:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Mandal, Saptarshi, Murthy, Yashaswini, Srikant, R.
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning I.2.6
Accesso online:	https://arxiv.org/abs/2510.01721
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

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

Universal Approximation of Continuous Functionals on Compact Subsets via Linear Measurements and Scalar Nonlinearities
di: Krylov, Andrey, et al.
Pubblicazione: (2026)

Learning Can Converge Stably to the Wrong Belief under Latent Reliability
di: Zhang, Zhipeng, et al.
Pubblicazione: (2026)

Hierarchical Universal Value Function Approximators
di: Arora, Rushiv
Pubblicazione: (2024)

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

2Mamba2Furious: Linear in Complexity, Competitive in Accuracy
di: Mongaras, Gabriel, et al.
Pubblicazione: (2026)

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

Symbol-Temporal Consistency Self-supervised Learning for Robust Time Series Classification
di: Garcia, Kevin, et al.
Pubblicazione: (2025)

Composing Linear Layers from Irreducibles
di: Pence, Travis, et al.
Pubblicazione: (2025)

Distributional Reinforcement Learning for Condition-Based Maintenance of Multi-Pump Equipment
di: Yasuno, Takato
Pubblicazione: (2026)

Understanding Boolean Function Learnability on Deep Neural Networks: PAC Learning Meets Neurosymbolic Models
di: Nicolau, Marcio, et al.
Pubblicazione: (2020)

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

ES-C51: Expected Sarsa Based C51 Distributional Reinforcement Learning Algorithm
di: Tandon, Rijul, et al.
Pubblicazione: (2025)

How Does the Pretraining Distribution Shape In-Context Learning? Task Selection, Generalization, and Robustness
di: Azizian, Waïss, et al.
Pubblicazione: (2025)

SQARL: A Size-Agnostic Reinforcement Learning approach for Circuit Allocation in Distributed Quantum Architectures
di: Carballo, Víctor, et al.
Pubblicazione: (2026)

Extrinsicaly Rewarded Soft Q Imitation Learning with Discriminator
di: Furuyama, Ryoma, et al.
Pubblicazione: (2024)

New Paradigm of Adversarial Training: Releasing Accuracy-Robustness Trade-Off via Dummy Class
di: Wang, Yanyun, et al.
Pubblicazione: (2024)

RobustModelMaker: Coupling Bootstrap Stability Selection with Leakage-Safe Nested Cross-Validation for Scientific Machine Learning
di: Barnard, Amanda S
Pubblicazione: (2026)

Learning Transferable Predictability Representations
di: Goswami, Diyali, et al.
Pubblicazione: (2026)

Deep Memory Search: A Metaheuristic Approach for Optimizing Heuristic Search
di: Hedar, Abdel-Rahman, et al.
Pubblicazione: (2024)

Beyond Monotonicity: Revisiting Factorization Principles in Multi-Agent Q-Learning
di: Hu, Tianmeng, et al.
Pubblicazione: (2025)

How to Boost Any Loss Function
di: Nock, Richard, et al.
Pubblicazione: (2024)

Strengthening the Internal Adversarial Robustness in Lifted Neural Networks
di: Zach, Christopher
Pubblicazione: (2025)

Pruning Spurious Subgraphs for Graph Out-of-Distribution Generalization
di: Yao, Tianjun, et al.
Pubblicazione: (2025)

Expressivity of Graph Neural Networks Through the Lens of Adversarial Robustness
di: Campi, Francesco, et al.
Pubblicazione: (2023)

BOND: License to Train with Black-Box Functions
di: Clark, Andrew, et al.
Pubblicazione: (2025)

Enhancing Classifier Evaluation: A Fairer Benchmarking Strategy Based on Ability and Robustness
di: Cardoso, Lucas, et al.
Pubblicazione: (2025)

RobustBlack: Challenging Black-Box Adversarial Attacks on State-of-the-Art Defenses
di: Djilani, Mohamed, et al.
Pubblicazione: (2024)

ZClassifier: Temperature Tuning and Manifold Approximation via KL Divergence on Logit Space
di: Yong, Shim Soon
Pubblicazione: (2025)

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

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

Perfecting Aircraft Maneuvers with Reinforcement Learning
di: Cilan, Atahan, et al.
Pubblicazione: (2026)

Why LoRA Resists Label Noise: A Theoretical Framework for Noise-Robust Parameter-Efficient Fine-Tuning
di: Steele, Brady
Pubblicazione: (2026)

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

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

KL-Regularised Q-Learning: A Token-level Action-Value perspective on Online RLHF
di: Brown, Jason R, et al.
Pubblicazione: (2025)

MEReQ: Max-Ent Residual-Q Inverse RL for Sample-Efficient Alignment from Intervention
di: Chen, Yuxin, et al.
Pubblicazione: (2024)

Symmetric Equilibrium Learning of VAEs
di: Flach, Boris, et al.
Pubblicazione: (2023)

A Comparative Analysis of Reinforcement Learning and Conventional Deep Learning Approaches for Bearing Fault Diagnosis
di: Çakır, Efe, et al.
Pubblicazione: (2025)

Path-Coupled Bellman Flows for Distributional Reinforcement Learning
di: Xu, Boyang, et al.
Pubblicazione: (2026)