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Found 7 papers, 1 papers with code
Bandits with Abstention under Expert Advice
We study the classic problem of prediction with expert advice under bandit feedback.
Query-Efficient Correlation Clustering with Noisy Oracle
We study a general clustering setting in which we have $n$ elements to be clustered, and we aim to perform as few queries as possible to an oracle that returns a noisy sample of the similarity between two elements.
A Survey on the Densest Subgraph Problem and its Variants
This survey provides a deep overview of the fundamental results and an exhaustive coverage of the many variants proposed in the literature, with a special attention on the most recent results.
Online Dense Subgraph Discovery via Blurred-Graph Feedback
Dense subgraph discovery aims to find a dense component in edge-weighted graphs.
Hypergraph Clustering Based on PageRank
For both algorithms, we discuss theoretical guarantees on the conductance of the output vertex set.
Graph Mining Meets Crowdsourcing: Extracting Experts for Answer Aggregation
Aggregating responses from crowd workers is a fundamental task in the process of crowdsourcing.
Polynomial-time Algorithms for Multiple-arm Identification with Full-bandit Feedback
Based on our approximation algorithm, we propose novel bandit algorithms for the top-k selection problem, and prove that our algorithms run in polynomial time.
