Optimization & Theory

Efficient Machine Translation with Model Pruning and Quantization EMNLP 2021 Efficient Multi-Stage Video Denoising With Recurrent Spatio-Temporal Fusion CVPR 2021 Efficient Neural Network Training via Forward and Backward Propagation Sparsification NeurIPS 2021 Efficient On-Chip Learning for Optical Neural Networks Through Power-Aware Sparse Zeroth-Order Optimization AAAI 2021 Efficient Test Time Adapter Ensembling for Low-resource Language Varieties EMNLP 2021 Efficient Wasserstein Natural Gradients for Reinforcement Learning ICLR 2021 Efficient Weight Factorization for Multilingual Speech Recognition Interspeech 2021 Elastic Consistency: A Practical Consistency Model for Distributed Stochastic Gradient Descent AAAI 2021 EL-Attention: Memory Efficient Lossless Attention for Generation ICML 2021 Elementary superexpressive activations ICML 2021 Embedding Principle of Loss Landscape of Deep Neural Networks NeurIPS 2021 Empowering Adaptive Early-Exit Inference with Latency Awareness AAAI 2021 Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization NeurIPS 2021 Enabling Lightweight Fine-tuning for Pre-trained Language Model Compression based on Matrix Product Operators ACL 2021 End-to-End High Dynamic Range Camera Pipeline Optimization CVPR 2021 Enhance Curvature Information by Structured Stochastic Quasi-Newton Methods CVPR 2021 Enhancing Robustness of Neural Networks through Fourier Stabilization ICML 2021 Ensembling With a Fixed Parameter Budget: When Does It Help and Why? ACML 2021 ErrorCompensatedX: error compensation for variance reduced algorithms NeurIPS 2021 Estimating informativeness of samples with Smooth Unique Information ICLR 2021 ESTIME: Estimation of Summary-to-Text Inconsistency by Mismatched Embeddings EMNLP 2021 Evaluating the carbon footprint of NLP methods: a survey and analysis of existing tools EMNLP 2021 EVALUATION OF NEURAL ARCHITECTURES TRAINED WITH SQUARE LOSS VS CROSS-ENTROPY IN CLASSIFICATION TASKS ICLR 2021 Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models ICML 2021 Examining the Inductive Bias of Neural Language Models with Artificial Languages ACL 2021