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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
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828
3,646
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2000
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Papers (including subtopics)

Lightweight Probabilistic Deep Networks CVPR 2018 Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data ICML 2018 Limbic: Author-Based Sentiment Aspect Modeling Regularized with Word Embeddings and Discourse Relations EMNLP 2018 Limitations in learning an interpreted language with recurrent models EMNLP 2018 Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design ICML 2018 Linear Spectral Estimators and an Application to Phase Retrieval ICML 2018 Linear Stochastic Approximation: How Far Does Constant Step-Size and Iterate Averaging Go? AISTATS 2018 Lipschitz Continuity in Model-based Reinforcement Learning ICML 2018 Lipschitz regularity of deep neural networks: analysis and efficient estimation NeurIPS 2018 Local and Global Optimization Techniques in Graph-Based Clustering CVPR 2018 Local Convergence Properties of SAGA/Prox-SVRG and Acceleration ICML 2018 Local Identifiability of ℓ_1-minimization Dictionary Learning: a Sufficient and Almost Necessary Condition JMLR 2018 Localized Incomplete Multiple Kernel k-means IJCAI 2018 Local Minima, Heavy Tails, and Search Effort for GBFS IJCAI 2018 Local moment matching: A unified methodology for symmetric functional estimation and distribution estimation under Wasserstein distance COLT 2018 Local Optimality and Generalization Guarantees for the Langevin Algorithm via Empirical Metastability COLT 2018 Local Private Hypothesis Testing: Chi-Square Tests ICML 2018 Local Rademacher Complexity-based Learning Guarantees for Multi-Task Learning JMLR 2018 Log-concave sampling: Metropolis-Hastings algorithms are fast! COLT 2018 Logistic Regression: The Importance of Being Improper COLT 2018 Long Short-Term Memory as a Dynamically Computed Element-wise Weighted Sum ACL 2018 Long-Term Human Motion Prediction by Modeling Motion Context and Enhancing Motion Dynamics IJCAI 2018 Loss-aware Weight Quantization of Deep Networks ICLR 2018 Loss Functions for Multiset Prediction NeurIPS 2018 Loss Surfaces, Mode Connectivity, and Fast Ensembling of DNNs NeurIPS 2018