21 Result(s)
within
Chapter
Hongyuan Zha
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Chapter and Conference Paper
A Particle-Evolving Method for Approximating the Optimal Transport Plan
We propose an innovative algorithm that iteratively evolves a particle system to approximate the sample-wised Optimal Transport plan for given continuous probability densities. Our algorithm is proposed via th...
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Chapter and Conference Paper
AutoMix: Mixup Networks for Sample Interpolation via Cooperative Barycenter Learning
This paper proposes new ways of sample mixing by thinking of the process as generation of barycenter in a metric space for data augmentation. First, we present an optimal-transport-based mixup technique to gen...
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Chapter and Conference Paper
Sequential Multi-fusion Network for Multi-channel Video CTR Prediction
In this work, we study video click-through rate (CTR) prediction, crucial for the refinement of video recommendation and the revenue of video advertising. Existing studies have verified the importance of model...
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Chapter and Conference Paper
Parametric Fokker-Planck Equation
We derive the Fokker-Planck equation on the parametric space. It is...
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Chapter and Conference Paper
Personalized Prescription for Comorbidity
Personalized medicine (PM) aiming at tailoring medical treatment to individual patient is critical in guiding precision prescription. An important challenge for PM is comorbidity due to the complex interrelati...
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Chapter and Conference Paper
Parallel Randomized Block Coordinate Descent for Neural Probabilistic Language Model with High-Dimensional Output Targets
Training a large probabilistic neural network language model, with typical high-dimensional output is excessively time-consuming, which is one of the main reasons that more simplified models such as n-gram is oft...
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Chapter and Conference Paper
Graduated Consistency-Regularized Optimization for Multi-graph Matching
Graph matching has a wide spectrum of computer vision applications such as finding feature point correspondences across images. The problem of graph matching is generally NP-hard, so most existing work pursues...
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Chapter and Conference Paper
Learning the Hotness of Information Diffusions with Multi-dimensional Hawkes Processes
Modeling the information cascading process over networks has attracted a lot of research attention due to its wide applications in viral marketing, epidemiology and recommendation systems. In particular, infor...
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Chapter and Conference Paper
On the Convergence of Graph Matching: Graduated Assignment Revisited
We focus on the problem of graph matching that is fundamental in computer vision and machine learning. Many state-of-the-arts frequently formulate it as integer quadratic programming, which incorporates both u...
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Chapter
Dimensionality Reduction and Topic Modeling: From Latent Semantic Indexing to Latent Dirichlet Allocation and Beyond
The bag-of-words representation commonly used in text analysis can be analyzed very efficiently and retains a great deal of useful information, but it is also troublesome because the same thought can be expres...
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Chapter and Conference Paper
Metric Learning for Regression Problems and Human Age Estimation
The estimation of human age from face images has great potential in real-world applications. However, how to discover the intrinsic aging trend is still a challenging problem. In this work, we proposed a gener...
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Chapter and Conference Paper
Variational Graph Embedding for Globally and Locally Consistent Feature Extraction
Existing feature extraction methods explore either global statistical or local geometric information underlying the data. In this paper, we propose a general framework to learn features that account for both t...
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Chapter and Conference Paper
Simple and Effective Variational Optimization of Surface and Volume Triangulations
Optimizing surface and volume triangulations is critical for advanced numerical simulations. We present a simple and effective variational approach for optimizing triangulated surface and volume meshes. Our me...
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Chapter and Conference Paper
Optimizing Surface Triangulation Via Near Isometry with Reference Meshes
Optimization of the mesh quality of surface triangulation is critical for advanced numerical simulations and is challenging under the constraints of error minimization and density control. We derive a new meth...
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Chapter and Conference Paper
IKNN: Informative K-Nearest Neighbor Pattern Classification
The K-nearest neighbor (KNN) decision rule has been a ubiquitous classification tool with good scalability. Past experience has shown that the optimal choice of K depends upon the data, making it laborious to tun...
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Chapter and Conference Paper
Spectral Clustering for Robust Motion Segmentation
In this paper, we propose a robust motion segmentation method using the techniques of matrix factorization and subspace separation. We first show that the shape interaction matrix can be derived using QR decompos...
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Chapter and Conference Paper
Extracting Shared Topics of Multiple Documents
In this paper, we present a weighted graph based method to simultaneously compare the textual content of two or more documents and extract the shared (sub)topics of them, if available. A set of documents are m...
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Chapter and Conference Paper
Nonlinear Dimension Reduction via Local Tangent Space Alignment
In this paper we present a new algorithm for manifold learning and nonlinear dimension reduction. Based on a set of unorganized data points sampled with noise from the manifold, we represent the local geometry...
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Chapter and Conference Paper
Unsupervised Learning: Self-aggregation in Scaled Principal Component Space*
We demonstrate that data clustering amounts to a dynamic process of self-aggregation in which data objects move towards each other to form clusters, revealing the inherent pattern of similarity. Selfaggregation i...
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Chapter and Conference Paper
Large-scale SVD and subspace-based methods for information retrieval
A theoretical foundation for latent semantic indexing (LSI) is proposed by adapting a model first used in array signal processing to the context of information retrieval using the concept of subspaces. It is show...
