Search Results for author: Petko Bogdanov

Found 8 papers, 0 papers with code

Multi-Dictionary Tensor Decomposition

no code implementations18 Sep 2023 Maxwell McNeil, Petko Bogdanov

In some cases side information is available about the tensor modes.

Imputation Philosophy +1

Unsupervised Instance and Subnetwork Selection for Network Data

no code implementations24 Dec 2022 Lin Zhang, Nicholas Moskwa, Melinda Larsen, Petko Bogdanov

We address these challenges within an unsupervised framework for joint subnetwork and instance selection in network data, called UISS, via a convex self-representation objective.

Temporal Scale Estimation for Oversampled Network Cascades: Theory, Algorithms, and Experiment

no code implementations22 Sep 2021 Abram Magner, Carolyn Kaminski, Petko Bogdanov

We highlight one such phenomenon -- temporal distortion -- caused by a misalignment between the rate at which observations of a cascade process are made and the rate at which the process itself operates, and argue that failure to correct for it results in degradation of performance on downstream statistical tasks.

Epidemiology Marketing

Temporal Graph Signal Decomposition

no code implementations25 Jun 2021 Maxwell McNeil, Lin Zhang, Petko Bogdanov

We propose a general, dictionary-based framework for temporal graph signal decomposition (TGSD).

Imputation Time Series Analysis

LinksIQ: Robust and Efficient Modulation Recognition with Imperfect Spectrum Scans

no code implementations7 May 2020 Wei Xiong, Karyn Doke, Petko Bogdanov, Mariya Zheleva

While critical for the practical progress of spectrum sharing, modulation recognition has so far been investigated under unrealistic assumptions: (i) a transmitter's bandwidth must be scanned alone and in full, (ii) prior knowledge of the technology must be available and (iii) a transmitter must be trustworthy.

DSL: Discriminative Subgraph Learning via Sparse Self-Representation

no code implementations24 Mar 2019 Lin Zhang, Petko Bogdanov

In this work we propose an optimization framework for discriminative subgraph learning (DSL) which simultaneously enforces (i) sparsity, (ii) connectivity and (iii) high discriminative power of the resulting subgraphs of features.

feature selection

A Distance Measure for the Analysis of Polar Opinion Dynamics in Social Networks

no code implementations17 Oct 2015 Victor Amelkin, Ambuj Singh, Petko Bogdanov

In this work, we introduce Social Network Distance (SND) - a distance measure that quantifies the "cost" of evolution of one snapshot of a social network into another snapshot under various models of polar opinion propagation.

Event Detection

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