupervised Machine Translation Using Monolingual Corpora Only
344. stat946w18/Wavelet Pooling For Convolutional Neural Networks
345. statf09841Proposal
346. statf09841Scribe
347. statf10841Scribe
348. summary
349. supervised Dictionary Learning
350. tRIAL for that odd behaviour
351. techniques for Normal and Gamma Sampling
352. test
353. the Indian Buffet Process: An Introduction and Review
354. the Manifold Tangent Classifier
355. the Wake-Sleep Algorithm for Unsupervised Neural Networks
356. time-series-using-GAN
357. very Deep Convoloutional Networks for Large-Scale Image Recognition
358. video-Based Face Recognition Using Adaptive Hidden Markov Models
359. visualizing Data using t-SNE
360. visualizing Similarity Data with a Mixture of Maps
361. what game are we playing
362. wikicoursenote:Manual of Style
363. wikicoursenote:cleanup