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

Differential Network Analysis NSDI 2022 Differential privacy and robust statistics in high dimensions COLT 2022 Different Tunes Played with Equal Skill: Exploring a Unified Optimization Subspace for Parameter-Efficient Tuning EMNLP 2022 DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism AAAI 2022 Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme ICLR 2022 Digging Errors in NMT: Evaluating and Understanding Model Errors from Partial Hypothesis Space EMNLP 2022 Dimensionality Reduction and Prioritized Exploration for Policy Search AISTATS 2022 Dimension-free Complexity Bounds for High-order Nonconvex Finite-sum Optimization ICML 2022 Dimension-free convergence rates for gradient Langevin dynamics in RKHS COLT 2022 DIMES: A Differentiable Meta Solver for Combinatorial Optimization Problems NeurIPS 2022 Dim-Krum: Backdoor-Resistant Federated Learning for NLP with Dimension-wise Krum-Based Aggregation EMNLP 2022 DiPS: Differentiable Policy for Sketching in Recommender Systems AAAI 2022 DiRe Committee : Diversity and Representation Constraints in Multiwinner Elections IJCAI 2022 Direct Voxel Grid Optimization: Super-Fast Convergence for Radiance Fields Reconstruction CVPR 2022 Discourse Context Predictability Effects in Hindi Word Order EMNLP 2022 DISCOVERING AND EXPLAINING THE REPRESENTATION BOTTLENECK OF DNNS ICLR 2022 Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian Inference AISTATS 2022 Discovering Interpretable Data-to-Sequence Generators AAAI 2022 Discovery and density estimation of latent confounders in Bayesian networks with evidence lower bound PGM 2022 Discrete Probabilistic Inverse Optimal Transport ICML 2022 Discriminative Similarity for Data Clustering ICLR 2022 Discriminator-Guided Model-Based Offline Imitation Learning CoRL 2022 Disentanglement Analysis with Partial Information Decomposition ICLR 2022 Disentangling Confidence Score Distribution for Out-of-Domain Intent Detection with Energy-Based Learning EMNLP 2022 Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning ICML 2022