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Optimization

1,664 papers

Papers per year

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Papers

A Generalized Framework for Edge-Preserving and Structure-Preserving Image Smoothing AAAI 2020
Sparsity-Inducing Binarized Neural Networks AAAI 2020
Pruning from Scratch AAAI 2020
Search Tree Pruning for Progressive Neural Architecture Search (Student Abstract) AAAI 2020
Streaming Batch Gradient Tracking for Neural Network Training (Student Abstract) AAAI 2020
An Effective Optimization Method for Neural Machine Translation: The Case of English-Persian Bilingually Low-Resource Scenario AACL 2020
SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization ACL 2020
A Batch Normalized Inference Network Keeps the KL Vanishing Away ACL 2020
Efficient Second-Order TreeCRF for Neural Dependency Parsing ACL 2020
Effective Estimation of Deep Generative Language Models ACL 2020
Deep-n-Cheap: An Automated Search Framework for Low Complexity Deep Learning ACML 2020
On the Convergence of SARAH and Beyond AISTATS 2020
Modular Block-diagonal Curvature Approximations for Feedforward Architectures AISTATS 2020
Learning in Gated Neural Networks AISTATS 2020
Fenchel Lifted Networks: A Lagrange Relaxation of Neural Network Training AISTATS 2020
An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise AISTATS 2020
Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural Networks AISTATS 2020
Deep Unfolding Network for Image Super-Resolution CVPR 2020
A Multigrid Method for Efficiently Training Video Models CVPR 2020
Discrete Model Compression With Resource Constraint for Deep Neural Networks CVPR 2020
On the Acceleration of Deep Learning Model Parallelism With Staleness CVPR 2020
Semantic Correspondence as an Optimal Transport Problem CVPR 2020
Bundle Adjustment on a Graph Processor CVPR 2020
MAGSAC++, a Fast, Reliable and Accurate Robust Estimator CVPR 2020
TomoFluid: Reconstructing Dynamic Fluid From Sparse View Videos CVPR 2020