Showing 1–20 of 32 results
/ Date/ Name
Jan 17, 2014An Analysis of Random Projections in Cancelable BiometricsFeb 20, 2020Neural Bayes: A Generic Parameterization Method for Unsupervised Representation LearningMay 23, 2016On Optimality Conditions for Auto-Encoder Signal RecoveryNov 13, 2017Three Factors Influencing Minima in SGDJan 11, 2019The Benefits of Over-parameterization at Initialization in Deep ReLU NetworksNov 15, 2017Variational Bi-LSTMsFeb 24, 2018A Walk with SGDOct 19, 2021Learning Rich Nearest Neighbor Representations from Self-supervised EnsemblesOct 19, 2021Momentum Contrastive Autoencoder: Using Contrastive Learning for Latent Space Distribution Matching in WAEOct 21, 2021Ensemble of Averages: Improving Model Selection and Boosting Performance in Domain GeneralizationJun 5, 2019How to Initialize your Network? Robust Initialization for WeightNorm & ResNetsOct 1, 2019Predicting with High Correlation FeaturesDec 7, 2014Dimensionality Reduction with Subspace Structure PreservationMay 21, 2015Why Regularized Auto-Encoders learn Sparse Representation?Dec 11, 2025TPV: Parameter Perturbations Through the Lens of Test Prediction VarianceJan 25, 2023Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular DataJun 22, 2018On the Spectral Bias of Neural NetworksOct 6, 2018h-detach: Modifying the LSTM Gradient Towards Better OptimizationMar 4, 2016Normalization Propagation: A Parametric Technique for Removing Internal Covariate Shift in Deep NetworksJun 16, 2017A Closer Look at Memorization in Deep Networks