Optimization

SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness NeurIPS 2021 Smooth Normalizing Flows NeurIPS 2021 Solving high-dimensional parabolic PDEs using the tensor train format ICML 2021 Some Theoretical Insights into Wasserstein GANs JMLR 2021 SONIA: A Symmetric Blockwise Truncated Optimization Algorithm AISTATS 2021 Sound Source Localization with Majorization Minimization Interspeech 2021 SPADE: A Spectral Method for Black-Box Adversarial Robustness Evaluation ICML 2021 Sparse and Imperceptible Adversarial Attack via a Homotopy Algorithm ICML 2021 Sparse Convex Optimization via Adaptively Regularized Hard Thresholding JMLR 2021 Sparse Flows: Pruning Continuous-depth Models NeurIPS 2021 Sparse Multi-Path Corrections in Fringe Projection Profilometry CVPR 2021 Sparse Quadratic Optimisation over the Stiefel Manifold with Application to Permutation Synchronisation NeurIPS 2021 Sparse sketches with small inversion bias COLT 2021 Sparse Spiking Gradient Descent NeurIPS 2021 Sparse Tensor Additive Regression JMLR 2021 Sparsifying Networks via Subdifferential Inclusion ICML 2021 Spectral Leakage and Rethinking the Kernel Size in CNNs ICCV 2021 Spectral Tensor Train Parameterization of Deep Learning Layers AISTATS 2021 Speed up Training with Variable Length Inputs by Efficient Batching Strategies Interspeech 2021 Square Root Bundle Adjustment for Large-Scale Reconstruction CVPR 2021 Square Root Marginalization for Sliding-Window Bundle Adjustment ICCV 2021 Square Root Principal Component Pursuit: Tuning-Free Noisy Robust Matrix Recovery NeurIPS 2021 Stability and Convergence of Stochastic Gradient Clipping: Beyond Lipschitz Continuity and Smoothness ICML 2021 Stability and Generalization of Bilevel Programming in Hyperparameter Optimization NeurIPS 2021 Stability and Generalization of Decentralized Stochastic Gradient Descent AAAI 2021