Differential privacy (DP) is the state-of-the-art framework for guarante...
As impact of COVID-19 pandemic winds down, both individuals and society
...
Existing Referring Image Segmentation (RIS) methods typically require
ex...
Drones have been widely used in many areas of our daily lives. It reliev...
Developers introduce code clones to improve programming productivity. Ma...
It is commonplace to use data containing personal information to build
p...
Variational inference is an increasingly popular method in statistics an...
We examine privacy-preserving inferences of group mean differences in
ze...
To address the challenges of long-tailed classification, researchers hav...
Tensor data are multi-dimension arrays. Low-rank decomposition-based
reg...
Electronic health records (EHR) often contain sensitive medical informat...
There is growing interest in software migration as the development of
so...
The construction of machine learning models involves many bi-level
multi...
Model bias triggered by long-tailed data has been widely studied. Howeve...
Natural language processing for programming, which aims to use NLP techn...
Change detection (CD) of remote sensing images is to detect the change r...
Deep learning based semantic segmentation is one of the popular methods ...
In this paper, a symmetrized two-scale finite element method is proposed...
The current work on reinforcement learning (RL) from demonstrations ofte...
Accelerated discovery with machine learning (ML) has begun to provide th...
Code completion tools are frequently used by software developers to
acce...
We propose the AdaPtive Noise Augmentation (PANDA) procedure to regulari...
Low-rankness plays an important role in traditional machine learning, bu...
The inherent slow imaging speed of Magnetic Resonance Image (MRI) has sp...
Dynamic attention mechanism and global modeling ability make Transformer...
Approximating probability distributions can be a challenging task,
parti...
In programming, the names for the program entities, especially for the
m...
Training speaker-discriminative and robust speaker verification systems
...
The COVID-19 pandemic has affected societies and human health and well-b...
We propose Noise-Augmented Privacy-Preserving Empirical Risk Minimizatio...
This report summarizes the results of Learning to Understand Aerial Imag...
Fast inference of numerical model parameters from data is an important
p...
Computational virtual high-throughput screening (VHTS) with density
func...
A huge amount of data of various types are collected during the COVID-19...
As an effective technique to achieve the implementation of deep neural
n...
Model quantization can reduce the model size and computational latency, ...
Since model quantization helps to reduce the model size and computation
...
Homogeneity attack allows adversaries to obtain the exact values on the
...
The rapid growth of GPS technology and mobile devices has led to a massi...
Code completion is one of the most useful features in the Integrated
Dev...
We study a variant of the classical multi-armed bandit problem (MABP) wh...
We propose a novel tree-based ensemble method named Selective Cascade of...
We consider a single-hop ad hoc network in which each node aims to broad...
The outbreak of the novel coronavirus (COVID-19) is unfolding as a major...
This paper reports a modified axiomatic foundation of the analytic hiera...
The eruption of big data with the increasing collection and processing o...
Contact tracing in the COVID-19 pandemic is key to prevent the further s...
Transparent topology is common in many mobile ad hoc networks (MANETs) s...
Small objects are difficult to detect because of their low resolution an...
We investigate contextual bandits in the presence of side-observations a...