
Augmented Skeleton Based Contrastive Action Learning with Momentum LSTM for Unsupervised Action Recognition
Action recognition via 3D skeleton data is an emerging important topic i...
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Policy Learning of MDPs with Mixed Continuous/Discrete Variables: A Case Study on ModelFree Control of Markovian Jump Systems
Markovian jump linear systems (MJLS) are an important class of dynamical...
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Emotion Recognition From Gait Analyses: Current Research and Future Directions
Human gait refers to a daily motion that represents not only mobility, b...
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Deterministic IntraVehicle Communications: Timing and Synchronization
As we power through to the future, invehicle communications reliance on...
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A study of restingstate EEG biomarkers for depression recognition
Background: Depression has become a major health burden worldwide, and e...
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A Novel Decision Tree for Depression Recognition in Speech
Depression is a common mental disorder worldwide which causes a range of...
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MODMA dataset: a Multimodal Open Dataset for Mentaldisorder Analysis
According to the World Health Organization, the number of mental disorde...
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MODMA dataset: a Multimodel Open Dataset for Mentaldisorder Analysis
According to the World Health Organization, the number of mental disorde...
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Convergence Guarantees of Policy Optimization Methods for Markovian Jump Linear Systems
Recently, policy optimization for control purposes has received renewed ...
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An adaptive finite element DtN method for the threedimensional acoustic scattering problem
This paper is concerned with a numerical solution of the acoustic scatte...
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Policy Optimization for H_2 Linear Control with H_∞ Robustness Guarantee: Implicit Regularization and Global Convergence
Policy optimization (PO) is a key ingredient for reinforcement learning ...
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Supervised feature selection with orthogonal regression and feature weighting
Effective features can improve the performance of a model, which can thu...
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Characterizing the Exact Behaviors of Temporal Difference Learning Algorithms Using Markov Jump Linear System Theory
In this paper, we provide a unified analysis of temporal difference lear...
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Identifying Illicit Accounts in Large Scale Epayment Networks  A Graph Representation Learning Approach
Rapid and massive adoption of mobile/ online payment services has brough...
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Local Probabilistic Model for Bayesian Classification: a Generalized Local Classification Model
In Bayesian classification, it is important to establish a probabilistic...
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Local Distribution in Neighborhood for Classification
The knearestneighbor method performs classification tasks for a query ...
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Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs
Techniques for reducing the variance of gradient estimates used in stoch...
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Analysis of Approximate Stochastic Gradient Using Quadratic Constraints and Sequential Semidefinite Programs
We present convergence rate analysis for the approximate stochastic grad...
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Learning Intrinsic Sparse Structures within Long ShortTerm Memory
Model compression is significant for the wide adoption of Recurrent Neur...
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A Unified Analysis of Stochastic Optimization Methods Using Jump System Theory and Quadratic Constraints
We develop a simple routine unifying the analysis of several important r...
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A Learning Based Optimal Human Robot Collaboration with Linear Temporal Logic Constraints
This paper considers an optimal task allocation problem for human robot ...
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An IntervalBased Bayesian Generative Model for Human Complex Activity Recognition
Complex activity recognition is challenging due to the inherent uncertai...
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Bin Hu
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