Optimization
1,960 papers
Papers per year
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2
4
2
3
4
8
25
19
28
34
44
82
125
160
195
201
234
394
302
89
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Papers
AutoInt: Automatic Integration for Fast Neural Volume Rendering
CVPR 2021
AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly
ICLR 2021
Automated Log-Scale Quantization for Low-Cost Deep Neural Networks
CVPR 2021
Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators
ICML 2021
A Zeroth-Order Block Coordinate Descent Algorithm for Huge-Scale Black-Box Optimization
ICML 2021
Boost Neural Networks by Checkpoints
NeurIPS 2021
Bringing UMAP Closer to the Speed of Light with GPU Acceleration
AAAI 2021
Closing the Gap: Tighter Analysis of Alternating Stochastic Gradient Methods for Bilevel Problems
NeurIPS 2021
Connecting Sphere Manifolds Hierarchically for Regularization
ICML 2021
ContactOpt: Optimizing Contact To Improve Grasps
CVPR 2021
Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization
ICLR 2021
Contrastive Neural Architecture Search With Neural Architecture Comparators
CVPR 2021
Convergence rates and approximation results for SGD and its continuous-time counterpart
COLT 2021
Convolutional Neural Network Pruning With Structural Redundancy Reduction
CVPR 2021
Cooperative SGD: A Unified Framework for the Design and Analysis of Local-Update SGD Algorithms
JMLR 2021
Corrected CBOW Performs as well as Skip-gram
EMNLP 2021
Correlation-Aware Heuristic Search for Intelligent Virtual Machine Provisioning in Cloud Systems
AAAI 2021
Cross Modal Focal Loss for RGBD Face Anti-Spoofing
CVPR 2021
DDSAS: Dynamic and Differentiable Space-Architecture Search
ACML 2021
DecentLaM: Decentralized Momentum SGD for Large-Batch Deep Training
ICCV 2021
DeepLM: Large-Scale Nonlinear Least Squares on Deep Learning Frameworks Using Stochastic Domain Decomposition
CVPR 2021
DeRF: Decomposed Radiance Fields
CVPR 2021
Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers
ICML 2021
Differentiable Fluids with Solid Coupling for Learning and Control
AAAI 2021
Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate
ICLR 2021