:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhang, Qingyang, Feng, Qiuxuan, Zhou, Joey Tianyi, Bian, Yatao, Hu, Qinghua, Zhang, Changqing
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2410.11576
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

COME: Test-time adaption by Conservatively Minimizing Entropy
by: Zhang, Qingyang, et al.
Published: (2024)

Right Question is Already Half the Answer: Fully Unsupervised LLM Reasoning Incentivization
by: Zhang, Qingyang, et al.
Published: (2025)

Selective Learning: Towards Robust Calibration with Dynamic Regularization
by: Han, Zongbo, et al.
Published: (2024)

Out-Of-Distribution Detection with Diversification (Provably)
by: Yao, Haiyun, et al.
Published: (2024)

Semantic Energy: Detecting LLM Hallucination Beyond Entropy
by: Ma, Huan, et al.
Published: (2025)

ID-like Prompt Learning for Few-Shot Out-of-Distribution Detection
by: Bai, Yichen, et al.
Published: (2023)

FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection
by: Liao, Xinting, et al.
Published: (2024)

Best-of-Both-Worlds Algorithms for Linear Contextual Bandits
by: Kuroki, Yuko, et al.
Published: (2023)

Best-of-Both-Worlds Policy Optimization for CMDPs with Bandit Feedback
by: Stradi, Francesco Emanuele, et al.
Published: (2024)

Best-of-Both Worlds for linear contextual bandits with paid observations
by: Boyer, Nathan, et al.
Published: (2025)

Best-of-Both-Worlds for Heavy-Tailed Markov Decision Processes
by: Chen, Yu, et al.
Published: (2026)

Best of Both Worlds: Regret Minimization versus Minimax Play
by: Müller, Adrian, et al.
Published: (2025)

Improved Best-of-Both-Worlds Regret for Bandits with Delayed Feedback
by: Schlisselberg, Ofir, et al.
Published: (2025)

Follow-the-Perturbed-Leader Approaches Best-of-Both-Worlds for the m-Set Semi-Bandit Problems
by: Zhan, Jingxin, et al.
Published: (2025)

TEMPO: Scaling Test-time Training for Large Reasoning Models
by: Zhang, Qingyang, et al.
Published: (2026)

Federated Adapter on Foundation Models: An Out-Of-Distribution Approach
by: Yang, Yiyuan, et al.
Published: (2025)

Follow-the-Perturbed-Leader for Decoupled Bandits: Best-of-Both-Worlds and Practicality
by: Kim, Chaiwon, et al.
Published: (2025)

Efficient Best-of-Both-Worlds Algorithms for Contextual Combinatorial Semi-Bandits
by: Li, Mengmeng, et al.
Published: (2025)

Best of Both Worlds: Advantages of Hybrid Graph Sequence Models
by: Behrouz, Ali, et al.
Published: (2024)

Graph Unitary Message Passing
by: Qiu, Haiquan, et al.
Published: (2024)

LC-Tsallis-INF: Generalized Best-of-Both-Worlds Linear Contextual Bandits
by: Kato, Masahiro, et al.
Published: (2024)

A Best-of-Both-Worlds Algorithm for Constrained MDPs with Long-Term Constraints
by: Germano, Jacopo, et al.
Published: (2023)

Multimodal Fusion on Low-quality Data: A Comprehensive Survey
by: Zhang, Qingyang, et al.
Published: (2024)

Best of Both Worlds: Practical and Theoretically Optimal Submodular Maximization in Parallel
by: Chen, Yixin, et al.
Published: (2021)

uniINF: Best-of-Both-Worlds Algorithm for Parameter-Free Heavy-Tailed MABs
by: Chen, Yu, et al.
Published: (2024)

Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds
by: Ito, Shinji, et al.
Published: (2024)

Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization
by: Bhuyan, Neelkamal, et al.
Published: (2023)

Data-independent Module-aware Pruning for Hierarchical Vision Transformers
by: He, Yang, et al.
Published: (2024)

A Best-of-Both-Worlds Proof for Tsallis-INF without Fenchel Conjugates
by: Lee, Wei-Cheng, et al.
Published: (2025)

Learning to Learn with Contrastive Meta-Objective
by: Wu, Shiguang, et al.
Published: (2024)

How Interpretable Are Interpretable Graph Neural Networks?
by: Chen, Yongqiang, et al.
Published: (2024)

Learning to Bid in FCR Markets: A Best-of-Both-Worlds Approach
by: Potfer, Marius, et al.
Published: (2026)

Predictive Dynamic Fusion
by: Cao, Bing, et al.
Published: (2024)

The Best of Both Worlds: Integrating Language Models and Diffusion Models for Video Generation
by: Yin, Aoxiong, et al.
Published: (2025)

Both Topology and Text Matter: Revisiting LLM-guided Out-of-Distribution Detection on Text-attributed Graphs
by: Zhu, Yinlin, et al.
Published: (2026)

Diversity-Driven Synthesis: Enhancing Dataset Distillation through Directed Weight Adjustment
by: Du, Jiawei, et al.
Published: (2024)

Follow-the-Perturbed-Leader with Fréchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds
by: Lee, Jongyeong, et al.
Published: (2024)

A Further Efficient Algorithm with Best-of-Both-Worlds Guarantees for $m$-Set Semi-Bandit Problem
by: Chen, Botao, et al.
Published: (2026)

HIGHT: Hierarchical Graph Tokenization for Molecule-Language Alignment
by: Chen, Yongqiang, et al.
Published: (2024)

On the Learnability of Out-of-distribution Detection
by: Fang, Zhen, et al.
Published: (2024)