principal component analysis

Autoencoding Improves Pre-trained Word Embeddings COLING 2020 Beyond Adjacency Pairs: Hierarchical Clustering of Long Sequences for Human-Machine Dialogues EMNLP 2020 Communication-Efficient Distributed PCA by Riemannian Optimization ICML 2020 Effect of Spectral Complexity Reduction and Number of Instruments on Musical Enjoyment with Cochlear Implants Interspeech 2020 Eliminating the Invariance on the Loss Landscape of Linear Autoencoders ICML 2020 Estimating Principal Components under Adversarial Perturbations COLT 2020 Exploring the Linear Subspace Hypothesis in Gender Bias Mitigation EMNLP 2020 Federated Principal Component Analysis NeurIPS 2020 Filter Distillation for Network Compression WACV 2020 Gain with no Pain: Efficiency of Kernel-PCA by Nyström Sampling AISTATS 2020 GANSpace: Discovering Interpretable GAN Controls NeurIPS 2020 Guided Variational Autoencoder for Disentanglement Learning CVPR 2020 Instance-optimality in differential privacy via approximate inverse sensitivity mechanisms NeurIPS 2020 Learning Feature Sparse Principal Subspace NeurIPS 2020 Learning Polynomials in Few Relevant Dimensions COLT 2020 On Dimensional Linguistic Properties of the Word Embedding Space ACL 2020 Online Convex Optimization in the Random Order Model ICML 2020 Principal Style Components: Expressive Style Control and Cross-Speaker Transfer in Neural TTS Interspeech 2020 Regularized linear autoencoders recover the principal components, eventually NeurIPS 2020 Stochastic Variance-Reduced Algorithms for PCA with Arbitrary Mini-Batch Sizes AISTATS 2020 Streaming Batch Gradient Tracking for Neural Network Training (Student Abstract) AAAI 2020 The estimation error of general first order methods COLT 2020 Understanding l4-based Dictionary Learning: Interpretation, Stability, and Robustness ICLR 2020 A Decomposition Algorithm for the Sparse Generalized Eigenvalue Problem CVPR 2019 AugBoost: Gradient Boosting Enhanced with Step-Wise Feature Augmentation IJCAI 2019