Interactive Recommender Systems (IRS) have been increasingly used in var...
Humans have the ability to reuse previously learned policies to solve ne...
Recently, Ye et al. (Mathematical Programming 2023) designed an algorith...
Recent offline meta-reinforcement learning (meta-RL) methods typically
u...
Decentralized, tamper-proof blockchain is regarded as a solution to a
ch...
In this paper, we focus on analyzing the supercloseness property of a
tw...
In this paper, we introduce a new metric, named Penalty upon Decision (P...
On Bakhvalov-type mesh, uniform convergence analysis of finite element m...
The Transformer has been successfully used in medical image segmentation...
As a popular stabilization technique, the nonsymmetric interior penalty
...
For singularly perturbed convection-diffusion problems, supercloseness
a...
In this paper, we study the convergence of the nonsymmetric interior pen...
In recent years, by utilizing optimization techniques to formulate the
p...
Gradient methods have become mainstream techniques for Bi-Level Optimiza...
A steerable parametric loudspeaker array is known for its directivity an...
In this paper, we propose rWiFiSLAM, an indoor localisation system based...
For singularly perturbed reaction-diffusion problems in 1D and 2D, we st...
Although Physics-Informed Neural Networks (PINNs) have been successfully...
The ability to reuse previous policies is an important aspect of human
i...
For decades, people have been seeking for fishlike flapping motions that...
Most existing salient object detection (SOD) models are difficult to app...
Recently, Optimization-Derived Learning (ODL) has attracted attention fr...
Gradient-based optimization methods for hyperparameter tuning guarantee
...
This paper reviews the challenge on constrained high dynamic range (HDR)...
Gradient methods have become mainstream techniques for Bi-Level Optimiza...
HDR is an important part of computational photography technology. In thi...
Many multi-object tracking (MOT) methods follow the framework of "tracki...
Deep neural networks are vulnerable to adversarial examples, which can f...
In this paper, we analyze the supercloseness result of nonsymmetric inte...
Point set registration is an essential step in many computer vision
appl...
We demonstrate ViDA-MAN, a digital-human agent for multi-modal interacti...
Gradient-based Bi-Level Optimization (BLO) methods have been widely appl...
In recent years, Bi-Level Optimization (BLO) techniques have received
ex...
Status update systems consist of sensors that take measurements of a phy...
Reconfigurable Intelligent Surface (RIS) is a revolutionizing approach t...
Bi-level optimization model is able to capture a wide range of complex
l...
Gridless methods show great superiority in line spectral estimation. The...
The source number identification is an essential step in direction-of-ar...
Goal-conditioned hierarchical reinforcement learning (HRL) serves as a
s...
The paper proposes a new text recognition network for scene-text images....
Fusion is critical for a two-stream network. In this paper, we propose a...
In recent years, gradient-based methods for solving bi-level optimizatio...
Bi-Level Optimization (BLO) is originated from the area of economic game...
For a singularly perturbed elliptic model problem with two small paramet...
We reconsider a linear finite element method on a Bakhvalov-type mesh fo...
A finite element method of any order is applied on a Bakhvalov-type mesh...
In convergence analysis of finite element methods for singularly perturb...
Deployment of Internet of Things (IoT) in smart buildings has received
c...
Meta reinforcement learning (meta-RL) provides a principled approach for...
In recent years, a variety of gradient-based first-order methods have be...