Cover Image

Semi-supervised learning with max-margin graph cuts

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kveton, Branislav, Valko, Michal, Rahimi, Ali, Huang, Ling
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Online semi-supervised perception: Real-time learning without explicit feedback
by: Kveton, Branislav, et al.
Published: (2026)

Learning from a single labeled face and a stream of unlabeled data
by: Kveton, Branislav, et al.
Published: (2026)

Spectral bandits for smooth graph functions
by: Valko, Michal, et al.
Published: (2026)

Spectral bandits for smooth graph functions with applications in recommender systems
by: Kocák, Tomáš, et al.
Published: (2026)

Adaptive graph-based algorithms for conditional anomaly detection and semi-supervised learning
by: Valko, Michal
Published: (2026)

Evidence-based anomaly detection in clinical domains
by: Hauskrecht, Milos, et al.
Published: (2026)

Large-scale semi-supervised learning with online spectral graph sparsification
by: Calandriello, Daniele, et al.
Published: (2026)

Spectral bandits
by: Kocák, Tomáš, et al.
Published: (2026)

Conditional anomaly detection with soft harmonic functions
by: Valko, Michal, et al.
Published: (2026)

Conditional anomaly detection using soft harmonic functions: An application to clinical alerting
by: Valko, Michal, et al.
Published: (2026)

Bandits on graphs and structures
by: Valko, Michal
Published: (2026)

Cross-Validated Off-Policy Evaluation
by: Cief, Matej, et al.
Published: (2024)

Pessimistic Off-Policy Optimization for Learning to Rank
by: Cief, Matej, et al.
Published: (2022)

Online learning with Erdős-Rényi side-observation graphs
by: Kocák, Tomáš, et al.
Published: (2026)

Revealing graph bandits for maximizing local influence
by: Carpentier, Alexandra, et al.
Published: (2026)

Distance metric learning for conditional anomaly detection
by: Valko, Michal, et al.
Published: (2026)

Improved large-scale graph learning through ridge spectral sparsification
by: Calandriello, Daniele, et al.
Published: (2026)

LLM-as-Judge on a Budget
by: Saha, Aadirupa, et al.
Published: (2026)

Efficient and Interpretable Bandit Algorithms
by: Mukherjee, Subhojyoti, et al.
Published: (2023)

Online learning with noisy side observations
by: Kocák, Tomáš, et al.
Published: (2026)

Maximum Entropy Semi-Supervised Inverse Reinforcement Learning
by: Audiffren, Julien, et al.
Published: (2026)

Adaptive multi-fidelity optimization with fast learning rates
by: Fiegel, Come, et al.
Published: (2026)

Pack only the essentials: Adaptive dictionary learning for kernel ridge regression
by: Calandriello, Daniele, et al.
Published: (2026)

VA-learning as a more efficient alternative to Q-learning
by: Tang, Yunhao, et al.
Published: (2023)

Feature importance analysis for patient management decisions
by: Valko, Michal, et al.
Published: (2026)

Online combinatorial optimization with stochastic decision sets and adversarial losses
by: Neu, Gergely, et al.
Published: (2026)

Extreme bandits
by: Carpentier, Alexandra, et al.
Published: (2026)

Efficient learning by implicit exploration in bandit problems with side observations
by: Kocak, Tomas, et al.
Published: (2026)

Off-Policy Evaluation from Logged Human Feedback
by: Bhargava, Aniruddha, et al.
Published: (2024)

Online Posterior Sampling with a Diffusion Prior
by: Kveton, Branislav, et al.
Published: (2024)

Multi-Objective Alignment of Large Language Models Through Hypervolume Maximization
by: Mukherjee, Subhojyoti, et al.
Published: (2024)

Finite-Time Logarithmic Bayes Regret Upper Bounds
by: Atsidakou, Alexia, et al.
Published: (2023)

Partial Policy Gradients for RL in LLMs
by: Mathur, Puneet, et al.
Published: (2026)

Middle-mile logistics through the lens of goal-conditioned reinforcement learning
by: Eberhard, Onno, et al.
Published: (2026)

ML-Tool-Bench: Tool-Augmented Planning for ML Tasks
by: Chittepu, Yaswanth, et al.
Published: (2025)

Meta-Semi: A Meta-learning Approach for Semi-supervised Learning
by: Wang, Yulin, et al.
Published: (2020)

Semi-supervised learning for linear extremile regression
by: Jiang, Rong, et al.
Published: (2025)

Active multiple matrix completion with adaptive confidence sets
by: Locatelli, Andrea, et al.
Published: (2026)

Bandits attack function optimization
by: Preux, Philippe, et al.
Published: (2026)

Stochastic simultaneous optimistic optimization
by: Valko, Michal, et al.
Published: (2026)