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Optimization & Theory

43,292 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

1
52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Illuminating Mario Scenes in the Latent Space of a Generative Adversarial Network AAAI 2021 Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels ICLR 2021 Image Generation using Continuous Filter Atoms NeurIPS 2021 Image Inpainting With External-Internal Learning and Monochromic Bottleneck CVPR 2021 Image Super-Resolution With Non-Local Sparse Attention CVPR 2021 Impact of Aliasing on Generalization in Deep Convolutional Networks ICCV 2021 Implicit Bias of Linear RNNs ICML 2021 Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity NeurIPS 2021 Implicit Convex Regularizers of CNN Architectures: Convex Optimization of Two- and Three-Layer Networks in Polynomial Time ICLR 2021 Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods NeurIPS 2021 Implicit Finite-Horizon Approximation and Efficient Optimal Algorithms for Stochastic Shortest Path NeurIPS 2021 Implicit Gradient Regularization ICLR 2021 Implicit Kernel Attention AAAI 2021 Implicit Langevin Algorithms for Sampling From Log-concave Densities JMLR 2021 Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions NeurIPS 2021 Implicit rate-constrained optimization of non-decomposable objectives ICML 2021 Implicit Regularization in Matrix Sensing via Mirror Descent NeurIPS 2021 Implicit Regularization in ReLU Networks with the Square Loss COLT 2021 Implicit Regularization in Tensor Factorization ICML 2021 Implicit Regularization via Neural Feature Alignment AISTATS 2021 Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning JMLR 2021 Implicit Sparse Regularization: The Impact of Depth and Early Stopping NeurIPS 2021 Implicit Task-Driven Probability Discrepancy Measure for Unsupervised Domain Adaptation NeurIPS 2021 Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning ICLR 2021 Implicit Unlikelihood Training: Improving Neural Text Generation with Reinforcement Learning EACL 2021