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Showing below up to 250 results in range #1 to #250.
- (hist) tRIAL for that odd behaviour [0 bytes]
- (hist) Curiosity-driven Exploration by Self-supervised Prediction [0 bytes]
- (hist) STAT946F17/ Dance Dance Convolution [0 bytes]
- (hist) Influenza Forecasting Framework based on Gaussian processes Summary [4 bytes]
- (hist) stat946w18/Hierarchical Representations for Efficient Architecture Search [11 bytes]
- (hist) stat946f15/Deep neural networks for acoustic modeling in speech recognition [16 bytes]
- (hist) Improving neural networks by preventing co-adaption of feature detectors 2020 Fall [16 bytes]
- (hist) video-Based Face Recognition Using Adaptive Hidden Markov Models [17 bytes]
- (hist) ModelFramework.jpg [27 bytes]
- (hist) maximum Variance Unfolding (June 2 2009) [34 bytes]
- (hist) monte Carlo methods [36 bytes]
- (hist) time-series-using-GAN [44 bytes]
- (hist) sandbox to test w2l [54 bytes]
- (hist) stat946w18/ [72 bytes]
- (hist) ALBERT [76 bytes]
- (hist) wikicoursenote:Manual of Style [82 bytes]
- (hist) Don't Just Blame Over-parametrization Summary [89 bytes]
- (hist) mark Your Contribution here [107 bytes]
- (hist) mark your contribution here [107 bytes]
- (hist) stat946-Fall 2010 [112 bytes]
- (hist) stat946F20/GradientLess Descent [137 bytes]
- (hist) stat946f15 [198 bytes]
- (hist) link to my paper [204 bytes]
- (hist) stat946f17 [215 bytes]
- (hist) 13Stat946papers [234 bytes]
- (hist) test1 [255 bytes]
- (hist) infoboxtest [260 bytes]
- (hist) Proposal for STAT946 (Deep Learning) final projects Fall 2017 [331 bytes]
- (hist) deepGenerativeModels [466 bytes]
- (hist) f11stat946EditorSignUp [501 bytes]
- (hist) wikicoursenote:cleanup [551 bytes]
- (hist) Bsodjahi [759 bytes]
- (hist) Deep Transfer Learning with Joint Adaptation Networks [760 bytes]
- (hist) statf10841Scribe [814 bytes]
- (hist) learning2reasoning [852 bytes]
- (hist) schedule [918 bytes]
- (hist) f11Stat946papers [941 bytes]
- (hist) singular Value Decomposition(SVD) [1,085 bytes]
- (hist) proof of Theorem 1 [1,140 bytes]
- (hist) f11Stat841EditorSignUp [1,220 bytes]
- (hist) schedule of Project Presentations [1,236 bytes]
- (hist) f14Stat842EditorSignUp [1,238 bytes]
- (hist) schedule946 [1,494 bytes]
- (hist) Meta-Learning-For-Domain Generalization [1,514 bytes]
- (hist) statf09841Scribe [1,515 bytes]
- (hist) Imagination Augmented Agents for Deep Reinforcement Learning [1,575 bytes]
- (hist) deflation Method for Penalized Matrix Decomposition Sparse PCA [1,621 bytes]
- (hist) f11Stat841presentation [1,695 bytes]
- (hist) signupformStat341F11 [1,775 bytes]
- (hist) paper Summaries [2,022 bytes]
- (hist) Pre-Training-Tasks-For-Embedding-Based-Large-Scale-Retrieval [2,068 bytes]
- (hist) importance Sampling June 2 2009 [2,099 bytes]
- (hist) is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction [2,146 bytes]
- (hist) proof of Lemma 1 [2,150 bytes]
- (hist) proof [3,086 bytes]
- (hist) f11Stat946presentation [3,162 bytes]
- (hist) contributions on Video-Based Face Recognition Using Adaptive Hidden Markov Models [3,211 bytes]
- (hist) a Dynamic Bayesian Network Click Model for web search ranking [3,492 bytes]
- (hist) Traffic Sign Recognition System (TSRS): SVM and Convolutional Neural Network [3,643 bytes]
- (hist) measuring and testing dependence by correlation of distances [3,675 bytes]
- (hist) Hash Embeddings for Efficient Word Representations [3,841 bytes]
- (hist) sign up for your presentation [4,160 bytes]
- (hist) Batch Normalization Summary [4,283 bytes]
- (hist) markov Chain Definitions [4,619 bytes]
- (hist) stat940F21 [4,782 bytes]
- (hist) stat441w18/summary 1 [4,834 bytes]
- (hist) binomial Probability Monte Carlo Sampling June 2 2009 [4,964 bytes]
- (hist) main Page [5,022 bytes]
- (hist) copyofstat341 [5,050 bytes]
- (hist) Task Understanding from Confushing Multitask Data [5,085 bytes]
- (hist) monte Carlo Integration [5,183 bytes]
- (hist) stat441w18 [5,299 bytes]
- (hist) acceptance-Rejection Sampling [5,779 bytes]
- (hist) bayesian and Frequentist Schools of Thought [5,797 bytes]
- (hist) stat441F18 [6,075 bytes]
- (hist) Batch Normalization [6,084 bytes]
- (hist) a Deeper Look into Importance Sampling [6,315 bytes]
- (hist) s13Stat946proposal [6,364 bytes]
- (hist) the Indian Buffet Process: An Introduction and Review [6,413 bytes]
- (hist) importance Sampling and Markov Chain Monte Carlo (MCMC) [6,450 bytes]
- (hist) genetics [6,457 bytes]
- (hist) Deep Learning for Extreme Multi-label Text Classification [6,578 bytes]
- (hist) metric and Kernel Learning Using a Linear Transformation [6,583 bytes]
- (hist) Deep Residual Learning for Image Recognition Summary [6,589 bytes]
- (hist) kernel Dimension Reduction in Regression [6,640 bytes]
- (hist) nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization [6,730 bytes]
- (hist) again on Markov Chain [6,938 bytes]
- (hist) Convolutional neural network for diagnosis of viral pneumonia and COVID-19 alike diseases [6,985 bytes]
- (hist) Convolutional Neural Networks for Sentence Classification [7,012 bytes]
- (hist) techniques for Normal and Gamma Sampling [7,262 bytes]
- (hist) large-Scale Supervised Sparse Principal Component Analysis [7,419 bytes]
- (hist) importance Sampling and Monte Carlo Simulation [7,462 bytes]
- (hist) proposal for STAT946 (Deep Learning) final projects Fall 2015 [7,533 bytes]
- (hist) Wide and Deep Learning for Recommender Systems [7,762 bytes]
- (hist) measuring statistical dependence with Hilbert-Schmidt norms [7,804 bytes]
- (hist) U-Time:A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging Summary [8,051 bytes]
- (hist) contributions on Context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis [8,071 bytes]
- (hist) Bayesian Network as a Decision Tool for Predicting ALS Disease [8,088 bytes]
- (hist) hierarchical Dirichlet Processes [8,178 bytes]
- (hist) on the Number of Linear Regions of Deep Neural Networks [8,398 bytes]
- (hist) generating Random Numbers [8,400 bytes]
- (hist) deep Learning of the tissue-regulated splicing code [8,523 bytes]
- (hist) Unsupervised Machine Translation Using Monolingual Corpora Only [8,547 bytes]
- (hist) stat441F21 [8,574 bytes]
- (hist) Dynamic Routing Between Capsulesl [8,625 bytes]
- (hist) a Rank Minimization Heuristic with Application to Minimum Order System Approximation [8,679 bytes]
- (hist) adaptive dimension reduction for clustering high dimensional data [8,820 bytes]
- (hist) decentralised Data Fusion: A Graphical Model Approach (Summary) [8,861 bytes]
- (hist) STAT946F20/BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding [8,936 bytes]
- (hist) deep Sparse Rectifier Neural Networks [8,983 bytes]
- (hist) cardinality Restricted Boltzmann Machines [9,174 bytes]
- (hist) parametric Local Metric Learning for Nearest Neighbor Classification [9,358 bytes]
- (hist) Research on Multiple Classification Based on Improved SVM Algorithm for Balanced Binary Decision Tree [9,395 bytes]
- (hist) Robust Probabilistic Modeling with Bayesian Data Reweighting [9,400 bytes]
- (hist) positive Semidefinite Metric Learning Using Boosting-like Algorithms [9,507 bytes]
- (hist) stat946w18 [9,537 bytes]
- (hist) Don't Just Blame Over-parametrization [9,544 bytes]
- (hist) Going Deeper with Convolutions [9,580 bytes]
- (hist) strategies for Training Large Scale Neural Network Language Models [9,641 bytes]
- (hist) semi-supervised Learning with Deep Generative Models [9,651 bytes]
- (hist) video-based face recognition using Adaptive HMM [9,786 bytes]
- (hist) Another look at distance-weighted discrimination [9,801 bytes]
- (hist) test [9,812 bytes]
- (hist) This Looks Like That: Deep Learning for Interpretable Image Recognition [9,951 bytes]
- (hist) f17Stat946PaperSignUp [9,982 bytes]
- (hist) Depthwise Convolution Is All You Need for Learning Multiple Visual Domains [10,043 bytes]
- (hist) kernel Spectral Clustering for Community Detection in Complex Networks [10,246 bytes]
- (hist) context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis [10,381 bytes]
- (hist) stat841F18/ [10,578 bytes]
- (hist) Learning The Difference That Makes A Difference With Counterfactually-Augmented Data [10,629 bytes]
- (hist) hamming Distance Metric Learning [10,708 bytes]
- (hist) Representations of Words and Phrases and their Compositionality [10,739 bytes]
- (hist) Poison Frogs Neural Networks [10,842 bytes]
- (hist) deep Convolutional Neural Networks For LVCSR [10,860 bytes]
- (hist) mULTIPLE OBJECT RECOGNITION WITH VISUAL ATTENTION [10,935 bytes]
- (hist) a Dynamic Bayesian Network Click Model for Web Search Ranking [10,982 bytes]
- (hist) Augmix: New Data Augmentation method to increase the robustness of the algorithm [11,257 bytes]
- (hist) A Knowledge-Grounded Neural Conversation Model [11,272 bytes]
- (hist) A Game Theoretic Approach to Class-wise Selective Rationalization [11,317 bytes]
- (hist) very Deep Convoloutional Networks for Large-Scale Image Recognition [11,457 bytes]
- (hist) GradientLess Descent [11,517 bytes]
- (hist) f15Stat946PaperSignUp [11,589 bytes]
- (hist) maximum-Margin Matrix Factorization [11,779 bytes]
- (hist) deep Generative Stochastic Networks Trainable by Backprop [11,830 bytes]
- (hist) nonparametric Latent Feature Models for Link Prediction [11,861 bytes]
- (hist) learning Phrase Representations [11,920 bytes]
- (hist) graph Laplacian Regularization for Larg-Scale Semidefinite Programming [11,952 bytes]
- (hist) neural Turing Machines [11,991 bytes]
- (hist) CRITICAL ANALYSIS OF SELF-SUPERVISION [11,995 bytes]
- (hist) stat441w18/Saliency-based Sequential Image Attention with Multiset Prediction [12,037 bytes]
- (hist) self-Taught Learning [12,049 bytes]
- (hist) F21-STAT 441/841 CM 763-Proposal [12,049 bytes]
- (hist) a fast learning algorithm for deep belief nets [12,051 bytes]
- (hist) Learning Combinatorial Optimzation [12,086 bytes]
- (hist) joint training of a convolutional network and a graphical model for human pose estimation [12,149 bytes]
- (hist) show, Attend and Tell: Neural Image Caption Generation with Visual Attention [12,161 bytes]
- (hist) learning Convolutional Feature Hierarchies for Visual Recognition [12,276 bytes]
- (hist) Predicting Hurricane Trajectories Using a Recurrent Neural Network [12,277 bytes]
- (hist) scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers Machines [12,303 bytes]
- (hist) Automatic Bank Fraud Detection Using Support Vector Machines [12,303 bytes]
- (hist) The Detection of Black Ice Accidents Using CNNs [12,531 bytes]
- (hist) Memory-Based Parameter Adaptation [12,660 bytes]
- (hist) summary [12,663 bytes]
- (hist) an HDP-HMM for Systems with State Persistence [12,699 bytes]
- (hist) On The Convergence Of ADAM And Beyond [12,957 bytes]
- (hist) paper 13 [12,976 bytes]
- (hist) Do Vision Transformers See Like CNN [13,013 bytes]
- (hist) imageNet Classification with Deep Convolutional Neural Networks [13,183 bytes]
- (hist) natural language processing (almost) from scratch. [13,194 bytes]
- (hist) Gradient Episodic Memory for Continual Learning [13,341 bytes]
- (hist) stat946w18/Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolutional Layers [13,361 bytes]
- (hist) Streaming Bayesian Inference for Crowdsourced Classification [13,491 bytes]
- (hist) the loss surfaces of multilayer networks (Choromanska et al.) [13,493 bytes]
- (hist) Robust Imitation Learning from Noisy Demonstrations [13,516 bytes]
- (hist) sparse PCA [13,535 bytes]
- (hist) The Curious Case of Degeneration [13,571 bytes]
- (hist) compressive Sensing (Candes) [13,587 bytes]
- (hist) dropout [13,614 bytes]
- (hist) stat441w18/A New Method of Region Embedding for Text Classification [13,622 bytes]
- (hist) F21-STAT 940-Proposal [13,656 bytes]
- (hist) DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION [13,738 bytes]
- (hist) dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces [13,891 bytes]
- (hist) stat946F18 [13,896 bytes]
- (hist) stat946w18/Predicting Floor-Level for 911 Calls with Neural Networks and Smartphone Sensor Data [13,936 bytes]
- (hist) ALBERT: A Lite BERT for Self-supervised Learning of Language Representations [13,956 bytes]
- (hist) f11Stat946ass [13,980 bytes]
- (hist) neural Machine Translation: Jointly Learning to Align and Translate [14,061 bytes]
- (hist) residual Component Analysis: Generalizing PCA for more flexible inference in linear-Gaussian models [14,327 bytes]
- (hist) matrix Completion with Noise [14,449 bytes]
- (hist) STAT946F17/ Learning Important Features Through Propagating Activation Differences [14,579 bytes]
- (hist) on using very large target vocabulary for neural machine translation [14,589 bytes]
- (hist) stat441w18/mastering-chess-and-shogi-self-play [14,596 bytes]
- (hist) Meta-Learning For Domain Generalization [14,600 bytes]
- (hist) extracting and Composing Robust Features with Denoising Autoencoders [14,613 bytes]
- (hist) Roberta [14,722 bytes]
- (hist) Dynamic Routing Between Capsules [14,778 bytes]
- (hist) Towards Deep Learning Models Resistant to Adversarial Attacks [14,812 bytes]
- (hist) visualizing Similarity Data with a Mixture of Maps [14,886 bytes]
- (hist) Breaking Certified Defenses: Semantic Adversarial Examples With Spoofed Robustness Certificates [14,911 bytes]
- (hist) XGBoost: A Scalable Tree Boosting System [15,042 bytes]
- (hist) contributions on Quantifying Cancer Progression with Conjunctive Bayesian Networks [15,193 bytes]
- (hist) quantifying cancer progression with conjunctive Bayesian networks. [15,204 bytes]
- (hist) goingDeeperWithConvolutions [15,240 bytes]
- (hist) continuous space language models [15,275 bytes]
- (hist) question Answering with Subgraph Embeddings [15,293 bytes]
- (hist) quantifying cancer progression with conjunctive Bayesian networks [15,306 bytes]
- (hist) Semantic Relation Classification——via Convolution Neural Network [15,324 bytes]
- (hist) Wavelet Pooling CNN [15,345 bytes]
- (hist) orthogonal gradient descent for continual learning [15,363 bytes]
- (hist) maximum likelihood estimation of intrinsic dimension [15,392 bytes]
- (hist) Model Agnostic Learning of Semantic Features [15,514 bytes]
- (hist) independent Component Analysis: algorithms and applications [15,526 bytes]
- (hist) statf09841Proposal [15,646 bytes]
- (hist) stat441w18/e-gan [15,651 bytes]
- (hist) Co-Teaching [15,712 bytes]
- (hist) rOBPCA: A New Approach to Robust Principal Component Analysis [15,775 bytes]
- (hist) From Variational to Deterministic Autoencoders [15,837 bytes]
- (hist) Extreme Multi-label Text Classification [15,848 bytes]
- (hist) proposal for STAT946 projects [15,862 bytes]
- (hist) neighbourhood Components Analysis [15,899 bytes]
- (hist) a fair comparison of graph neural networks for graph classification [15,982 bytes]
- (hist) Patch Based Convolutional Neural Network for Whole Slide Tissue Image Classification [16,111 bytes]
- (hist) the Wake-Sleep Algorithm for Unsupervised Neural Networks [16,139 bytes]
- (hist) kernelized Sorting [16,226 bytes]
- (hist) parsing natural scenes and natural language with recursive neural networks [16,235 bytes]
- (hist) Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness [16,296 bytes]
- (hist) stat946w18/Spectral normalization for generative adversial network [16,342 bytes]
- (hist) STAT946F17/ Automated Curriculum Learning for Neural Networks [16,391 bytes]
- (hist) inductive Kernel Low-rank Decomposition with Priors: A Generalized Nystrom Method [16,450 bytes]
- (hist) SuperGLUE [16,457 bytes]
- (hist) DeepVO Towards end to end visual odometry with deep RNN [16,676 bytes]
- (hist) stat946w18/Implicit Causal Models for Genome-wide Association Studies [16,805 bytes]
- (hist) Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition [16,892 bytes]
- (hist) When Does Self-Supervision Improve Few-Shot Learning? [16,936 bytes]
- (hist) CatBoost: unbiased boosting with categorical features [17,013 bytes]
- (hist) kernelized Locality-Sensitive Hashing [17,115 bytes]
- (hist) Dense Passage Retrieval for Open-Domain Question Answering [17,125 bytes]
- (hist) BERTScore: Evaluating Text Generation with BERT [17,132 bytes]
- (hist) discLDA: Discriminative Learning for Dimensionality Reduction and Classification [17,184 bytes]
- (hist) deep Neural Nets as a Method for Quantitative Structure–Activity Relationships [17,219 bytes]
- (hist) F18-STAT946-Proposal [17,305 bytes]
- (hist) Influenza Forecasting Framework based on Gaussian Processes [17,358 bytes]
- (hist) proposal for STAT946 projects Fall 2010 [17,366 bytes]
- (hist) stat946w18/Synthetic and natural noise both break neural machine translation [17,403 bytes]
- (hist) multi-Task Feature Learning [17,528 bytes]
- (hist) graphical models for structured classification, with an application to interpreting images of protein subcellular location patterns [17,604 bytes]
- (hist) Pixels to Graphs by Associative Embedding [17,615 bytes]
- (hist) Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments [17,715 bytes]
- (hist) THE LOGICAL EXPRESSIVENESS OF GRAPH NEURAL NETWORKS [17,773 bytes]
- (hist) One pixel attack for fooling deep neural networks [17,832 bytes]