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Showing below up to 177 results in range #51 to #227.
- F11stat946EditorSignUp → f11stat946EditorSignUp
- F14Stat842EditorSignUp → f14Stat842EditorSignUp
- F15Stat946PaperSignUp → f15Stat946PaperSignUp
- F20-STAT 441/841 CM 763-Proposal → F21-STAT 441/841 CM 763-Proposal
- F20-STAT 946-Proposal → F21-STAT 940-Proposal
- From Machine Learning to Machine Reasoning → from Machine Learning to Machine Reasoning
- Generating Random Numbers → generating Random Numbers
- Generating text with recurrent neural networks → generating text with recurrent neural networks
- Genetics → genetics
- GoingDeeperWithConvolutions → goingDeeperWithConvolutions
- Graph Laplacian Regularization for Larg-Scale Semidefinite Programming → graph Laplacian Regularization for Larg-Scale Semidefinite Programming
- Graphical models for structured classification, with an application to interpreting images of protein subcellular location patterns → graphical models for structured classification, with an application to interpreting images of protein subcellular location patterns
- Graves et al., Speech recognition with deep recurrent neural networks → graves et al., Speech recognition with deep recurrent neural networks
- Hamming Distance Metric Learning → hamming Distance Metric Learning
- Hierarchical Dirichlet Processes → hierarchical Dirichlet Processes
- Human-level control through deep reinforcement learning → human-level control through deep reinforcement learning
- ImageNet Classification with Deep Convolutional Neural Networks → imageNet Classification with Deep Convolutional Neural Networks
- Importance Sampling June 2 2009 → importance Sampling June 2 2009
- Importance Sampling and Markov Chain Monte Carlo (MCMC) → importance Sampling and Markov Chain Monte Carlo (MCMC)
- Importance Sampling and Monte Carlo Simulation → importance Sampling and Monte Carlo Simulation
- Incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains(Summary) → incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains(Summary)
- Independent Component Analysis: algorithms and applications → independent Component Analysis: algorithms and applications
- Inductive Kernel Low-rank Decomposition with Priors: A Generalized Nystrom Method → inductive Kernel Low-rank Decomposition with Priors: A Generalized Nystrom Method
- Infoboxtest → infoboxtest
- Is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction → is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction
- Joint training of a convolutional network and a graphical model for human pose estimation → joint training of a convolutional network and a graphical model for human pose estimation
- Kernel Dimension Reduction in Regression → kernel Dimension Reduction in Regression
- Kernel Spectral Clustering for Community Detection in Complex Networks → kernel Spectral Clustering for Community Detection in Complex Networks
- Kernelized Locality-Sensitive Hashing → kernelized Locality-Sensitive Hashing
- Kernelized Sorting → kernelized Sorting
- Large-Scale Supervised Sparse Principal Component Analysis → large-Scale Supervised Sparse Principal Component Analysis
- Learning2reasoning → learning2reasoning
- Learning Convolutional Feature Hierarchies for Visual Recognition → learning Convolutional Feature Hierarchies for Visual Recognition
- Learning Fast Approximations of Sparse Coding → learning Fast Approximations of Sparse Coding
- Learning Hierarchical Features for Scene Labeling → learning Hierarchical Features for Scene Labeling
- Learning Long-Range Vision for Autonomous Off-Road Driving → learning Long-Range Vision for Autonomous Off-Road Driving
- Learning Phrase Representations → learning Phrase Representations
- Learning Spectral Clustering, With Application To Speech Separation → learning Spectral Clustering, With Application To Speech Separation
- Learning a Nonlinear Embedding by Preserving Class Neighborhood Structure → learning a Nonlinear Embedding by Preserving Class Neighborhood Structure
- Link to my paper → link to my paper
- MULTIPLE OBJECT RECOGNITION WITH VISUAL ATTENTION → mULTIPLE OBJECT RECOGNITION WITH VISUAL ATTENTION
- Main Page → main Page
- Mark Your Contribution here → mark Your Contribution here
- Mark your contribution here → mark your contribution here
- Markov Chain Definitions → markov Chain Definitions
- Markov Random Fields for Super-Resolution → markov Random Fields for Super-Resolution
- Matrix Completion with Noise → matrix Completion with Noise
- Maximum-Margin Matrix Factorization → maximum-Margin Matrix Factorization
- Maximum Variance Unfolding (June 2 2009) → maximum Variance Unfolding (June 2 2009)
- Maximum likelihood estimation of intrinsic dimension → maximum likelihood estimation of intrinsic dimension
- Measuring Statistical Dependence with Hilbert-Schmidt Norm → measuring Statistical Dependence with Hilbert-Schmidt Norm
- Measuring and testing dependence by correlation of distances → measuring and testing dependence by correlation of distances
- Measuring statistical dependence with Hilbert-Schmidt norms → measuring statistical dependence with Hilbert-Schmidt norms
- Memory Networks → memory Networks
- Metric and Kernel Learning Using a Linear Transformation → metric and Kernel Learning Using a Linear Transformation
- Monte Carlo Integration → monte Carlo Integration
- Monte Carlo methods → monte Carlo methods
- Multi-Task Feature Learning → multi-Task Feature Learning
- Natural language processing (almost) from scratch. → natural language processing (almost) from scratch.
- Neighbourhood Components Analysis → neighbourhood Components Analysis
- Neural Machine Translation: Jointly Learning to Align and Translate → neural Machine Translation: Jointly Learning to Align and Translate
- Neural Speed Reading → Neural Speed Reading via Skim-RNN
- Neural Turing Machines → neural Turing Machines
- Nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization → nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization
- Nonparametric Latent Feature Models for Link Prediction → nonparametric Latent Feature Models for Link Prediction
- On the Number of Linear Regions of Deep Neural Networks → on the Number of Linear Regions of Deep Neural Networks
- On the difficulty of training recurrent neural networks → on the difficulty of training recurrent neural networks
- On using very large target vocabulary for neural machine translation → on using very large target vocabulary for neural machine translation
- Optimal Solutions forSparse Principal Component Analysis → optimal Solutions forSparse Principal Component Analysis
- Overfeat: integrated recognition, localization and detection using convolutional networks → overfeat: integrated recognition, localization and detection using convolutional networks
- Paper 13 → paper 13
- Paper Summaries → paper Summaries
- Parametric Local Metric Learning for Nearest Neighbor Classification → parametric Local Metric Learning for Nearest Neighbor Classification
- Parsing natural scenes and natural language with recursive neural networks → parsing natural scenes and natural language with recursive neural networks
- Positive Semidefinite Metric Learning Using Boosting-like Algorithms → positive Semidefinite Metric Learning Using Boosting-like Algorithms
- Probabilistic Matrix Factorization → probabilistic Matrix Factorization
- Probabilistic PCA with GPLVM → probabilistic PCA with GPLVM
- Proof → proof
- Proof of Lemma 1 → proof of Lemma 1
- Proof of Theorem 1 → proof of Theorem 1
- Proposal Fall 2010 → proposal Fall 2010
- Proposal for STAT946 (Deep Learning) final projects Fall 2015 → proposal for STAT946 (Deep Learning) final projects Fall 2015
- Proposal for STAT946 projects → proposal for STAT946 projects
- Proposal for STAT946 projects Fall 2010 → proposal for STAT946 projects Fall 2010
- Proposed Title → Bag of Tricks for Efficient Text Classification
- Quantifying cancer progression with conjunctive Bayesian networks → quantifying cancer progression with conjunctive Bayesian networks
- Quantifying cancer progression with conjunctive Bayesian networks. → quantifying cancer progression with conjunctive Bayesian networks.
- Question Answering with Subgraph Embeddings → question Answering with Subgraph Embeddings
- ROBPCA: A New Approach to Robust Principal Component Analysis → rOBPCA: A New Approach to Robust Principal Component Analysis
- Regression on Manifold using Kernel Dimension Reduction → regression on Manifold using Kernel Dimension Reduction
- Regression on Manifolds Using Kernel Dimension Reduction → regression on Manifolds Using Kernel Dimension Reduction
- Relevant Component Analysis → relevant Component Analysis
- Residual Component Analysis: Generalizing PCA for more flexible inference in linear-Gaussian models → residual Component Analysis: Generalizing PCA for more flexible inference in linear-Gaussian models
- S13Stat946proposal → s13Stat946proposal
- STAT946F17/cognitive psychology for deep neural networks a shape bias case study → STAT946F17/Cognitive Psychology For Deep Neural Networks: A Shape Bias Case Study
- STAT 940 F21 → stat946F20
- Sandbox to test w2l → sandbox to test w2l
- Scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers Machines → scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers Machines
- Schedule → schedule
- Schedule946 → schedule946
- Schedule of Project Presentations → schedule of Project Presentations
- Self-Taught Learning → self-Taught Learning
- Semi-supervised Learning with Deep Generative Models → semi-supervised Learning with Deep Generative Models
- Show, Attend and Tell: Neural Image Caption Generation with Visual Attention → show, Attend and Tell: Neural Image Caption Generation with Visual Attention
- Sign up for your presentation → sign up for your presentation
- SignupformStat341F11 → signupformStat341F11
- Singular Value Decomposition(SVD) → singular Value Decomposition(SVD)
- Sparse PCA → sparse PCA
- Stat340s13 → stat340s13
- Stat341 → stat341
- Stat341 / CM 361 → stat341 / CM 361
- Stat341f11 → stat341f11
- Stat841 → stat841
- Stat841f10 → stat841f10
- Stat841f11 → stat841f11
- Stat841f14 → stat841f14
- Stat946 → stat946
- Stat946-Fall 2010 → stat946-Fall 2010
- Stat946f10 → stat946f10
- Stat946f11 → stat946f11
- Stat946f11pool → stat946f11pool
- Stat946f15 → stat946f15
- Stat946f15/Deep neural networks for acoustic modeling in speech recognition → stat946f15/Deep neural networks for acoustic modeling in speech recognition
- Stat946f15/Sequence to sequence learning with neural networks → stat946f15/Sequence to sequence learning with neural networks
- Stat946s13 → stat946s13
- Statf09841Proposal → statf09841Proposal
- Statf09841Scribe → statf09841Scribe
- Statf10841Scribe → statf10841Scribe
- Strategies for Training Large Scale Neural Network Language Models → strategies for Training Large Scale Neural Network Language Models
- Summary → summary
- Summary for Saliency-based Sequential Image Attention with Multiset Prediction → stat441w18/Saliency-based Sequential Image Attention with Multiset Prediction
- Supervised Dictionary Learning → supervised Dictionary Learning
- TRIAL for that odd behaviour → tRIAL for that odd behaviour
- Techniques for Normal and Gamma Sampling → techniques for Normal and Gamma Sampling
- Test1 → test1
- Text Mining Classification Clustering Extraction Techniques → A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques
- The Indian Buffet Process: An Introduction and Review → the Indian Buffet Process: An Introduction and Review
- The Manifold Tangent Classifier → the Manifold Tangent Classifier
- The Wake-Sleep Algorithm for Unsupervised Neural Networks → the Wake-Sleep Algorithm for Unsupervised Neural Networks
- The loss surfaces of multilayer networks (Choromanska et al.) → the loss surfaces of multilayer networks (Choromanska et al.)
- Uncovering Shared Structures in Multiclass Classification → uncovering Shared Structures in Multiclass Classification
- Very Deep Convoloutional Networks for Large-Scale Image Recognition → very Deep Convoloutional Networks for Large-Scale Image Recognition
- Video-Based Face Recognition Using Adaptive Hidden Markov Models → video-Based Face Recognition Using Adaptive Hidden Markov Models
- Video-based face recognition using Adaptive HMM → video-based face recognition using Adaptive HMM
- Visualizing Data using t-SNE → visualizing Data using t-SNE
- Visualizing Similarity Data with a Mixture of Maps → visualizing Similarity Data with a Mixture of Maps
- Wikicoursenote:Manual of Style → wikicoursenote:Manual of Style
- Wikicoursenote:cleanup → wikicoursenote:cleanup
- cm361 → Stat341 / CM 361
- neural sketch drawings → A Neural Representation of Sketch Drawings
- new page → Learning Combinatorial Optimzation
- regression on Manifolds Using Kernel Dimension Reduction → Kernel Dimension Reduction in Regression
- stat341 → Stat341 / CM 361
- stat441F20 → stat441F21
- stat946 → Stat946f10
- stat946F18/Hierarchical Representations for Efficient Architecture Search → Hierarchical Representations for Efficient Architecture Search
- stat946F20 → stat940F21
- understanding image motion with group representations → Understanding Image Motion with Group Representations
- Talk:STAT 940 F21 → Talk:stat946F20
- Talk:stat441F20 → Talk:stat441F21
- Talk:stat946F20 → Talk:stat940F21
- User:Bsodjahi → Bayesian Network as a Decision Tool for Predicting ALS Disease
- User:Dfagan → Efficient kNN Classification with Different Numbers of Nearest Neighbors
- User:G285sing → BERTScore: Evaluating Text Generation with BERT
- User:Kb7lee → statwiki:DETECTING STATISTICAL INTERACTIONS FROM NEURAL NETWORK WEIGHTS
- User:Q58yu → Adversarial Attacks on Copyright Detection Systems
- User:STAT946F20/BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding → STAT946F20/BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
- User:W28shen → User:STAT946F20/BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
- User:Y93fang → Summary for survey of neural networked-based cancer prediction models from microarray data
- statwiki:DETECTING STATISTICAL INTERACTIONS FROM NEURAL NETWORK WEIGHTS → DETECTING STATISTICAL INTERACTIONS FROM NEURAL NETWORK WEIGHTS
- File:MaskTrackTable2.jpg → File:MaskRNNTable2.jpg
- File:MaskTrackTable3.jpg → File:MaskRNNTable3.jpg
- File:MaskTrackTable4.jpg → File:MaskRNNTable4.jpg
- Template:Clr → Template:-
- Template:Doc → Template:Documentation
- Template:Documentation, template → Template:Documentation
- Template:Tnavbar → Template:Navbar
