Copertina

MBDP: A Model-based Approach to Achieve both Robustness and Sample Efficiency via Double Dropout Planning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhang, Wanpeng, Xiao, Xi, Yao, Yao, Chen, Mingzhe, Luo, Dijun
Natura:	Preprint
Pubblicazione:	2021
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Enhance Sample Efficiency and Robustness of End-to-end Urban Autonomous Driving via Semantic Masked World Model
di: Gao, Zeyu, et al.
Pubblicazione: (2022)

Dropout Regularization in Extended Generalized Linear Models based on Double Exponential Families
di: Schwienhorst, Benedikt Lütke, et al.
Pubblicazione: (2023)

Dropout Drops Double Descent
di: Yang, Tian-Le, et al.
Pubblicazione: (2023)

Enhancing Transformer Training Efficiency with Dynamic Dropout
di: Yan, Hanrui, et al.
Pubblicazione: (2024)

Dropout Robustness and Cognitive Profiling of Transformer Models via Stochastic Inference
di: Caiado, Antônio Junior Alves, et al.
Pubblicazione: (2026)

Improving Sampling Efficiency in RLVR through Adaptive Rollout and Response Reuse
di: Zhang, Yuheng, et al.
Pubblicazione: (2025)

DeepSpeed Data Efficiency: Improving Deep Learning Model Quality and Training Efficiency via Efficient Data Sampling and Routing
di: Li, Conglong, et al.
Pubblicazione: (2022)

Actor-Critics Can Achieve Optimal Sample Efficiency
di: Tan, Kevin, et al.
Pubblicazione: (2025)

Effects of Exponential Gaussian Distribution on (Double Sampling) Randomized Smoothing
di: Shu, Youwei, et al.
Pubblicazione: (2024)

SPABA: A Single-Loop and Probabilistic Stochastic Bilevel Algorithm Achieving Optimal Sample Complexity
di: Chu, Tianshu, et al.
Pubblicazione: (2024)

Tackling Non-Stationarity in Reinforcement Learning via Causal-Origin Representation
di: Zhang, Wanpeng, et al.
Pubblicazione: (2023)

Robust Principal Component Analysis via Discriminant Sample Weight Learning
di: Deng, Yingzhuo, et al.
Pubblicazione: (2024)

Double Descent as a Lens for Sample Efficiency in Autoregressive vs. Discrete Diffusion Models
di: Fraij, Ahmad, et al.
Pubblicazione: (2025)

Lost in Execution: On the Multilingual Robustness of Tool Calling in Large Language Models
di: Luo, Zheng, et al.
Pubblicazione: (2026)

An Adaptive Dropout Approach for High-Dimensional Bayesian Optimization
di: Huang, Jundi, et al.
Pubblicazione: (2025)

Path Planning for Masked Diffusion Model Sampling
di: Peng, Fred Zhangzhi, et al.
Pubblicazione: (2025)

DPad: Efficient Diffusion Language Models with Suffix Dropout
di: Chen, Xinhua, et al.
Pubblicazione: (2025)

Flow-based Distributionally Robust Optimization
di: Xu, Chen, et al.
Pubblicazione: (2023)

Model-based Offline RL via Robust Value-Aware Model Learning with Implicitly Differentiable Adaptive Weighting
di: Qiao, Zhongjian, et al.
Pubblicazione: (2026)

Fit CATE Once: Model-Assisted Randomization Tests Without Sample Splitting
di: Zheng, Fangnan, et al.
Pubblicazione: (2026)

An Efficient NAS-based Approach for Handling Imbalanced Datasets
di: Yao, Zhiwei
Pubblicazione: (2024)

PIONM: A Generalized Approach to Solving Density-Constrained Mean-Field Games Equilibrium under Modified Boundary Conditions
di: Liu, Jinwei, et al.
Pubblicazione: (2025)

LEASE: Offline Preference-based Reinforcement Learning with High Sample Efficiency
di: Liu, Xiao-Yin, et al.
Pubblicazione: (2024)

Enhancing Dropout-based Bayesian Neural Networks with Multi-Exit on FPGA
di: Chen, Hao Mark, et al.
Pubblicazione: (2024)

D3: Diversity, Difficulty, and Dependability-Aware Data Selection for Sample-Efficient LLM Instruction Tuning
di: Zhang, Jia, et al.
Pubblicazione: (2025)

Multi-modal Data based Semi-Supervised Learning for Vehicle Positioning
di: Huan, Ouwen, et al.
Pubblicazione: (2024)

FairDropout: Using Example-Tied Dropout to Enhance Generalization of Minority Groups
di: Nanfack, Geraldin, et al.
Pubblicazione: (2025)

GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning
di: Zhang, Guibin, et al.
Pubblicazione: (2024)

Sample-Mean Anchored Thompson Sampling for Offline-to-Online Learning with Distribution Shift
di: Li, Bochao, et al.
Pubblicazione: (2026)

Training-Free Generative Sampling via Moment-Matched Score Smoothing
di: Yao, Zhenyu, et al.
Pubblicazione: (2026)

Achieving Domain-Independent Certified Robustness via Knowledge Continuity
di: Sun, Alan, et al.
Pubblicazione: (2024)

SPRINT: Robust Model Attribution of Generated Images via Secret Pixel Reconstruction
di: Yao, Kai, et al.
Pubblicazione: (2025)

Understanding Transformer Encoder-Decoder Representations through Bernoulli Dropout
di: Chen, Xuanzhou
Pubblicazione: (2026)

Fairness Without Harm: An Influence-Guided Active Sampling Approach
di: Pang, Jinlong, et al.
Pubblicazione: (2024)

FreCT: Frequency-augmented Convolutional Transformer for Robust Time Series Anomaly Detection
di: Zhang, Wenxin, et al.
Pubblicazione: (2025)

Control in Stochastic Environment with Delays: A Model-based Reinforcement Learning Approach
di: Yao, Zhiyuan, et al.
Pubblicazione: (2024)

Annealing Flow Generative Models Towards Sampling High-Dimensional and Multi-Modal Distributions
di: Wu, Dongze, et al.
Pubblicazione: (2024)

From Rubrics to Reliable Scores: Evidence-Grounded Text Evaluation with LLM Judges
di: Hong, Yihan, et al.
Pubblicazione: (2026)

Model Predictive Task Sampling for Efficient and Robust Adaptation
di: Wang, Qi, et al.
Pubblicazione: (2025)

Achieving the Asymptotically Optimal Sample Complexity of Offline Reinforcement Learning: A DRO-Based Approach
di: Wang, Yue, et al.
Pubblicazione: (2023)