[HTML][HTML] Machine learning for mental health in social media: bibliometric study
Background: Social media platforms provide an easily accessible and time-saving
communication approach for individuals with mental disorders compared to face-to-face …
communication approach for individuals with mental disorders compared to face-to-face …
Recent advances of large-scale linear classification
Linear classification is a useful tool in machine learning and data mining. For some data in a
rich dimensional space, the performance (ie, testing accuracy) of linear classifiers has …
rich dimensional space, the performance (ie, testing accuracy) of linear classifiers has …
Fast and faster convergence of sgd for over-parameterized models and an accelerated perceptron
Modern machine learning focuses on highly expressive models that are able to fit or
interpolate the data completely, resulting in zero training loss. For such models, we show …
interpolate the data completely, resulting in zero training loss. For such models, we show …
Minimizing finite sums with the stochastic average gradient
We analyze the stochastic average gradient (SAG) method for optimizing the sum of a finite
number of smooth convex functions. Like stochastic gradient (SG) methods, the SAG …
number of smooth convex functions. Like stochastic gradient (SG) methods, the SAG …
A decentralized proximal-gradient method with network independent step-sizes and separated convergence rates
This paper proposes a novel proximal-gradient algorithm for a decentralized optimization
problem with a composite objective containing smooth and nonsmooth terms. Specifically …
problem with a composite objective containing smooth and nonsmooth terms. Specifically …
Multi-agent distributed optimization via inexact consensus ADMM
Multi-agent distributed consensus optimization problems arise in many signal processing
applications. Recently, the alternating direction method of multipliers (ADMM) has been …
applications. Recently, the alternating direction method of multipliers (ADMM) has been …
Face liveness detection from a single image with sparse low rank bilinear discriminative model
Spoofing with photograph or video is one of the most common manner to circumvent a face
recognition system. In this paper, we present a real-time and non-intrusive method to …
recognition system. In this paper, we present a real-time and non-intrusive method to …
Hyperspectral image classification based on structured sparse logistic regression and three-dimensional wavelet texture features
Hyperspectral remote sensing imagery contains rich information on spectral and spatial
distributions of distinct surface materials. Owing to its numerous and continuous spectral …
distributions of distinct surface materials. Owing to its numerous and continuous spectral …
Asynchronous distributed ADMM for large-scale optimization—Part I: Algorithm and convergence analysis
Aiming at solving large-scale optimization problems, this paper studies distributed
optimization methods based on the alternating direction method of multipliers (ADMM). By …
optimization methods based on the alternating direction method of multipliers (ADMM). By …
A surrogate-assisted multi-objective particle swarm optimization of expensive constrained combinatorial optimization problems
Q Gu, Q Wang, X Li, X Li - Knowledge-Based Systems, 2021 - Elsevier
Surrogate-assisted evolutionary algorithms have been commonly used in extremely
expensive optimization problems. However, many existing algorithms are only significantly …
expensive optimization problems. However, many existing algorithms are only significantly …