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Optimization & Theory

6,829 papers (27 classified directly here)

Subtopics

Model Compression (1,785) Optimization (1,664) Efficient Computing (1,579) Theory (1,082) Neural Network Optimization (903) Evaluation (509) Loss Functions (123) Interpretability (105) Stochastic Methods (97) Regularization (77) Generalization (24) Sparse Optimization (7)

Papers per year

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Papers (including subtopics)

The Devil is in the Details: On the Pitfalls of Vocabulary Selection in Neural Machine Translation NAACL 2022
Don’t Take It Literally: An Edit-Invariant Sequence Loss for Text Generation NAACL 2022
KroneckerBERT: Significant Compression of Pre-trained Language Models Through Kronecker Decomposition and Knowledge Distillation NAACL 2022
Towards Efficient NLP: A Standard Evaluation and A Strong Baseline NAACL 2022
Tricks for Training Sparse Translation Models NAACL 2022
Adaptable Adapters NAACL 2022
Leaner and Faster: Two-Stage Model Compression for Lightweight Text-Image Retrieval NAACL 2022
Massive-scale Decoding for Text Generation using Lattices NAACL 2022
Dynamic Programming in Rank Space: Scaling Structured Inference with Low-Rank HMMs and PCFGs NAACL 2022
Sketching as a Tool for Understanding and Accelerating Self-attention for Long Sequences NAACL 2022
ExSum: From Local Explanations to Model Understanding NAACL 2022
Learning to Win Lottery Tickets in BERT Transfer via Task-agnostic Mask Training NAACL 2022
Looking Beyond GPUs for DNN Scheduling on Multi-Tenant Clusters OSDI 2022
Efficient and Scalable Graph Pattern Mining on GPUs OSDI 2022
Adversarial Branch Architecture Search for Unsupervised Domain Adaptation WACV 2022
Numerical influence of ReLU’(0) on backpropagation NIPS 2021
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks NIPS 2021
Demystifying and Generalizing BinaryConnect NIPS 2021
Towards Stable and Robust AdderNets NIPS 2021
Channel Permutations for N:M Sparsity NIPS 2021
Nonsmooth Implicit Differentiation for Machine-Learning and Optimization NIPS 2021
Overparameterization Improves Robustness to Covariate Shift in High Dimensions NIPS 2021
Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation NIPS 2021
Optimizing Reusable Knowledge for Continual Learning via Metalearning NIPS 2021
Convergence of adaptive algorithms for constrained weakly convex optimization NIPS 2021