Optimization

Relaxed Core Stability in Fractional Hedonic Games IJCAI 2021 Relaxed Marginal Consistency for Differentially Private Query Answering NeurIPS 2021 Relaxing Local Robustness NeurIPS 2021 ReNAS: Relativistic Evaluation of Neural Architecture Search CVPR 2021 Replica Exchange for Non-Convex Optimization JMLR 2021 Representer Theorems in Banach Spaces: Minimum Norm Interpolation, Regularized Learning and Semi-Discrete Inverse Problems JMLR 2021 Representing Hyperbolic Space Accurately using Multi-Component Floats NeurIPS 2021 RepVGG: Making VGG-Style ConvNets Great Again CVPR 2021 Residual Pathway Priors for Soft Equivariance Constraints NeurIPS 2021 ResNet After All: Neural ODEs and Their Numerical Solution ICLR 2021 Rethinking Attention with Performers ICLR 2021 Rethinking Bi-Level Optimization in Neural Architecture Search: A Gibbs Sampling Perspective AAAI 2021 Rethinking BiSeNet for Real-Time Semantic Segmentation CVPR 2021 Rethinking Deep Image Prior for Denoising ICCV 2021 Rethinking gradient sparsification as total error minimization NeurIPS 2021 Rethinking Neural Operations for Diverse Tasks NeurIPS 2021 Rethinking Perturbations in Encoder-Decoders for Fast Training NAACL 2021 Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss ICML 2021 Rethinking the Pruning Criteria for Convolutional Neural Network NeurIPS 2021 Rethinking the Variational Interpretation of Accelerated Optimization Methods NeurIPS 2021 RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning NeurIPS 2021 Reverse engineering learned optimizers reveals known and novel mechanisms NeurIPS 2021 Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices AAAI 2021 Revisiting Dynamic Convolution via Matrix Decomposition ICLR 2021 Revisiting Projection-free Online Learning: the Strongly Convex Case AISTATS 2021