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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)

Delay-Adaptive Step-sizes for Asynchronous Learning ICML 2022 Delving into Sample Loss Curve to Embrace Noisy and Imbalanced Data AAAI 2022 Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization ICLR 2022 Demystifying the Adversarial Robustness of Random Transformation Defenses ICML 2022 Demystifying the Neural Tangent Kernel From a Practical Perspective: Can It Be Trusted for Neural Architecture Search Without Training? CVPR 2022 Demystifying Why Local Aggregation Helps: Convergence Analysis of Hierarchical SGD AAAI 2022 Denoising and change point localisation in piecewise-constant high-dimensional regression coefficients AISTATS 2022 Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data MLHC 2022 Density Ratio Estimation via Infinitesimal Classification AISTATS 2022 Dependent randomized rounding for clustering and partition systems with knapsack constraints JMLR 2022 Depth and Feature Learning are Provably Beneficial for Neural Network Discriminators COLT 2022 Depth is More Powerful than Width with Prediction Concatenation in Deep Forest NeurIPS 2022 Depth separation beyond radial functions JMLR 2022 (De-)Randomized Smoothing for Decision Stump Ensembles NeurIPS 2022 Derivative-Based Neural Modelling of Cumulative Distribution Functions for Survival Analysis AISTATS 2022 Derivatives and residual distribution of regularized M-estimators with application to adaptive tuning COLT 2022 Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks NeurIPS 2022 De-Sequentialized Monte Carlo: a parallel-in-time particle smoother JMLR 2022 Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization ICML 2022 DESTR: Object Detection With Split Transformer CVPR 2022 Detached Error Feedback for Distributed SGD with Random Sparsification ICML 2022 Detecting Dissonant Stance in Social Media: The Role of Topic Exposure EMNLP 2022 Detecting Misclassification Errors in Neural Networks with a Gaussian Process Model AAAI 2022 Detecting Textual Adversarial Examples Based on Distributional Characteristics of Data Representations ACL 2022 Detecting Unintended Memorization in Language-Model-Fused ASR Interspeech 2022