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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

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Papers (including subtopics)

Knowledge Augmented Deep Neural Networks for Joint Facial Expression and Action Unit Recognition NeurIPS 2020 Knowledge-Based Regularization in Generative Modeling IJCAI 2020 Knowledge Base Embedding By Cooperative Knowledge Distillation COLING 2020 Kriging Prediction with Isotropic Matern Correlations: Robustness and Experimental Designs JMLR 2020 Krylov Subspace Method for Nonlinear Dynamical Systems with Random Noise JMLR 2020 k-SDPP: Fixed-Size Video Summarization via Sequential Determinantal Point Processes IJCAI 2020 KungFu: Making Training in Distributed Machine Learning Adaptive OSDI 2020 Kvell+: Snapshot Isolation without Snapshots OSDI 2020 L2-GCN: Layer-Wise and Learned Efficient Training of Graph Convolutional Networks CVPR 2020 Lagrangian Decomposition for Neural Network Verification UAI 2020 Lagrangian Fluid Simulation with Continuous Convolutions ICLR 2020 Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks ICML 2020 Langevin Monte Carlo without smoothness AISTATS 2020 Language Model Prior for Low-Resource Neural Machine Translation EMNLP 2020 Laplacian-Regularized Graph Bandits: Algorithms and Theoretical Analysis AISTATS 2020 Large Batch Optimization for Deep Learning: Training BERT in 76 minutes ICLR 2020 Large-Scale Methods for Distributionally Robust Optimization NeurIPS 2020 Last Iterate is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems COLT 2020 Latent Variable Modelling with Hyperbolic Normalizing Flows ICML 2020 Layering-MCMC for Structure Learning in Bayesian Networks UAI 2020 Layerwise Sparse Coding for Pruned Deep Neural Networks with Extreme Compression Ratio AAAI 2020 Lazy-CFR: fast and near-optimal regret minimization for extensive games with imperfect information ICLR 2020 Leakage-Adjusted Simulatability: Can Models Generate Non-Trivial Explanations of Their Behavior in Natural Language? EMNLP 2020 Leakage-Robust Classifier via Mask-Enhanced Training (Student Abstract) AAAI 2020 Learnability with Indirect Supervision Signals NeurIPS 2020