
Fast blockcoordinate FrankWolfe algorithm for semirelaxed optimal transport
Optimal transport (OT), which provides a distance between two probabilit...
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Manifold optimization for optimal transport
Optimal transport (OT) has recently found widespread interest in machine...
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LCS Graph Kernel Based on Wasserstein Distance in Longest Common Subsequence Metric Space
For graph classification tasks, many methods use a common strategy to ag...
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Wasserstein kmeans with sparse simplex projection
This paper presents a proposal of a faster Wasserstein kmeans algorithm...
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Consistencyaware and Inconsistencyaware Graphbased Multiview Clustering
Multiview data analysis has gained increasing popularity because multi...
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Graph embedding using multilayer adjacent point merging model
For graph classification tasks, many traditional kernel methods focus on...
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Riemannian optimization on the simplex of positive definite matrices
We discuss optimizationrelated ingredients for the Riemannian manifold ...
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Riemannian joint dimensionality reduction and dictionary learning on symmetric positive definite manifold
Dictionary leaning (DL) and dimensionality reduction (DR) are powerful t...
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Adaptive stochastic gradient algorithms on Riemannian manifolds
Adaptive stochastic gradient algorithms in the Euclidean space have attr...
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McTorch, a manifold optimization library for deep learning
In this paper, we introduce McTorch, a manifold optimization library for...
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Lowrank geometric mean metric learning
We propose a lowrank approach to learning a Mahalanobis metric from dat...
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Stochastic variance reduced multiplicative update for nonnegative matrix factorization
Nonnegative matrix factorization (NMF), a dimensionality reduction and f...
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SGDLibrary: A MATLAB library for stochastic gradient descent algorithms
We consider the problem of finding the minimizer of a function f: R^d →R...
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Fast online lowrank tensor subspace tracking by CP decomposition using recursive least squares from incomplete observations
We consider the problem of online subspace tracking of a partially obser...
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Riemannian stochastic quasiNewton algorithm with variance reduction and its convergence analysis
Stochastic variance reduction algorithms have recently become popular fo...
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Riemannian stochastic variance reduced gradient
Stochastic variance reduction algorithms have recently become popular fo...
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Network Volume Anomaly Detection and Identification in Largescale Networks based on Online Timestructured Traffic Tensor Tracking
This paper addresses network anomography, that is, the problem of inferr...
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Lowrank tensor completion: a Riemannian manifold preconditioning approach
We propose a novel Riemannian manifold preconditioning approach for the ...
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Riemannian stochastic variance reduced gradient on Grassmann manifold
Stochastic variance reduction algorithms have recently become popular fo...
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Duration and Interval Hidden Markov Model for Sequential Data Analysis
Analysis of sequential event data has been recognized as one of the esse...
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Hiroyuki Kasai
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