Copertina

Unified Unbiased Variance Estimation for Maximum Mean Discrepancy: Robust Finite-Sample Performance with Imbalanced Data and Exact Acceleration under Null and Alternative Hypotheses

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhong, Shijie, Yang, Yikun, Gong, Da, Fu, Jiangfeng
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning I.2.6; F.2.2; G.3
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Maximum Mean Discrepancy on Exponential Windows for Online Change Detection
di: Kalinke, Florian, et al.
Pubblicazione: (2022)

Stratified Hazard Sampling: Minimal-Variance Event Scheduling for CTMC/DTMC Discrete Diffusion and Flow Models
di: Jang, Seunghwan, et al.
Pubblicazione: (2026)

Synergy over Discrepancy: A Partition-Based Approach to Multi-Domain LLM Fine-Tuning
di: Ye, Hua, et al.
Pubblicazione: (2025)

Mean-Pooled Cosine Similarity is Not Length-Invariant: Theory and Cross-Domain Evidence for a Length-Invariant Alternative
di: Mitra, Sibayan, et al.
Pubblicazione: (2026)

Variance Is Not Importance: Structural Analysis of Transformer Compressibility Across Model Scales
di: Salfati, Samuel
Pubblicazione: (2026)

ACE: Exploring Activation Cosine Similarity and Variance for Accurate and Calibration-Efficient LLM Pruning
di: Mi, Zhendong, et al.
Pubblicazione: (2025)

Human-Corrected Labels Learning: Enhancing Labels Quality via Human Correction of VLMs Discrepancies
di: Li, Zhongnian, et al.
Pubblicazione: (2025)

ME-IGM: Individual-Global-Max in Maximum Entropy Multi-Agent Reinforcement Learning
di: Chen, Wen-Tse, et al.
Pubblicazione: (2024)

Federated Learning and Class Imbalances
di: Zhu, Siqi, et al.
Pubblicazione: (2026)

StepScorer: Accelerating Reinforcement Learning with Step-wise Scoring and Psychological Regret Modeling
di: Xu, Zhe
Pubblicazione: (2026)

Mallows Model with Learned Distance Metrics: Sampling and Maximum Likelihood Estimation
di: Alimohammadi, Yeganeh, et al.
Pubblicazione: (2025)

Adaptive Epsilon Adversarial Training for Robust Gravitational Wave Parameter Estimation Using Normalizing Flows
di: Yang, Yiqian, et al.
Pubblicazione: (2024)

AI and Machine Learning Approaches for Predicting Nanoparticles Toxicity The Critical Role of Physiochemical Properties
di: Yousaf, Iqra
Pubblicazione: (2024)

Exact and general decoupled solutions of the LMC Multitask Gaussian Process model
di: Truffinet, Olivier, et al.
Pubblicazione: (2023)

From Theory to Practice with RAVEN-UCB: Addressing Non-Stationarity in Multi-Armed Bandits through Variance Adaptation
di: Fang, Junyi, et al.
Pubblicazione: (2025)

Fusing Rewards and Preferences in Reinforcement Learning
di: Khorasani, Sadegh, et al.
Pubblicazione: (2025)

Sample-Efficient Language Model for Hinglish Conversational AI
di: Singh, Sakshi, et al.
Pubblicazione: (2025)

Scalable GPU-Accelerated Euler Characteristic Curves: Optimization and Differentiable Learning for PyTorch
di: Saxena, Udit
Pubblicazione: (2025)

Understanding Variational Autoencoders with Intrinsic Dimension and Information Imbalance
di: Camboulin, Charles, et al.
Pubblicazione: (2024)

Rewarding Beliefs, Not Actions: Consistency-Guided Credit Assignment for Long-Horizon Agents
di: Tang, Wenjie, et al.
Pubblicazione: (2026)

Implicit Counterfactual Data Augmentation for Robust Learning
di: Zhou, Xiaoling, et al.
Pubblicazione: (2023)

Calibrated Confidence Estimation for Tabular Question Answering
di: Voss, Lukas
Pubblicazione: (2026)

Chunked TabPFN: Exact Training-Free In-Context Learning for Long-Context Tabular Data
di: Sergazinov, Renat, et al.
Pubblicazione: (2025)

Online Analytic Exemplar-Free Continual Learning with Large Models for Imbalanced Autonomous Driving Task
di: Zhuang, Huiping, et al.
Pubblicazione: (2024)

KerZOO: Kernel Function Informed Zeroth-Order Optimization for Accurate and Accelerated LLM Fine-Tuning
di: Mi, Zhendong, et al.
Pubblicazione: (2025)

AGOP as Explanation: From Feature Learning to Per-Sample Attribution in Image Classifiers
di: Katakam, Raj Kiran Gupta
Pubblicazione: (2026)

To Bin or not to Bin: Alternative Representations of Mass Spectra
di: de Jonge, Niek, et al.
Pubblicazione: (2025)

TensLoRA: Tensor Alternatives for Low-Rank Adaptation
di: Marmoret, Axel, et al.
Pubblicazione: (2025)

Feel-Good Thompson Sampling for Contextual Bandits: a Markov Chain Monte Carlo Showdown
di: Anand, Emile, et al.
Pubblicazione: (2025)

Balancing the Scales: A Comprehensive Study on Tackling Class Imbalance in Binary Classification
di: Abdelhamid, Mohamed, et al.
Pubblicazione: (2024)

DELTA: Variational Disentangled Learning for Privacy-Preserving Data Reprogramming
di: Malarkkan, Arun Vignesh, et al.
Pubblicazione: (2025)

Evaluating and Learning Robust Bandit Policies Under Uncertain Causal Mechanisms
di: Avery, Katherine, et al.
Pubblicazione: (2025)

Robust and Diverse Multi-Agent Learning via Rational Policy Gradient
di: Lauffer, Niklas, et al.
Pubblicazione: (2025)

Algorithmic Analysis of Dense Associative Memory: Finite-Size Guarantees and Adversarial Robustness
di: Gaikwad, Madhava
Pubblicazione: (2026)

Accelerating Structure-Property Relationship Discovery with Multimodal Machine Learning and Self-Driving Microscopy
di: Gong, Jiawei, et al.
Pubblicazione: (2026)

A Technical Note on the Architectural Effects on Maximum Dependency Lengths of Recurrent Neural Networks
di: Kent, Jonathan S., et al.
Pubblicazione: (2024)

Alternating Gradient Flow Utility: A Unified Metric for Structural Pruning and Dynamic Routing in Deep Networks
di: Qian, Tianhao, et al.
Pubblicazione: (2026)

Robustness of Spatio-temporal Graph Neural Networks for Fault Location in Partially Observable Distribution Grids
di: Karabulut, Burak, et al.
Pubblicazione: (2026)

Hard Samples, Bad Labels: Robust Loss Functions That Know When to Back Off
di: Pellegrino, Nicholas, et al.
Pubblicazione: (2025)

SUN Team's Contribution to ABAW 2024 Competition: Audio-visual Valence-Arousal Estimation and Expression Recognition
di: Dresvyanskiy, Denis, et al.
Pubblicazione: (2024)