Optimization & Theory

Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization ICML 2021 Post-Hoc Uncertainty Calibration for Domain Drift Scenarios CVPR 2021 Post-Training Sparsity-Aware Quantization NeurIPS 2021 PQK: Model Compression via Pruning, Quantization, and Knowledge Distillation Interspeech 2021 Practical Single-Image Super-Resolution Using Look-Up Table CVPR 2021 Pragmatic Image Compression for Human-in-the-Loop Decision-Making NeurIPS 2021 Principal Bit Analysis: Autoencoding with Schur-Concave Loss ICML 2021 Prioritized Architecture Sampling With Monto-Carlo Tree Search CVPR 2021 Probabilistic Selective Encryption of Convolutional Neural Networks for Hierarchical Services CVPR 2021 Probing Across Time: What Does RoBERTa Know and When? EMNLP 2021 Projection Robust Wasserstein Barycenters ICML 2021 ProSelfLC: Progressive Self Label Correction for Training Robust Deep Neural Networks CVPR 2021 Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks AAAI 2021 Provable Lipschitz Certification for Generative Models ICML 2021 Provable Memorization via Deep Neural Networks using Sub-linear Parameters COLT 2021 Provably Strict Generalisation Benefit for Equivariant Models ICML 2021 Pruning Neural Machine Translation for Speed Using Group Lasso EMNLP 2021 Pruning of Deep Spiking Neural Networks through Gradient Rewiring IJCAI 2021 PSRR-MaxpoolNMS: Pyramid Shifted MaxpoolNMS With Relationship Recovery CVPR 2021 QPP: Real-Time Quantization Parameter Prediction for Deep Neural Networks CVPR 2021 Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels ICML 2021 RainBench: Towards Data-Driven Global Precipitation Forecasting from Satellite Imagery AAAI 2021 Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning EMNLP 2021 Random Feature Attention ICLR 2021 Ranking Neural Checkpoints CVPR 2021