Theory

Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization AAAI 2020 Training Linear Neural Networks: Non-Local Convergence and Complexity Results ICML 2020 Transferable Perturbations of Deep Feature Distributions ICLR 2020 Transformation of ReLU-based recurrent neural networks from discrete-time to continuous-time ICML 2020 True Nonlinear Dynamics from Incomplete Networks AAAI 2020 Truncated Linear Regression in High Dimensions NeurIPS 2020 Truth or backpropaganda? An empirical investigation of deep learning theory ICLR 2020 Truth or Error? Towards systematic analysis of factual errors in abstractive summaries EMNLP 2020 Two Birds with One Stone: Investigating Invertible Neural Networks for Inverse Problems in Morphology AAAI 2020 Two-Grid Preconditioned Solver for Bundle Adjustment WACV 2020 Understanding Deep Architecture with Reasoning Layer NeurIPS 2020 Understanding Double Descent Requires A Fine-Grained Bias-Variance Decomposition NeurIPS 2020 Understanding Generalization in Recurrent Neural Networks ICLR 2020 Understanding Global Feature Contributions With Additive Importance Measures NeurIPS 2020 Understanding the Source of Semantic Regularities in Word Embeddings CoNLL 2020 Universal Approximation with Certified Networks ICLR 2020 Universal Approximation with Deep Narrow Networks COLT 2020 Universal Average-Case Optimality of Polyak Momentum ICML 2020 Universal Equivariant Multilayer Perceptrons ICML 2020 Universal Value Iteration Networks: When Spatially-Invariant Is Not Universal AAAI 2020 Using PRMSE to evaluate automated scoring systems in the presence of label noise ACL 2020 VCG under Sybil (False-Name) Attacks - A Bayesian Analysis AAAI 2020 VECA: A Method for Detecting Overfitting in Neural Networks (Student Abstract) AAAI 2020 Verifying Individual Fairness in Machine Learning Models UAI 2020 Visualizing Deep Networks by Optimizing with Integrated Gradients AAAI 2020