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

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31

52

189

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382

457

787

816

828

1,066

1,391

1,913

3,012

3,646

4,303

4,450

5,357

6,155

5,854

1,521

2000

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Papers (including subtopics)

Learning Compact Recurrent Neural Networks With Block-Term Tensor Decomposition CVPR 2018 Learning Compressed Transforms with Low Displacement Rank NeurIPS 2018 “Learning-Compression” Algorithms for Neural Net Pruning CVPR 2018 Learning Concave Conditional Likelihood Models for Improved Analysis of Tandem Mass Spectra NeurIPS 2018 Learning Continuous Time Bayesian Networks in Non-stationary Domains IJCAI 2018 Learning convex bounds for linear quadratic control policy synthesis NeurIPS 2018 Learning convex polytopes with margin NeurIPS 2018 Learning Deep ResNet Blocks Sequentially using Boosting Theory ICML 2018 Learning Diffusion using Hyperparameters ICML 2018 Learning Discrete Weights Using the Local Reparameterization Trick ICLR 2018 Learning Distributions of Shape Trajectories From Longitudinal Datasets: A Hierarchical Model on a Manifold of Diffeomorphisms CVPR 2018 Learning Features from Co-occurrences: A Theoretical Analysis COLING 2018 Learning from Comparisons and Choices JMLR 2018 Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds NeurIPS 2018 Learning Generative Models with Sinkhorn Divergences AISTATS 2018 Learning Hidden Markov Models from Pairwise Co-occurrences with Application to Topic Modeling ICML 2018 Learning Hierarchical Structures On-The-Fly with a Recurrent-Recursive Model for Sequences ACL 2018 Learning Implicit Generative Models with the Method of Learned Moments ICML 2018 Learning in Integer Latent Variable Models with Nested Automatic Differentiation ICML 2018 Learning in Reproducing Kernel Kreı̆n Spaces ICML 2018 Learning Intrinsic Sparse Structures within Long Short-Term Memory ICLR 2018 Learning Latent Semantic Annotations for Grounding Natural Language to Structured Data EMNLP 2018 Learning latent variable structured prediction models with Gaussian perturbations NeurIPS 2018 Learning linear structural equation models in polynomial time and sample complexity AISTATS 2018 Learning Localized Spatio-Temporal Models From Streaming Data ICML 2018