Adaptive Sampling

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Period ending 2026-09-14

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Period ending 2026-09-07

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A weekly snapshot of new work published in Adaptive Sampling.

82 papers

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Tight Sampling Complexity with stochastic gradient oracles in Fixed Dimensions
Sep 14, 2026Weiming Ou, Xiao WangAdaptive Sampling
Optimal Slice-Adaptive Tuning of Hybrid Slice Sampling
Sep 8, 2026Trevor CampbellMonte Carlo Sampling Adaptive Sampling
ASSERT: Adaptive Stochastic Sampling for Robust Diffusion Models on Analog Compute-in-Memory Hardware
Sep 1, 2026Yuannuo Feng, Yizhe Chen, Wenshuai Yao +4Diffusion Models In-Memory Computing
Batch Size or Negatives? A Selection Rule for Memory-Constrained Recommender Training
Aug 11, 2026Artyom Sabitov, Daniil Volkov, Alexey ZaytsevRecommender Systems Batch Size
PAST: Prompt-Adaptive Sampling Termination for Efficient Diffusion Model
Aug 7, 2026Renye Yan, Jikang Cheng, You Wu +4Diffusion Models Reward Gradients
Interpretable Adaptive Sampling for LLM Test-Time Scaling
Aug 4, 2026Mobina Kashaniyan, Ali JannesariTest-Time Scaling Test Time
Adaptive Sampling for Automated Post-Disaster Rapid Damage Assessment via Level-Set Cost-Aware Bayesian Optimization
Aug 3, 2026Boyang Xu, Mostafa Reisi Gahrooei, Mohammad Ilbeigi +1Post-Disaster Damage Assessment Disasters
Characterizing Bias in Post-Bandit Inference under Index Algorithms
Aug 2, 2026Lisu Wang, Yilun Chen, Jiaqi LuGeneralized Linear Bandit Lightweight Tabular Contextual Bandit
Commit Locally, Exit Globally: Coordinating Adaptive Sampling and Early Exit in Diffusion Language Models
Jul 30, 2026Chia-Ming Lee, Shao-Kai Liu, Ming-Ching Chang +3Diffusion Language Models Adaptive Sampling
Endo-NeRF++: Uncertainty-Aware Neural Rendering with Multi-Resolution Hash Encoding for Dynamic Surgical Scene Reconstruction
Jul 30, 2026Gousia Habib, Laura RuotsalainenNeural Rendering Adaptive Shape Refinement
BayesAME: Bayesian Active Model Evaluation
Jul 29, 2026Paula Cordero Encinar, Taylan Cemgil, Arnaud Doucet +2Geometry-Aware Uncertainty Coresets Model Selection
Understanding Context Sampling in TabPFN on Small Tabular Datasets
Jul 29, 2026Mohammed AbdullahTabular Learning Tabular Data
Guiding Posterior Exploration with Optimizer-Derived Geometry
Jul 28, 2026Moritz Schlager, Emanuel Sommer, Thomas Möllenhoff +1Adaptive Sampling Bayesian Neural Networks
Adaptive Data Admission and Retention for Streaming Federated Learning
Jul 27, 2026Zhuoyi Zhao, Ben LiangAdaptive Sampling Retention
Learning Sampling Parameters for Diffusion Models
Jul 26, 2026Arisrei Lim, Yossi GandelsmanDiffusion Models Adaptive Sampling
From Perturbation Correction to Geometry-Aware Sampling: Sharpness-Guided Equilibrium Sampling for Balanced Flat Minima in Long-Tailed Learning
Jul 24, 2026Jiaxin Deng, Junbiao PangSharpness-Aware Minimization Adaptive Sampling
Frequency-Hierarchical Active k-Space Sampling for Diagnostic MRI
Jul 22, 2026Ruru Xu, Kian Anvari Hamedani, Zhikai Yang +1Adaptive Sampling Magnetic Resonance Imaging
The Tractability Landscape of Sampling with Inexact Scores
Jul 21, 2026Anming Gu, Kevin Tian, Hubert Yang +1Adaptive Sampling Gibbs Measures
Scalable Model-Assisted Multi-Target Estimation in Large Image Collections
Jul 20, 2026Max Hamilton, Jinlin Lai, Daniel Sheldon +1Adaptive Sampling Ground Truth
Information-Directed Sampling for Causal Bandits
Jul 17, 2026Muhammad Qasim Elahi, Murat Kocaoglu, Mahsa GhasemiLightweight Tabular Contextual Bandit Linear Regret
Confidence-based Ranking with Adaptive Sampling for Noisy Black-Box Optimisation
Jul 16, 2026Enrico Halim, Hemant Kumar Singh, Tapabrata RayEvolutionary Algorithms Adaptive Sampling
Information-Theoretic Adaptive Cooling for Deterministic MPPI via Entropy Feedback
Jul 15, 2026Shuqi Wang, Wenrong Sun, Tao Han +2Model Predictive Path Integral Optimal Control
Advancing Optimal Subset Oracle via Learning Relaxation of Neural Set Functions
Jul 13, 2026Yongquan Shi, Zijing Ou, Shiping Wang +1Variational Inference Surrogate Gradient
Efficient Online Proportional Sampling with Applications to Smoothed Online Learning
Jul 13, 2026Amirmahdi Mirfakhar, Maria-Florina Balcan, Hedyeh BeyhaghiLearning-Augmented Algorithms Sublinear Regret
Is Randomness Necessary for Adaptive Data Analysis?
Jul 8, 2026Edith Cohen, Haim Kaplan, Yishay Mansour +2Adaptive Adversary Data Collection
Sensitivity Sampling with Predictions for k-Means Clustering
Jul 6, 2026Cristian Boldrin, Fabio VandinK$-Means Clustering
Sampling Bias Compensation for Robust Evaluation of Audio Classification Systems with Partially Labeled Evaluation Datasets
Jul 5, 2026Javier Naranjo-Alcazar, Annamaria Mesaros, Tuomas Virtanen +1Audio Classification Acoustic Representation
Optimal Mixture-of-Experts Model Averaging for Conditional Generative Models
Jul 5, 2026Shijin Gong, Baihua He, Xinyu ZhangGenerative Models Mixture-Of-Experts Layer
Self-Improving Diffusion Classifiers with Minority Preference Optimization
Jul 4, 2026Hyunsoo Kim, Jungmyung Wi, Soobin Um +2Diffusion Models Minority
CuBAS: Information Geometric Curvature-Based Adaptive Sampling for Supervised Classification
Jul 3, 2026Alexandre L. M. LevadaStatistical Manifold Adaptive Sampling
UT-AISTimprt submission for ICME 2026 Grand Challenge on Academic Text-to-Music Generation
Jul 2, 2026Shunsuke Yoshida, Yu-Hua Chen, Satoru FukayamaGenerative Music Models Audio Reasoning
Decision-Aware Training for Sample-Based Generative Models
Jul 1, 2026Kornelius Raeth, Nicole LudwigGenerative Models Score Function
Stochastic Gradient Optimization with Model-Assisted Sampling
Jun 25, 2026Jonne Pohjankukka, Jukka HeikkonenStochastic Gradient Descent Variance Reduction
Stabilizing black-box algorithms through task-oriented randomization
Jun 24, 2026Yali Wang, Zhaojun WangRandom Black Box
Flow-Corrected Thompson Sampling for Non-Stationary Contextual Bandits
Jun 22, 2026AmirHossein Naghdi, Ali BaheriThompson Sampling Non-Stationarity
FPAS: Frontier-Based Path Planning with Adaptive Sampling for Large-Scale Unknown Environments
Jun 22, 2026Jinwoo Choi, Yeonkyu Lee, Jung-Taak Kim +2Efficient Path Planning Adaptive Sampling
AdaPrivate-TS: Private Thompson Sampling for Contextual Bandits with Privacy Amplification
Jun 19, 2026Mohammadreza Riyazat, Eranga UkwattaMulti-Objective Bandits Thompson Sampling
Denoising Implicit Feedback for Cold-start Recommendation
Jun 17, 2026Gaode Chen, Shicheng Wang, Shikun Li +8Cold-Start Recommender Systems
Uncertainty Quantification of Engineering Structures by Polynomial Chaos Expansion and Multivariate Active Learning
Jun 15, 2026Qitian Lu, Jafar Jafari-Asl, Panagiotis Spyridis +1Surrogate Modeling Uncertainty Quantification
LESS Is More: Mutual-Stability Sampling for Diffusion Language Models
Jun 15, 2026Amr Mohamed, Guokan Shang, Michalis VazirgiannisDiffusion Language Models Diffusion Models
Calibrated Sampling-Free Uncertainty Estimation in Bayesian Deep Learning
Jun 15, 2026Tobias Jan Wieczorek, Leon de Andrade, Thomas Möllenhoff +1Bayesian Neural Networks Adaptive Sampling
Learning Task-Aware Sampling with Shared Saliency through Density-Equalizing Mappings
Jun 11, 2026Tsz Lok Ip, Han Zhang, Lok Ming LuiReceptive Fields Convolutional Neural Networks
The Power of Test-Time Training for Approximate Sampling
Jun 9, 2026Noah Golowich, Ankur Moitra, Dhruv RohatgiAdaptive Sampling Inference-Time
Attention-Discounted Adaptive Sampler for Masked Diffusion Language Models
Jun 9, 2026Yusuf Sahin, Ahmed Rockey Saikia, Volkan Cevher +1Masked Diffusion Language Models Diffusion Language Models
Frequency-based Constrained Sampling for Interval Patterns
Jun 8, 2026Djawad Bekkoucha, Abdelkader Ouali, Bruno CrémilleuxData Mining Adaptive Sampling
Generative Frontier Planning for Adaptive Peer-Referral Recruitment under Covariate-Dependent Arrivals
Jun 6, 2026Lingkai Kong, Hezi Jiang, Andrew Ma +3Optimal Comparison Allocation Adaptive Sampling
DAS-PINNs for high-dimensional partial differential equations: extending deep adaptive sampling to spacetime domains
Jun 4, 2026Anshima Singh, David J. SilvesterPartial Differential Equations Euler Discretization
Reactive Flux Matching: Mechanism Discovery and Adaptive Sampling of Rare Events
Jun 4, 2026Rishal Aggarwal, David Ryan Koes, Nicholas M. Boffi +1Conditional Flow Matching Incomplete Kinetics
Small RL Controller, Large Language Model: RL-Guided Adaptive Sampling for Test-Time Scaling
Jun 2, 2026Runpeng Dai, Tong Zheng, Rui Liu +2Test-Time Scaling Adaptive Sampling
Towards Efficient LLMs Annealing with Principled Sample Selection
May 29, 2026Yuanjian Xu, Jianing Hao, Wanbo Zhang +2Efficient Data Selection Cosine Annealing
Parallel Tempering Initial Sampling in Inference-Time Reward Alignment
May 29, 2026Myeongjun Oh, Gwangho Kim, Sungyoon LeeReward Gradients Adaptive Sampling
The Sample Complexity of Multiclass and Sparse Contextual Bandits
May 28, 2026Liad Erez, Fan Chen, Alon Cohen +4Sample Complexity Sparse Rewards
Bridging the Sampling Distribution Shift in Radio Map Estimation: A Trajectory-Aware Paradigm
May 27, 2026Feng Qiu, Zheng Fang, Shuhang Zhang +4Unmanned Aerial Vehicle Trajectories Trajectory-Based Representations
Uncertainty-Aware Budget Allocation for Adaptive Test-Time Reasoning
May 26, 2026Manh Nguyen, Sunil Gupta, Hung LeLLM Reasoning Methods Budgets
A computational phase transition for learning-to-sample from Ising models
May 23, 2026Andrej Risteski, Thuy-Duong VuongTwo-Dimensional Ising Model Phase Transitions
Active Context Selection Improves Simple Regret in Contextual Bandits
May 19, 2026Mohammad Shahverdikondori, Jalal Etesami, Negar KiyavashMulti-Objective Bandits Adaptive Sampling
EviTrack: Selection over Sampling for Delayed Disambiguation
May 19, 2026Omer HaqLatent Trajectories Adaptive Sampling
Federated Martingale Posterior Samping
May 18, 2026Boning Zhang, Matteo Zecchin, Mingzhao Guo +2Bayesian Neural Networks Posterior
SIREM: Speech-Informed MRI Reconstruction with Learned Sampling
May 18, 2026Md Hasan, Nyvenn Castro, Daiqi Liu +6Magnetic Resonance Imaging Reconstruction Vocalizations
Curriculum Group Policy Optimization: Adaptive Sampling for Unleashing the Potential of Text-to-Image Generation
May 18, 2026Baoteng Li, Xianghao Zang, Xinran Wang +8Repair-Based Group-Relative Policy Optimization Unified Generative Framework

Sep 14, 2026 · math.STJ/K move · Enter open · S save

Tight Sampling Complexity with stochastic gradient oracles in Fixed Dimensions

Weiming Ou, Xiao Wang

We investigate the stochastic-gradient query complexity of sampling smooth strongly log-concave distributions in any fixed Euclidean dimension. The potential is

\mu

-strongly convex and

L

-smooth, with an unknown mode in the ball of radius

\mu^{-1/2}

about the origin. We have access to unbiased stochastic oracles with the variance at most

\sigma^2

. For every

\sigma^2\ge0

and total variation (TV) accuracy

0<\varepsilon\le1/10

, we prove that the tight complexity of sampling a distribution within

\epsilon

-TV distance from the target distribution is

N^\star_{\text{TV}}=\Theta\!\left(\log(1+\kappa)+ \frac{\sigma^2}{\mu\epsilon}\right),

where

\kappa:=\frac L\mu

is the condition number. Note that this complexity bound is simultaneously tight for the condition number

\kappa

and accuracy

\epsilon

. Besides, our tight complexity bound is adaptive to noiseless setting

\sigma=0

, which is

N^\star_{\text{TV}}=\Theta\!\left(\log(1+\kappa)\right)

Adaptive Sampling

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