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Sampling

22 directly classified papers

Papers per year

Papers

FedCS: Coreset Selection for Federated Learning CVPR 2025
Length Controlled Generation for Black-box LLMs ACL 2025
Top-n𝜎: Eliminating Noise in Logit Space for Robust Token Sampling of LLM ACL 2025
Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion NIPS 2024
DISCount: Counting in Large Image Collections with Detector-Based Importance Sampling AAAI 2024
Local and Global Decoding in Text Generation EMNLP 2024
Continuously Tempered PDMP samplers NIPS 2022
Perfect Sampling from Pairwise Comparisons NIPS 2022
Top Two Algorithms Revisited NIPS 2022
Learning Influence Adoption in Heterogeneous Networks AAAI 2022
IQDet: Instance-Wise Quality Distribution Sampling for Object Detection CVPR 2021
Recovery of sparse linear classifiers from mixture of responses NIPS 2020
Primal Dual Interpretation of the Proximal Stochastic Gradient Langevin Algorithm NIPS 2020
On Importance Sampling-Based Evaluation of Latent Language Models ACL 2020
On Testing of Samplers NIPS 2020
Stochastic Proximal Langevin Algorithm: Potential Splitting and Nonasymptotic Rates NIPS 2019
Importance sampling for unbiased on-demand evaluation of knowledge base population EMNLP 2017
Reflection, Refraction, and Hamiltonian Monte Carlo NIPS 2015
Flexible sampling of discrete data correlations without the marginal distributions NIPS 2013
Dynamic Pruning of Factor Graphs for Maximum Marginal Prediction NIPS 2012
Continuous Relaxations for Discrete Hamiltonian Monte Carlo NIPS 2012
Simultaneous Sampling and Multi-Structure Fitting with Adaptive Reversible Jump MCMC NIPS 2011