Non-stationary online learning has drawn much attention in recent years....
To consider model uncertainty in global Fréchet regression and improve
d...
Weakly-supervised action localization aims to recognize and localize act...
Deterministic planning assumes that the planning evolves along a fully
p...
In this paper, we propose an online convex optimization method with two
...
With the increasing amount of distributed energy resources (DERs)
integr...
In the transfer-based adversarial attacks, adversarial examples are only...
With the development of adversarial attacks, adversairal examples have b...
Gaussian graphical models typically assume a homogeneous structure acros...
Non-stationary parametric bandits have attracted much attention recently...
This paper investigates group distributionally robust optimization (GDRO...
Stochastically Extended Adversarial (SEA) model is introduced by Sachs e...
Dealing with distribution shifts is one of the central challenges for mo...
Modern data science applications often involve complex relational data w...
We consider a latent space model for dynamic networks, where our objecti...
We investigate online Markov Decision Processes (MDPs) with adversariall...
In this paper, we introduce a matrix quantile factor model for matrix
se...
The standard supervised learning paradigm works effectively when trainin...
In the strong adversarial attacks against deep neural network (DNN), the...
Deep neural network (DNN) with dropout can be regarded as an ensemble mo...
Due to the vulnerability of deep neural networks, the black-box attack h...
Hierarchical clustering recursively partitions data at an increasingly f...
We consider the problem of combining and learning over a set of adversar...
We consider the problem of adversarial bandit convex optimization, that ...
Learning from repeated play in a fixed two-player zero-sum game is a cla...
We investigate online convex optimization in non-stationary environments...
Environmental microorganisms (EMs) are ubiquitous around us and have an
...
The Environmental Microorganism Image Dataset Seventh Version (EMDS-7) i...
In recent years, deep learning has made brilliant achievements in image
...
Nowadays, analysis of transparent images in the field of computer vision...
In this paper we study the problem of stochastic multi-armed bandits (MA...
Image classification has achieved unprecedented advance with the the rap...
Video super-resolution (VSR) aims at restoring a video in low-resolution...
Modeling cyber risks has been an important but challenging task in the d...
In this note, we revisit non-stationary linear bandits, a variant of
sto...
We study the problem of Online Convex Optimization (OCO) with memory, wh...
Latent Dirichlet Allocation (LDA) is a popular topic modeling technique ...
Spherical videos, also known as 360 (panorama) videos, can be viewed
wit...
In recent years, deep learning has made great progress in the fields of ...
Feature evolvable learning has been widely studied in recent years where...
We investigate online convex optimization in non-stationary environments...
In this paper, we present an improved analysis for dynamic regret of str...
The emerging edge-cloud collaborative Deep Learning (DL) paradigm aims a...
Spatial regression models are ubiquitous in many different areas such as...
In conventional supervised learning, a training dataset is given with
gr...
In this paper, we study the problem of learning with augmented classes (...
Bandit Convex Optimization (BCO) is a fundamental framework for modeling...
We consider Hadamard product parametrization as a change-of-variable
(ov...
Background subtraction is a significant component of computer vision sys...
Recently, deep neural networks (DNNs) have been widely applied in mobile...