With the surge in attention to Egocentric Hand-Object Interaction (Ego-H...
Existing adversarial attacks against Object Detectors (ODs) suffer from ...
Data-efficient learning has drawn significant attention, especially give...
Feed recommendation systems, which recommend a sequence of items for use...
Integrated recommendation, which aims at jointly recommending heterogene...
Adversarial example is a rising way of protecting facial privacy securit...
Understanding objects is a central building block of artificial intellig...
Cold start is an essential and persistent problem in recommender systems...
Recent studies on Click-Through Rate (CTR) prediction has reached new le...
Graph Convolutional Networks (GCNs) and their variants have achieved
sig...
Long-tailed image recognition presents massive challenges to deep learni...
Waterfall Recommender System (RS), a popular form of RS in mobile
applic...
User historical behaviors are proved useful for Click Through Rate (CTR)...
The recently proposed Graph Convolutional Networks (GCNs) have achieved
...
Human activity understanding is of widespread interest in artificial
int...
Attributes and objects can compose diverse compositions. To model the
co...
In this paper, we address the "black-box" problem in predictive process
...
Graph Convolutional Networks (GCNs) are powerful models for node
represe...
Data-driven paradigms are well-known and salient demands of future wirel...
The right to be forgotten has been legislated in many countries but the
...
Card payment fraud is a serious problem, and a roadblock for an optimall...
Graph Convolutional Networks (GCNs) and their variants have received
sig...
Existing image-based activity understanding methods mainly adopt direct
...
Attributes and objects can compose diverse compositions. To model the
co...
In this paper, we propose a new localization framework in which mobile u...
The marriage of wireless big data and machine learning techniques
revolu...
The recent success of single-agent reinforcement learning (RL) encourage...
In this paper, we propose a deep reinforcement learning (DRL) based mobi...
The cloud radio access network (C-RAN) is a promising paradigm to meet t...
Accurate annotation of medical image is the crucial step for image AI
cl...
Magnetic Resonance Imaging (MRI) is widely used in the pathological and
...
In this paper, we propose a two-layer framework to learn the optimal han...