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Sampling

58 directly classified papers

Papers per year

Papers

Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent NIPS 2022
IQDet: Instance-Wise Quality Distribution Sampling for Object Detection CVPR 2021
A Gradient Based Strategy for Hamiltonian Monte Carlo Hyperparameter Optimization ICML 2021
Primal Dual Interpretation of the Proximal Stochastic Gradient Langevin Algorithm NIPS 2020
On Importance Sampling-Based Evaluation of Latent Language Models ACL 2020
Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration NIPS 2020
Sampling from a k-DPP without looking at all items NIPS 2020
Neutralizing Self-Selection Bias in Sampling for Sortition NIPS 2020
Bridging the Gap Between Anchor-Based and Anchor-Free Detection via Adaptive Training Sample Selection CVPR 2020
Stein Self-Repulsive Dynamics: Benefits From Past Samples NIPS 2020
Training for Gibbs Sampling on Conditional Random Fields with Neural Scoring Factors EMNLP 2020
On Testing of Uniform Samplers AAAI 2019
Random Tessellation Forests NIPS 2019
Sampling Matters! An Empirical Study of Negative Sampling Strategies for Learning of Matching Models in Retrieval-based Dialogue Systems EMNLP 2019
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates NIPS 2019
Determinantal Point Processes for Coresets JMLR 2019
Learning Erdos-Renyi Random Graphs via Edge Detecting Queries NIPS 2019
Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo NIPS 2018
Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation NIPS 2018
Geometrically Coupled Monte Carlo Sampling NIPS 2018
Sampling Informative Training Data for RNN Language Models ACL 2018
Importance sampling for unbiased on-demand evaluation of knowledge base population EMNLP 2017
Measuring Sample Quality with Stein's Method NIPS 2015
Approximate Slice Sampling for Bayesian Posterior Inference AISTATS 2014
A* Sampling NIPS 2014