Time-homogeneous top-K ranking using tensor decompositions
From MaRDI portal
Publication:5858998
DOI10.1080/10556788.2019.1584623zbMath1467.62039OpenAlexW2918651208MaRDI QIDQ5858998
Shengyuan Chen, Zi-Jiang Yang, Masoud Ataei, M. Reza Peyghami
Publication date: 15 April 2021
Published in: Optimization Methods and Software (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/10556788.2019.1584623
tensor decompositionrank aggregationrank centralityS\&P500top-\(K\) rankingBradley-Terry-Luce (BTL) modelcardinality-constrained portfolio optimizationnon-stationary spatio-temporal data analysis
Applications of statistics to economics (62P20) Statistical ranking and selection procedures (62F07)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Tensor Decompositions and Applications
- Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation
- Models for paired comparison data: a review with emphasis on dependent data
- Statistical methods for ranking data
- Testing the null hypothesis of stationarity against the alternative of a unit root. How sure are we that economic time series have a unit root?
- Active ranking from pairwise comparisons and when parametric assumptions do not help
- Spectral method and regularized MLE are both optimal for top-\(K\) ranking
- Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 1 Low-Rank Tensor Decompositions
- NON-NULL RANKING MODELS. I
- Simple, Robust and Optimal Ranking from Pairwise Comparisons
- Competitive analysis of the top-K ranking problem
- Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 2 Applications and Future Perspectives
- Approximate Hamming Distance in a Stream
- A Flexible and Efficient Algorithmic Framework for Constrained Matrix and Tensor Factorization
- Tensor Decomposition for Signal Processing and Machine Learning
- Adversarial Top- $K$ Ranking
- Ranking Tournaments
- Analysis of Financial Time Series
- Rank Centrality: Ranking from Pairwise Comparisons
- Aggregating inconsistent information