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Found 11 papers, 0 papers with code
Community Detection in the Multi-View Stochastic Block Model
This paper considers the problem of community detection on multiple potentially correlated graphs from an information-theoretical perspective.
Matrix Completion with Hypergraphs:Sharp Thresholds and Efficient Algorithms
Theoretical analyses show that our algorithm succeeds with high probability as long as the sample probability exceeds the aforementioned threshold, and this theoretical result is further validated by synthetic experiments.
MVPatch: More Vivid Patch for Adversarial Camouflaged Attacks on Object Detectors in the Physical World
Our method employs a model-perception-based approach that reduces the object confidence scores of several object detectors to boost the transferability of adversarial patches.
Mutual Information Learned Regressor: an Information-theoretic Viewpoint of Training Regression Systems
We first argue that the MSE minimization approach is equivalent to a conditional entropy learning problem, and then propose a mutual information learning formulation for solving regression problems by using a reparameterization technique.
Mutual Information Learned Classifiers: an Information-theoretic Viewpoint of Training Deep Learning Classification Systems
Deep learning systems have been reported to acheive state-of-the-art performances in many applications, and one of the keys for achieving this is the existence of well trained classifiers on benchmark datasets which can be used as backbone feature extractors in downstream tasks.
Mutual Information Learned Classifiers: an Information-theoretic Viewpoint of Training Deep Learning Classification Systems
Deep learning systems have been reported to achieve state-of-the-art performances in many applications, and a key is the existence of well trained classifiers on benchmark datasets.
Exact Recovery in the General Hypergraph Stochastic Block Model
This paper investigates fundamental limits of exact recovery in the general d-uniform hypergraph stochastic block model (d-HSBM), wherein n nodes are partitioned into k disjoint communities with relative sizes (p1,..., pk).
MC2G: An Efficient Algorithm for Matrix Completion with Social and Item Similarity Graphs
In this paper, we design and analyze MC2G (Matrix Completion with 2 Graphs), an algorithm that performs matrix completion in the presence of social and item similarity graphs.
Optimal Change-Point Detection with Training Sequences in the Large and Moderate Deviations Regimes
This paper investigates a novel offline change-point detection problem from an information-theoretic perspective.
Community Detection and Matrix Completion with Social and Item Similarity Graphs
We consider the problem of recovering a binary rating matrix as well as clusters of users and items based on a partially observed matrix together with side-information in the form of social and item similarity graphs.
Comparison among dimensionality reduction techniques based on Random Projection for cancer classification
FS followed by RP outperforms other combination methods in classification accuracy on most of the datasets.
