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Found 8 papers, 2 papers with code
Multilayer Correlation Clustering
In this paper, we establish Multilayer Correlation Clustering, a novel generalization of Correlation Clustering (Bansal et al., FOCS '02) to the multilayer setting.
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 weighted similarity between two elements.
A Survey on the Densest Subgraph Problem and Its Variants
The Densest Subgraph Problem requires to find, in a given graph, a subset of vertices whose induced subgraph maximizes a measure of density.
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.
