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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)

Latent Autoregressive Source Separation AAAI 2023 Latent Neural ODEs with Sparse Bayesian Multiple Shooting ICLR 2023 Latent Positional Information is in the Self-Attention Variance of Transformer Language Models Without Positional Embeddings ACL 2023 Latent SDEs on Homogeneous Spaces NeurIPS 2023 LAVA: Data Valuation without Pre-Specified Learning Algorithms ICLR 2023 Law of Large Numbers for Bayesian two-layer Neural Network trained with Variational Inference COLT 2023 Layer-Neighbor Sampling --- Defusing Neighborhood Explosion in GNNs NeurIPS 2023 Layer-Wise Adaptive Model Aggregation for Scalable Federated Learning AAAI 2023 Laziness Is a Virtue When It Comes to Compositionality in Neural Semantic Parsing ACL 2023 Lazy-k Decoding: Constrained Decoding for Information Extraction EMNLP 2023 L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based Inference NeurIPS 2023 LCS: Learning Compressible Subspaces for Efficient, Adaptive, Real-Time Network Compression at Inference Time WACV 2023 Leaky Hockey Stick Loss: The First Negatively Divergent Margin-based Loss Function for Classification JMLR 2023 LEAN-DMKDE: Quantum Latent Density Estimation for Anomaly Detection (Student Abstract) AAAI 2023 Learnability and Algorithm for Continual Learning ICML 2023 Learnable Surrogate Gradient for Direct Training Spiking Neural Networks IJCAI 2023 Learned Adapters Are Better Than Manually Designed Adapters ACL 2023 Learned Compressive Representations for Single-Photon 3D Imaging ICCV 2023 Learned Index with Dynamic ε ICLR 2023 Learning Activation Functions for Sparse Neural Networks AutoML 2023 Learning Adaptive Tensorial Density Fields for Clean Cryo-ET Reconstruction NeurIPS 2023 Learning a Depth Covariance Function CVPR 2023 Learning Adversarial Linear Mixture Markov Decision Processes with Bandit Feedback and Unknown Transition ICLR 2023 Learning Adversarial Low-rank Markov Decision Processes with Unknown Transition and Full-information Feedback NeurIPS 2023 Learning Analytical Posterior Probability for Human Mesh Recovery CVPR 2023