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Optimization

1638 directly classified papers

Papers per year

Papers

On the Practical Robustness of the Nesterov’s Accelerated Quasi-Newton Method AAAI 2022
Proof of Learning: Towards a Practical Blockchain Consensus Mechanism Using Directed Guiding Gradients (Student Abstract) AAAI 2022
Combining Compressions for Multiplicative Size Scaling on Natural Language Tasks COLING 2022
Parameter-Efficient Mixture-of-Experts Architecture for Pre-trained Language Models COLING 2022
Non-Autoregressive Machine Translation: It’s Not as Fast as it Seems NAACL 2022
The Devil is in the Details: On the Pitfalls of Vocabulary Selection in Neural Machine Translation NAACL 2022
Tricks for Training Sparse Translation Models 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
GreedyNASv2: Greedier Search With a Greedy Path Filter CVPR 2022
Subspace Adversarial Training CVPR 2022
Robust Structured Declarative Classifiers for 3D Point Clouds: Defending Adversarial Attacks With Implicit Gradients CVPR 2022
Fully Hyperbolic Neural Networks ACL 2022
Efficient Hyper-parameter Search for Knowledge Graph Embedding ACL 2022
Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning NIPS 2022
Looking Beyond GPUs for DNN Scheduling on Multi-Tenant Clusters OSDI 2022
Annihilation of Spurious Minima in Two-Layer ReLU Networks NIPS 2022
Amortized Projection Optimization for Sliced Wasserstein Generative Models NIPS 2022
Revisit last-iterate convergence of mSGD under milder requirement on step size NIPS 2022
Chefs' Random Tables: Non-Trigonometric Random Features NIPS 2022
Distributed Online Convex Optimization with Compressed Communication NIPS 2022
Blessing of Depth in Linear Regression: Deeper Models Have Flatter Landscape Around the True Solution NIPS 2022
On Learning Fairness and Accuracy on Multiple Subgroups NIPS 2022
Module-Aware Optimization for Auxiliary Learning NIPS 2022
Make Sharpness-Aware Minimization Stronger: A Sparsified Perturbation Approach NIPS 2022