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Showing below up to 333 results in range #51 to #383.

51. Dense Passage Retrieval for Open-Domain Question Answering
52. Depthwise Convolution Is All You Need for Learning Multiple Visual Domains
53. Describtion of Text Mining
54. Dialog-based Language Learning
55. Do Deep Neural Networks Suffer from Crowding
56. Do Vision Transformers See Like CNN
57. Don't Just Blame Over-parametrization
58. Don't Just Blame Over-parametrization Summary
59. Dynamic Routing Between Capsules
60. Dynamic Routing Between Capsules STAT946
61. Dynamic Routing Between Capsulesl
62. Efficient kNN Classification with Different Numbers of Nearest Neighbors
63. End-to-End Differentiable Adversarial Imitation Learning
64. End to end Active Object Tracking via Reinforcement Learning
65. Evaluating Machine Accuracy on ImageNet
66. Extreme Multi-label Text Classification
67. F18-STAT841-Proposal
68. F18-STAT946-Proposal
69. F21-STAT 441/841 CM 763-Proposal
70. F21-STAT 940-Proposal
71. Fairness Without Demographics in Repeated Loss Minimization
72. FeUdal Networks for Hierarchical Reinforcement Learning
73. Fix your classifier: the marginal value of training the last weight layer
74. From Variational to Deterministic Autoencoders
75. Functional regularisation for continual learning with gaussian processes
76. Generating Image Descriptions
77. Going Deeper with Convolutions
78. GradientLess Descent
79. Gradient Episodic Memory for Continual Learning
80. Graph Structure of Neural Networks
81. Hash Embeddings for Efficient Word Representations
82. Hierarchical Representations for Efficient Architecture Search
83. IPBoost
84. Imagination-Augmented Agents for Deep Reinforcement Learning
85. Imagination Augmented Agents for Deep Reinforcement Learning
86. Improving neural networks by preventing co-adaption of feature detectors
87. Improving neural networks by preventing co-adaption of feature detectors 2020 Fall
88. Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition
89. Influenza Forecasting Framework based on Gaussian Processes
90. Influenza Forecasting Framework based on Gaussian processes Summary
91. Label-Free Supervision of Neural Networks with Physics and Domain Knowledge
92. Learning Combinatorial Optimzation
93. Learning The Difference That Makes A Difference With Counterfactually-Augmented Data
94. Learning What and Where to Draw
95. Learning the Number of Neurons in Deep Networks
96. Learning to Navigate in Cities Without a Map
97. Learning to Teach
98. LightRNN: Memory and Computation-Efficient Recurrent Neural Networks
99. Loss Function Search for Face Recognition
100. MULTI-VIEW DATA GENERATION WITHOUT VIEW SUPERVISION
101. Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
102. MarrNet: 3D Shape Reconstruction via 2.5D Sketches
103. Mask RCNN
104. Memory-Based Parameter Adaptation
105. Meta-Learning-For-Domain Generalization
106. Meta-Learning For Domain Generalization
107. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
108. ModelFramework.jpg
109. Model Agnostic Learning of Semantic Features
110. Modular Multitask Reinforcement Learning with Policy Sketches
111. Multi-scale Dense Networks for Resource Efficient Image Classification
112. Music Recommender System Based using CRNN
113. Neural Audio Synthesis of Musical Notes with WaveNet autoencoders
114. Neural ODEs
115. Neural Speed Reading via Skim-RNN
116. Obfuscated Gradients Give a False Sense of Security Circumventing Defenses to Adversarial Examples
117. On The Convergence Of ADAM And Beyond
118. One-Shot Imitation Learning
119. One-Shot Object Detection with Co-Attention and Co-Excitation
120. One pixel attack for fooling deep neural networks
121. Patch Based Convolutional Neural Network for Whole Slide Tissue Image Classification
122. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
123. Pixels to Graphs by Associative Embedding
124. Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence
125. PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
126. Poison Frogs Neural Networks
127. Pre-Training-Tasks-For-Embedding-Based-Large-Scale-Retrieval
128. Pre-Training Tasks For Embedding-Based Large-Scale Retrieval
129. Predicting Floor Level For 911 Calls with Neural Network and Smartphone Sensor Data
130. Predicting Hurricane Trajectories Using a Recurrent Neural Network
131. Proposal for STAT946 (Deep Learning) final projects Fall 2017
132. Reinforcement Learning of Theorem Proving
133. Representations of Words and Phrases and their Compositionality
134. Research Papers Classification System
135. Research on Multiple Classification Based on Improved SVM Algorithm for Balanced Binary Decision Tree
136. Roberta
137. Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias
138. Robust Imitation Learning from Noisy Demonstrations
139. Robust Imitation of Diverse Behaviors
140. Robust Probabilistic Modeling with Bayesian Data Reweighting
141. STAT946F17/Cognitive Psychology For Deep Neural Networks: A Shape Bias Case Study
142. STAT946F17/Conditional Image Generation with PixelCNN Decoders
143. STAT946F17/Decoding with Value Networks for Neural Machine Translation
144. STAT946F17/ Automated Curriculum Learning for Neural Networks
145. STAT946F17/ Coupled GAN
146. STAT946F17/ Dance Dance Convolution
147. STAT946F17/ Improved Variational Inference with Inverse Autoregressive Flow
148. STAT946F17/ Learning Important Features Through Propagating Activation Differences
149. STAT946F17/ Learning a Probabilistic Latent Space of Object Shapes via 3D GAN
150. STAT946F17/ Teaching Machines to Describe Images via Natural Language Feedback
151. STAT946F20/BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
152. Searching For Efficient Multi Scale Architectures For Dense Image Prediction
153. Self-Supervised Learning of Pretext-Invariant Representations
154. Semantic Relation Classification——via Convolution Neural Network
155. ShakeDrop Regularization
156. Speech2Face: Learning the Face Behind a Voice
157. Spherical CNNs
158. Streaming Bayesian Inference for Crowdsourced Classification
159. Summary - A Neural Representation of Sketch Drawings
160. Summary for survey of neural networked-based cancer prediction models from microarray data
161. Summary of A Probabilistic Approach to Neural Network Pruning
162. SuperGLUE
163. Superhuman AI for Multiplayer Poker
164. Surround Vehicle Motion Prediction
165. Synthesizing Programs for Images usingReinforced Adversarial Learning
166. THE LOGICAL EXPRESSIVENESS OF GRAPH NEURAL NETWORKS
167. Task Understanding from Confushing Multitask Data
168. Task Understanding from Confusing Multi-task Data
169. The Curious Case of Degeneration
170. The Detection of Black Ice Accidents Using CNNs
171. This Looks Like That: Deep Learning for Interpretable Image Recognition
172. Time-series Generative Adversarial Networks
173. Towards Deep Learning Models Resistant to Adversarial Attacks
174. Traffic Sign Recognition System (TSRS): SVM and Convolutional Neural Network
175. Training And Inference with Integers in Deep Neural Networks
176. U-Time:A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging Summary
177. Understanding Image Motion with Group Representations
178. Understanding the Effective Receptive Field in Deep Convolutional Neural Networks
179. Universal Style Transfer via Feature Transforms
180. Unsupervised Domain Adaptation with Residual Transfer Networks
181. Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness
182. Unsupervised Machine Translation Using Monolingual Corpora Only
183. Unsupervised Neural Machine Translation
184. Visual Reinforcement Learning with Imagined Goals
185. Wasserstein Auto-Encoders
186. Wasserstein Auto-encoders
187. Wavelet Pooling CNN
188. When Does Self-Supervision Improve Few-Shot Learning?
189. When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary
190. Wide and Deep Learning for Recommender Systems
191. Word translation without parallel data
192. XGBoost
193. XGBoost: A Scalable Tree Boosting System
194. Zero-Shot Visual Imitation
195. a Direct Formulation For Sparse PCA Using Semidefinite Programming
196. a Dynamic Bayesian Network Click Model for Web Search Ranking
197. a Dynamic Bayesian Network Click Model for web search ranking
198. a New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
199. a Rank Minimization Heuristic with Application to Minimum Order System Approximation
200. a fair comparison of graph neural networks for graph classification
201. a fast learning algorithm for deep belief nets
202. a neural representation of sketch drawings
203. adaptive dimension reduction for clustering high dimensional data
204. again on Markov Chain
205. binomial Probability Monte Carlo Sampling June 2 2009
206. cardinality Restricted Boltzmann Machines
207. compressed Sensing Reconstruction via Belief Propagation
208. compressive Sensing
209. compressive Sensing (Candes)
210. conditional neural process
211. consistency of Trace Norm Minimization
212. context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
213. continuous space language models
214. contributions on Context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
215. contributions on Quantifying Cancer Progression with Conjunctive Bayesian Networks
216. contributions on Video-Based Face Recognition Using Adaptive Hidden Markov Models
217. convex and Semi Nonnegative Matrix Factorization
218. copyofstat341
219. decentralised Data Fusion: A Graphical Model Approach (Summary)
220. deepGenerativeModels
221. deep Convolutional Neural Networks For LVCSR
222. deep Generative Stochastic Networks Trainable by Backprop
223. deep Learning of the tissue-regulated splicing code
224. deep Neural Nets as a Method for Quantitative Structure–Activity Relationships
225. deep Sparse Rectifier Neural Networks
226. deep neural networks for acoustic modeling in speech recognition
227. deflation Method for Penalized Matrix Decomposition Sparse PCA
228. dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces
229. discLDA: Discriminative Learning for Dimensionality Reduction and Classification
230. distributed Representations of Words and Phrases and their Compositionality
231. dropout
232. extracting and Composing Robust Features with Denoising Autoencoders
233. f11Stat841EditorSignUp
234. f11Stat841presentation
235. f11Stat841proposal
236. f11Stat946ass
237. f11stat946EditorSignUp
238. f14Stat842EditorSignUp
239. from Machine Learning to Machine Reasoning
240. generating text with recurrent neural networks
241. genetics
242. goingDeeperWithConvolutions
243. graph Laplacian Regularization for Larg-Scale Semidefinite Programming
244. graves et al., Speech recognition with deep recurrent neural networks
245. hamming Distance Metric Learning
246. hierarchical Dirichlet Processes
247. human-level control through deep reinforcement learning
248. imageNet Classification with Deep Convolutional Neural Networks
249. importance Sampling June 2 2009
250. incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains(Summary)
251. inductive Kernel Low-rank Decomposition with Priors: A Generalized Nystrom Method
252. infoboxtest
253. is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction
254. joint training of a convolutional network and a graphical model for human pose estimation
255. kernel Dimension Reduction in Regression
256. kernel Spectral Clustering for Community Detection in Complex Networks
257. kernelized Locality-Sensitive Hashing
258. kernelized Sorting
259. large-Scale Supervised Sparse Principal Component Analysis
260. learn what not to learn
261. learning2reasoning
262. learning Convolutional Feature Hierarchies for Visual Recognition
263. learning Fast Approximations of Sparse Coding
264. learning Hierarchical Features for Scene Labeling
265. learning Long-Range Vision for Autonomous Off-Road Driving
266. learning Phrase Representations
267. learning Spectral Clustering, With Application To Speech Separation
268. link to my paper
269. mULTIPLE OBJECT RECOGNITION WITH VISUAL ATTENTION
270. mark Your Contribution here
271. mark your contribution here
272. markov Random Fields for Super-Resolution
273. matrix Completion with Noise
274. maximum-Margin Matrix Factorization
275. maximum Variance Unfolding (June 2 2009)
276. maximum likelihood estimation of intrinsic dimension
277. meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting
278. measuring Statistical Dependence with Hilbert-Schmidt Norm
279. measuring and testing dependence by correlation of distances
280. measuring statistical dependence with Hilbert-Schmidt norms
281. memory Networks
282. metric and Kernel Learning Using a Linear Transformation
283. monte Carlo methods
284. multi-Task Feature Learning
285. natural language processing (almost) from scratch.
286. neighbourhood Components Analysis
287. neural Machine Translation: Jointly Learning to Align and Translate
288. neural Turing Machines
289. nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization
290. nonparametric Latent Feature Models for Link Prediction
291. on the Number of Linear Regions of Deep Neural Networks
292. on the difficulty of training recurrent neural networks
293. on using very large target vocabulary for neural machine translation
294. orthogonal gradient descent for continual learning
295. overfeat: integrated recognition, localization and detection using convolutional networks
296. paper 13
297. parametric Local Metric Learning for Nearest Neighbor Classification
298. parsing natural scenes and natural language with recursive neural networks
299. policy optimization with demonstrations
300. positive Semidefinite Metric Learning Using Boosting-like Algorithms
301. probabilistic Matrix Factorization
302. probabilistic PCA with GPLVM
303. proof
304. proof of Lemma 1
305. proof of Theorem 1
306. proposal Fall 2010
307. proposal for STAT946 (Deep Learning) final projects Fall 2015
308. proposal for STAT946 projects
309. proposal for STAT946 projects Fall 2010
310. quantifying cancer progression with conjunctive Bayesian networks
311. quantifying cancer progression with conjunctive Bayesian networks.
312. question Answering with Subgraph Embeddings
313. rOBPCA: A New Approach to Robust Principal Component Analysis
314. regression on Manifold using Kernel Dimension Reduction
315. relevant Component Analysis
316. residual Component Analysis: Generalizing PCA for more flexible inference in linear-Gaussian models
317. s13Stat946proposal
318. sandbox to test w2l
319. scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers Machines
320. schedule
321. schedule946
322. schedule of Project Presentations
323. self-Taught Learning
324. semi-supervised Learning with Deep Generative Models
325. show, Attend and Tell: Neural Image Caption Generation with Visual Attention
326. signupformStat341F11
327. singular Value Decomposition(SVD)
328. sparse PCA
329. stat441F18/TCNLM
330. stat441F18/YOLO
331. stat441w18/A New Method of Region Embedding for Text Classification
332. stat441w18/Convolutional Neural Networks for Sentence Classification
333. stat441w18/Image Question Answering using CNN with Dynamic Parameter Prediction
334. stat441w18/Saliency-based Sequential Image Attention with Multiset Prediction
335. stat441w18/e-gan
336. stat441w18/mastering-chess-and-shogi-self-play
337. stat441w18/summary 1
338. stat841F18/
339. stat946F18/Autoregressive Convolutional Neural Networks for Asynchronous Time Series
340. stat946F18/Beyond Word Importance Contextual Decomposition to Extract Interactions from LSTMs
341. stat946F18/differentiableplasticity
342. stat946F20/GradientLess Descent
343. stat946f11pool
344. stat946f15/Deep neural networks for acoustic modeling in speech recognition
345. stat946f15/Sequence to sequence learning with neural networks
346. stat946w18
347. stat946w18/
348. stat946w18/AmbientGAN: Generative Models from Lossy Measurements
349. stat946w18/Hierarchical Representations for Efficient Architecture Search
350. stat946w18/IMPROVING GANS USING OPTIMAL TRANSPORT
351. stat946w18/Implicit Causal Models for Genome-wide Association Studies
352. stat946w18/MaskRNN: Instance Level Video Object Segmentation
353. stat946w18/Predicting Floor-Level for 911 Calls with Neural Networks and Smartphone Sensor Data
354. stat946w18/Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolutional Layers
355. stat946w18/Self Normalizing Neural Networks
356. stat946w18/Spectral
357. stat946w18/Spectral normalization for generative adversial network
358. stat946w18/Synthetic and natural noise both break neural machine translation
359. stat946w18/Tensorized LSTMs
360. stat946w18/Towards Image Understanding From Deep Compression Without Decoding
361. stat946w18/Unsupervised Machine Translation Using Monolingual Corpora Only
362. stat946w18/Wavelet Pooling For Convolutional Neural Networks
363. statf09841Proposal
364. statf09841Scribe
365. statf10841Scribe
366. strategies for Training Large Scale Neural Network Language Models
367. summary
368. supervised Dictionary Learning
369. tRIAL for that odd behaviour
370. test
371. the Indian Buffet Process: An Introduction and Review
372. the Manifold Tangent Classifier
373. the Wake-Sleep Algorithm for Unsupervised Neural Networks
374. the loss surfaces of multilayer networks (Choromanska et al.)
375. time-series-using-GAN
376. uncovering Shared Structures in Multiclass Classification
377. very Deep Convoloutional Networks for Large-Scale Image Recognition
378. video-Based Face Recognition Using Adaptive Hidden Markov Models
379. visualizing Data using t-SNE
380. visualizing Similarity Data with a Mixture of Maps
381. what game are we playing
382. wikicoursenote:Manual of Style
383. wikicoursenote:cleanup