conftrace_

Optimization & Theory

36,874 papers (3 classified directly here)

Subtopics

Optimization (14,983) Bayesian Inference (5,566) Learning Theory (5,334) Theory (4,955) Statistical Learning (4,117) Neural Network Optimization (3,649) Stochastic Processes (2,667) Loss Functions (1,162) Distributed Learning (1,135) Stochastic Methods (1,118) Online Algorithms (806) Statistics (684) Information Theory (318) Generalization (220) Sparse Optimization (158) Sample Complexity (99) Game Theory (30) Robust Optimization (17) Optimal Transport (14) Approximation Algorithms (10) Distributed Optimization (8) Convex Optimization (8)

Papers per year

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Papers (including subtopics)

Natural Gradients in Practice: Non-Conjugate Variational Inference in Gaussian Process Models AISTATS 2018
Variational inference for the multi-armed contextual bandit AISTATS 2018
Tracking the gradients using the Hessian: A new look at variance reducing stochastic methods AISTATS 2018
Subsampling for Ridge Regression via Regularized Volume Sampling AISTATS 2018
Scalable Gaussian Processes with Billions of Inducing Inputs via Tensor Train Decomposition AISTATS 2018
Batch-Expansion Training: An Efficient Optimization Framework AISTATS 2018
Batched Large-scale Bayesian Optimization in High-dimensional Spaces AISTATS 2018
Temporally-Reweighted Chinese Restaurant Process Mixtures for Clustering, Imputing, and Forecasting Multivariate Time Series AISTATS 2018
Stochastic Three-Composite Convex Minimization with a Linear Operator AISTATS 2018
Direct Learning to Rank And Rerank AISTATS 2018
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD AISTATS 2018
Variational Inference based on Robust Divergences AISTATS 2018
Variational Rejection Sampling AISTATS 2018
Best arm identification in multi-armed bandits with delayed feedback AISTATS 2018
Contextual Bandits with Stochastic Experts AISTATS 2018
Community Detection in Hypergraphs: Optimal Statistical Limit and Efficient Algorithms AISTATS 2018
Robust Maximization of Non-Submodular Objectives AISTATS 2018
Tree-based Bayesian Mixture Model for Competing Risks AISTATS 2018
Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information AISTATS 2018
Quotient Normalized Maximum Likelihood Criterion for Learning Bayesian Network Structures AISTATS 2018
Variational Sequential Monte Carlo AISTATS 2018
Statistically Efficient Estimation for Non-Smooth Probability Densities AISTATS 2018
SDCA-Powered Inexact Dual Augmented Lagrangian Method for Fast CRF Learning AISTATS 2018
Generalized Concomitant Multi-Task Lasso for Sparse Multimodal Regression AISTATS 2018
Gradient Layer: Enhancing the Convergence of Adversarial Training for Generative Models AISTATS 2018