Copertina

Manipulating Predictions over Discrete Inputs in Machine Teaching

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wu, Xiaodong, Han, Yufei, Dahrouj, Hayssam, Ni, Jianbing, Liang, Zhenwen, Zhang, Xiangliang
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence I.2.6
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

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

Relevance-driven Input Dropout: an Explanation-guided Regularization Technique
di: Gururaj, Shreyas, et al.
Pubblicazione: (2025)

Manipulating 3D Molecules in a Fixed-Dimensional E(3)-Equivariant Latent Space
di: Chen, Zitao, et al.
Pubblicazione: (2025)

Machine Learning vs Deep Learning: The Generalization Problem
di: Bay, Yong Yi, et al.
Pubblicazione: (2024)

Fusion-Based Neural Generalization for Predicting Temperature Fields in Industrial PET Preform Heating
di: Alsheikh, Ahmad, et al.
Pubblicazione: (2025)

OFMU: Optimization-Driven Framework for Machine Unlearning
di: Asif, Sadia, et al.
Pubblicazione: (2025)

A Practical Approach to using Supervised Machine Learning Models to Classify Aviation Safety Occurrences
di: Siow, Bryan Y.
Pubblicazione: (2025)

Behavior Learning (BL): Learning Hierarchical Optimization Structures from Data
di: Ma, Zhenyao, et al.
Pubblicazione: (2026)

Black Box Model Explanations and the Human Interpretability Expectations -- An Analysis in the Context of Homicide Prediction
di: Ribeiro, José, et al.
Pubblicazione: (2022)

Simulation-Driven Railway Delay Prediction: An Imitation Learning Approach
di: Elliker, Clément, et al.
Pubblicazione: (2025)

CircuitProbe: Predicting Reasoning Circuits in Transformers via Stability Zone Detection
di: Panuganti, Rajkiran
Pubblicazione: (2026)

Democratic Preference Alignment via Sortition-Weighted RLHF
di: Sana, Suvadip, et al.
Pubblicazione: (2026)

Structured Prompt Optimization Meets Reinforcement Learning for Global and Local Interpretability over Complex Text
di: Zhou, Tianyang, et al.
Pubblicazione: (2026)

Towards Independence Criterion in Machine Unlearning of Features and Labels
di: Han, Ling, et al.
Pubblicazione: (2024)

SourceSplice: Source Selection for Machine Learning Tasks
di: Singh, Ambarish, et al.
Pubblicazione: (2025)

Explainable Machine Learning System for Predicting Chronic Kidney Disease in High-Risk Cardiovascular Patients
di: Nguycharoen, Nantika
Pubblicazione: (2024)

EXCODER: EXplainable Classification Of DiscretE time series Representations
di: Hahn, Yannik, et al.
Pubblicazione: (2026)

Scaling Value Iteration Networks to 5000 Layers for Extreme Long-Term Planning
di: Wang, Yuhui, et al.
Pubblicazione: (2024)

Entropy-Based Measurement of Value Drift and Alignment Work in Large Language Models
di: Fadli, Samih
Pubblicazione: (2025)

Towards a Robust Soft Baby Robot With Rich Interaction Ability for Advanced Machine Learning Algorithms
di: Alhakami, Mohannad, et al.
Pubblicazione: (2024)

Comprehensive Metapath-based Heterogeneous Graph Transformer for Gene-Disease Association Prediction
di: Cui, Wentao, et al.
Pubblicazione: (2025)

Evaluating SAP RPT-1 for Enterprise Business Process Prediction: In-Context Learning vs. Traditional Machine Learning on Structured SAP Data
di: Lal, Amit
Pubblicazione: (2026)

Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search
di: Zawalski, Michał, et al.
Pubblicazione: (2022)

Out of Distribution Detection for Efficient Continual Learning in Quality Prediction for Arc Welding
di: Hahn, Yannik, et al.
Pubblicazione: (2025)

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

FastForward Pruning: Efficient LLM Pruning via Single-Step Reinforcement Learning
di: Yuan, Xin, et al.
Pubblicazione: (2025)

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

Simplifying Hyperparameter Tuning in Online Machine Learning -- The spotRiverGUI
di: Bartz-Beielstein, Thomas
Pubblicazione: (2024)

Tailoring Machine Learning for Process Mining
di: Ceravolo, Paolo, et al.
Pubblicazione: (2023)

TACO: Tackling Over-correction in Federated Learning with Tailored Adaptive Correction
di: Liu, Weijie, et al.
Pubblicazione: (2025)

DataRater: Meta-Learned Dataset Curation
di: Calian, Dan A., et al.
Pubblicazione: (2025)

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

Axiomatic Characterisations of Sample-based Explainers
di: Amgoud, Leila, et al.
Pubblicazione: (2024)

ParalESN: Enabling parallel information processing in Reservoir Computing
di: Pinna, Matteo, et al.
Pubblicazione: (2026)

The Lattice Geometry of Neural Network Quantization -- A Short Equivalence Proof of GPTQ and Babai's Algorithm
di: Birnick, Johann
Pubblicazione: (2025)

Evaluation of post-hoc interpretability methods in time-series classification
di: Turbé, Hugues, et al.
Pubblicazione: (2022)

Resilience to the Flowing Unknown: an Open Set Recognition Framework for Data Streams
di: Barcina-Blanco, Marcos, et al.
Pubblicazione: (2024)

Understanding Goal Generalisation in Sequential Reinforcement Learning
di: Brown, Jason Ross, et al.
Pubblicazione: (2026)

Unlearning's Blind Spots: Over-Unlearning and Prototypical Relearning Attack
di: Ha, SeungBum, et al.
Pubblicazione: (2025)

Residual Reservoir Memory Networks
di: Pinna, Matteo, et al.
Pubblicazione: (2025)