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Showing below up to 100 results in range #201 to #300.
- a Dynamic Bayesian Network Click Model for web search ranking
- a New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
- a Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis
- a Rank Minimization Heuristic with Application to Minimum Order System Approximation
- a fair comparison of graph neural networks for graph classification
- a fast learning algorithm for deep belief nets
- a neural representation of sketch drawings
- acceptance-Rejection Sampling
- adaptive dimension reduction for clustering high dimensional data
- again on Markov Chain
- an HDP-HMM for Systems with State Persistence
- bayesian and Frequentist Schools of Thought
- binomial Probability Monte Carlo Sampling June 2 2009
- cardinality Restricted Boltzmann Machines
- compressed Sensing Reconstruction via Belief Propagation
- compressive Sensing
- compressive Sensing (Candes)
- conditional neural process
- consistency of Trace Norm Minimization
- context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
- continuous space language models
- contributions on Context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
- contributions on Quantifying Cancer Progression with Conjunctive Bayesian Networks
- contributions on Video-Based Face Recognition Using Adaptive Hidden Markov Models
- convex and Semi Nonnegative Matrix Factorization
- copyofstat341
- decentralised Data Fusion: A Graphical Model Approach (Summary)
- deepGenerativeModels
- deep Convolutional Neural Networks For LVCSR
- deep Generative Stochastic Networks Trainable by Backprop
- deep Learning of the tissue-regulated splicing code
- deep Neural Nets as a Method for Quantitative Structure–Activity Relationships
- deep Sparse Rectifier Neural Networks
- deep neural networks for acoustic modeling in speech recognition
- deflation Method for Penalized Matrix Decomposition Sparse PCA
- deflation Methods for Sparse PCA
- dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces
- discLDA: Discriminative Learning for Dimensionality Reduction and Classification
- distributed Representations of Words and Phrases and their Compositionality
- dropout
- extracting and Composing Robust Features with Denoising Autoencoders
- f10 Stat841 digest
- f11Stat841EditorSignUp
- f11Stat841presentation
- f11Stat841proposal
- f11Stat946ass
- f11Stat946papers
- f11Stat946presentation
- f11stat946EditorSignUp
- f14Stat842EditorSignUp
- f15Stat946PaperSignUp
- f17Stat946PaperSignUp
- from Machine Learning to Machine Reasoning
- generating Random Numbers
- generating text with recurrent neural networks
- genetics
- goingDeeperWithConvolutions
- graph Laplacian Regularization for Larg-Scale Semidefinite Programming
- 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
- hamming Distance Metric Learning
- hierarchical Dirichlet Processes
- human-level control through deep reinforcement learning
- imageNet Classification with Deep Convolutional Neural Networks
- importance Sampling June 2 2009
- importance Sampling and Markov Chain Monte Carlo (MCMC)
- importance Sampling and Monte Carlo Simulation
- incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains(Summary)
- independent Component Analysis: algorithms and applications
- inductive Kernel Low-rank Decomposition with Priors: A Generalized Nystrom Method
- infoboxtest
- is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction
- joint training of a convolutional network and a graphical model for human pose estimation
- kernel Dimension Reduction in Regression
- kernel Spectral Clustering for Community Detection in Complex Networks
- kernelized Locality-Sensitive Hashing
- kernelized Sorting
- large-Scale Supervised Sparse Principal Component Analysis
- learn what not to learn
- learning2reasoning
- learning Convolutional Feature Hierarchies for Visual Recognition
- learning Fast Approximations of Sparse Coding
- learning Hierarchical Features for Scene Labeling
- learning Long-Range Vision for Autonomous Off-Road Driving
- learning Phrase Representations
- learning Spectral Clustering, With Application To Speech Separation
- learning a Nonlinear Embedding by Preserving Class Neighborhood Structure
- link to my paper
- mULTIPLE OBJECT RECOGNITION WITH VISUAL ATTENTION
- main Page
- mark Your Contribution here
- mark your contribution here
- markov Chain Definitions
- markov Random Fields for Super-Resolution
- matrix Completion with Noise
- maximum-Margin Matrix Factorization
- maximum Variance Unfolding (June 2 2009)
- maximum likelihood estimation of intrinsic dimension
- meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting
- measuring Statistical Dependence with Hilbert-Schmidt Norm