Knowledge distillation (KD) is an effective technique to transfer knowle...
It is well observed that in deep learning and computer vision literature...
This paper presents GraphFederator, a novel approach to construct joint
...
Deep supervised learning has achieved great success in the last decade.
...
Single-objective black box optimization (also known as zeroth-order
opti...
While vehicular sensor networks (VSNs) have earned the stature of a mobi...
In this paper, we investigate learning-based MIMO-OFDM symbol detection
...
In this paper, we study the beamforming design problem in frequency-divi...
We consider the problem of covert communication over continuous-time add...
Reconfigurable intelligent surface (RIS) is envisioned to be an essentia...
We consider the problem of recovering communities of users and communiti...
We advocate the use of differential visual shape metrics to train deep n...
The classical low rank approximation problem is to find a rank k matrix
...
Zeroth-order optimization is the process of minimizing an objective f(x)...
Point clouds-based Networks have achieved great attention in 3D object
c...
Modern Blockchains support the execution of user programs, called smart
...
In this paper, we study joint antenna activity detection, channel estima...
A crucial assumption in most statistical learning theory is that samples...
In recent years, search story, a combined display with other organic
cha...
Mobile Network Operators (MNOs) are in process of overlaying their
conve...
Beamforming in multiple input multiple output (MIMO) systems is one of t...
This paper overviews the state of the art, research challenges, and futu...
In cinema, large camera lenses create beautiful shallow depth of field (...
The 5th edition of the International Conference on Cloud and Robotics (I...
This paper investigates the capability of millimeter-wave (mmWave) chann...
We consider the problem of stealth communication over a multipath networ...
A key problem in deep multi-attribute learning is to effectively discove...
In this paper, we present BigDL, a distributed deep learning framework f...
Load balancing is an effective approach to address the spatial-temporal
...
Due to their growing popularity and computational cost, deep neural netw...
Zero-Shot Learning (ZSL) is typically achieved by resorting to a class
s...
Clickbait (headlines) make use of misleading titles that hide critical
i...
As an environment-friendly substitute for conventional fuel-powered vehi...