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)

Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems AISTATS 2019
Contrasting Exploration in Parameter and Action Space: A Zeroth-Order Optimization Perspective AISTATS 2019
Sampling from Non-Log-Concave Distributions via Variance-Reduced Gradient Langevin Dynamics AISTATS 2019
A maximum-mean-discrepancy goodness-of-fit test for censored data AISTATS 2019
Sobolev Descent AISTATS 2019
A Fast Sampling Algorithm for Maximum Inner Product Search AISTATS 2019
Minimum Volume Topic Modeling AISTATS 2019
Binary Space Partitioning Forest AISTATS 2019
Optimizing over a Restricted Policy Class in MDPs AISTATS 2019
Stochastic Gradient Descent on Separable Data: Exact Convergence with a Fixed Learning Rate AISTATS 2019
Structured Robust Submodular Maximization: Offline and Online Algorithms AISTATS 2019
Probabilistic Multilevel Clustering via Composite Transportation Distance AISTATS 2019
A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes AISTATS 2019
Online Algorithm for Unsupervised Sensor Selection AISTATS 2019
Best of many worlds: Robust model selection for online supervised learning AISTATS 2019
Online Learning in Kernelized Markov Decision Processes AISTATS 2019
Lifting high-dimensional non-linear models with Gaussian regressors AISTATS 2019
Database Alignment with Gaussian Features AISTATS 2019
Reparameterizing Distributions on Lie Groups AISTATS 2019
Revisit Batch Normalization: New Understanding and Refinement via Composition Optimization AISTATS 2019
Multi-Order Information for Working Set Selection of Sequential Minimal Optimization AISTATS 2019
Harmonizable mixture kernels with variational Fourier features AISTATS 2019
Multiscale Gaussian Process Level Set Estimation AISTATS 2019
Adversarial Learning of a Sampler Based on an Unnormalized Distribution AISTATS 2019
Active Ranking with Subset-wise Preferences AISTATS 2019