While the performance of cross-lingual TTS based on monolingual corpora ...
In this paper, we propose the global quaternion full orthogonalization
(...
Deep learning (DL) for network models have achieved excellent performanc...
Limited labeled data makes it hard to train models from scratch in medic...
End-to-end training with global optimization have popularized graph neur...
The growing focus on indoor robot navigation utilizing wireless signals ...
With the demand for autonomous control and personalized speech generatio...
This paper addresses the question of how to efficiently learn from disjo...
Misinformation has become a growing issue on online social platforms (OS...
Integrating Global Navigation Satellite Systems (GNSS) in Simultaneous
L...
Exploring the expected quantizing scheme with suitable mixed-precision p...
Intelligent Navigation Systems (INS) are exposed to an increasing
number...
Transparency of information disclosure has always been considered an
ins...
We establish a framework of random inverse problems with real-time
obser...
Invariant Extended Kalman Filter (IEKF) has been successfully applied in...
The increasing connectivity and intricate remote access environment have...
The emergence of harvesting robotics offers a promising solution to the ...
Although fast adversarial training provides an efficient approach for
bu...
Information asymmetry in games enables players with the information adva...
As an effective method to deliver external materials into biological cel...
To fully uncover the great potential of deep neural networks (DNNs), var...
This paper aims to synthesize target speaker's speech with desired speak...
We study Nash equilibria learning of a general-sum stochastic game with ...
Powered by deep representation learning, reinforcement learning (RL) pro...
Meta reinforcement learning (meta RL), as a combination of meta-learning...
We study the decentralized online regularized linear regression algorith...
Effectively integrating multi-scale information is of considerable
signi...
Distribution comparison plays a central role in many machine learning ta...
Stochastic gradient descent (SGD) and its variants are commonly consider...
Trends like Industry 4.0 will pose new challenges for future industrial
...
Measuring the perceptual quality of images automatically is an essential...
In this paper, we present a tightly coupled optimization-based
GPS-Visua...
We introduce M2DGR: a novel large-scale dataset collected by a ground ro...
Single-step adversarial training (AT) has received wide attention as it
...
Source location privacy (SLP) protection is an emerging research topic i...
Quantization has been proven to be a vital method for improving the infe...
In many complex applications, data heterogeneity and homogeneity exist
s...
Recent years have witnessed significant advances in technologies and ser...
Subsampling methods aim to select a subsample as a surrogate for the obs...
The acceleration of CNNs has gained increasing atten-tion since their su...
There is a growing privacy concern due to the popularity of social media...
Although there are massive parameters in deep neural networks, the train...
There is growing concern about image privacy due to the popularity of so...
Cross-chain interaction is among different blockchains. When the number ...
In ophthalmology, early fundus screening is an economic and effective wa...
The use of fundus images for the early screening of eye diseases is of g...
This work provides a novel interpretation of Markov Decision Processes (...
Light Detection and Ranging (LiDAR) based Simultaneous Localization and
...
Network games have been instrumental in understanding strategic behavior...
Emotion embedding space learned from references is a straightforward app...