Skip to content
conftrace_

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
'5
'10
'15
'20
'25

Papers (including subtopics)

In and Out-of-Domain Text Adversarial Robustness via Label Smoothing ACL 2023 IncDSI: Incrementally Updatable Document Retrieval ICML 2023 Incentive-aware Contextual Pricing with Non-parametric Market Noise AISTATS 2023 Incentive-Compatible Selection for One or Two Influentials IJCAI 2023 Incentives in Private Collaborative Machine Learning NeurIPS 2023 Incentivizing honest performative predictions with proper scoring rules UAI 2023 Incentivizing Honesty among Competitors in Collaborative Learning and Optimization NeurIPS 2023 Inconsistency, Instability, and Generalization Gap of Deep Neural Network Training NeurIPS 2023 Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach AISTATS 2023 Incorporating L2 Phonemes Using Articulatory Features for Robust Speech Recognition Interspeech 2023 Incorporating Syntactic Knowledge into Pre-trained Language Model using Optimization for Overcoming Catastrophic Forgetting EMNLP 2023 Incremental Aggregated Riemannian Gradient Method for Distributed PCA AISTATS 2023 Incremental and Decremental Optimal Margin Distribution Learning IJCAI 2023 Incremental Learning in Diagonal Linear Networks JMLR 2023 Incremental Nonlinear Dynamic Inversion based Optical Flow Control for Flying Robots: An Efficient Data-driven Approach RSS 2023 In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer NeurIPS 2023 Independent Component Alignment for Multi-Task Learning CVPR 2023 Indirect Adversarial Losses via an Intermediate Distribution for Training GANs WACV 2023 Indirectly Supervised Natural Language Processing ACL 2023 Individualized Dosing Dynamics via Neural Eigen Decomposition NeurIPS 2023 Indoor Depth Recovery Based on Deep Unfolding with Non-Local Prior ICCV 2023 Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation AISTATS 2023 Inductive Bias Is in the Eye of the Beholder EMNLP 2023 Inequality phenomenon in l_∞-adversarial training, and its unrealized threats ICLR 2023 Inference and sampling of point processes from diffusion excursions UAI 2023