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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)

Investigating data partitioning strategies for crosslinguistic low-resource ASR evaluation EACL 2023 Investigating how ReLU-networks encode symmetries NeurIPS 2023 Investigating model performance in language identification: beyond simple error statistics Interspeech 2023 Investigating the Effect of Discourse Connectives on Transformer Surprisal: Language Models Understand Connectives, Even So They Are Surprised EMNLP 2023 Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks? ICML 2023 Is Distance Matrix Enough for Geometric Deep Learning? NeurIPS 2023 Ising-Traffic: Using Ising Machine Learning to Predict Traffic Congestion under Uncertainty AAAI 2023 Is interpolation benign for random forest regression? AISTATS 2023 Is Learning in Games Good for the Learners? NeurIPS 2023 Is Learning Summary Statistics Necessary for Likelihood-free Inference? ICML 2023 Isometric Quotient Variational Auto-Encoders for Structure-Preserving Representation Learning NeurIPS 2023 Isotropic Gaussian Processes on Finite Spaces of Graphs AISTATS 2023 Is Overfitting Necessary for Implicit Video Representation? ICML 2023 Is Planted Coloring Easier than Planted Clique? COLT 2023 Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification ICLR 2023 Is the volume of a credal set a good measure for epistemic uncertainty? UAI 2023 Is This Loss Informative? Faster Text-to-Image Customization by Tracking Objective Dynamics NeurIPS 2023 Is Your Noise Correction Noisy? PLS: Robustness To Label Noise With Two Stage Detection WACV 2023 Iterated Block Particle Filter for High-dimensional Parameter Learning: Beating the Curse of Dimensionality JMLR 2023 Iterative Approximate Cross-Validation ICML 2023 Iterative autoregression: a novel trick to improve your low-latency speech enhancement model Interspeech 2023 Iteratively Enhanced Semidefinite Relaxations for Efficient Neural Network Verification AAAI 2023 Iterative Teaching by Data Hallucination AISTATS 2023 It’s about Time: Rethinking Evaluation on Rumor Detection Benchmarks using Chronological Splits EACL 2023 It’s MBR All the Way Down: Modern Generation Techniques Through the Lens of Minimum Bayes Risk EMNLP 2023