As an effective tool for eliciting the power of Large Language Models (L...
Personas are crucial in software development processes, particularly in ...
In the multimedia era, image is an effective medium in search advertisin...
One of the fundamental challenges in causal inference is to estimate the...
In this article we develop a feasible version of the assumption-lean tes...
Image compression aims to reduce the information redundancy in images. M...
Ranking model plays an essential role in e-commerce search and
recommend...
When the base station has downlink channel status information (CSI), the...
Computed tomography (CT) scans offer a detailed, three-dimensional
repre...
Treatment effect estimation under unconfoundedness is a fundamental task...
An essential problem in causal inference is estimating causal effects fr...
A predictive model makes outcome predictions based on some given feature...
In this paper, we propose an effective sound event detection (SED) metho...
Estimating direct and indirect causal effects from observational data is...
Higher-Order Influence Functions (HOIFs) provide a unified theory for
co...
The instrumental variable (IV) approach is a widely used way to estimate...
Identifying prognostic factors for disease progression is a cornerstone ...
Causal mediation analysis can unpack the black box of causality and is
t...
Low-light video enhancement (LLVE) is an important yet challenging task ...
In many fields of scientific research and real-world applications, unbia...
Much research has been devoted to the problem of learning fair
represent...
Pathologists need to combine information from differently stained
pathol...
This paper studies the problem of estimating the contributions of featur...
Instrumental variable (IV) is a powerful approach to inferring the causa...
This paper reviews the challenge on constrained high dynamic range (HDR)...
Federated learning protects data privacy and security by exchanging mode...
Learning an generalized prior for natural image restoration is an import...
Many fundamental problems affecting the care of critically ill patients ...
Recent years have seen a significant amount of interests in Sequential
R...
Lane change for autonomous vehicles (AVs) is an important but challengin...
Unobserved confounding is the main obstacle to causal effect estimation ...
Local-to-global learning approach plays an essential role in Bayesian ne...
We propose a novel zero-shot multi-frame image restoration method for
re...
We propose a splitting Hamiltonian Monte Carlo (SHMC) algorithm, which c...
We study an interesting and challenging problem, learning any part of a
...
Causal Learner is a toolbox for learning causal structure and Markov bla...
In the simulation-based testing and evaluation of autonomous vehicles (A...
In this paper, we present a novel scenario for directional modulation (D...
Brain tumor is one of the leading causes of cancer-related death globall...
Anomaly detection is an important research problem because anomalies oft...
Domain adaptation solves the learning problem in a target domain by
leve...
Moire artifacts are common in digital photography, resulting from the
in...
The increasing maturity of machine learning technologies and their
appli...
Having a large number of covariates can have a negative impact on the qu...
This is the rejoinder to the discussion by Kennedy, Balakrishnan and
Was...
Product search is the most common way for people to satisfy their shoppi...
Causal effect estimation from observational data is an important but
cha...
When smartphone cameras are used to take photos of digital screens, usua...
A central question in many fields of scientific research is to determine...
Motivation: Uncovering the genomic causes of cancer, known as cancer dri...