research
∙
09/05/2023
Debiased Regression Adjustment in Completely Randomized Experiments with Moderately High-dimensional Covariates
Completely randomized experiment is the gold standard for causal inferen...
share
research
∙
09/05/2023
Scenario-Aware Hierarchical Dynamic Network for Multi-Scenario Recommendation
Click-Through Rate (CTR) prediction is a fundamental technique in recomm...
research
∙
07/12/2023
Reading Radiology Imaging Like The Radiologist
Automated radiology report generation aims to generate radiology reports...
research
∙
07/12/2023
Unified Medical Image-Text-Label Contrastive Learning With Continuous Prompt
Contrastive language-image Pre-training (CLIP) [13] can leverage large d...
research
∙
06/05/2023
SelfEvolve: A Code Evolution Framework via Large Language Models
Large language models (LLMs) have already revolutionized code generation...
research
∙
05/18/2023
Bayesian Risk-Averse Q-Learning with Streaming Observations
We consider a robust reinforcement learning problem, where a learning ag...
research
∙
05/07/2023
Root-n consistent semiparametric learning with high-dimensional nuisance functions under minimal sparsity
Treatment effect estimation under unconfoundedness is a fundamental task...
research
∙
04/18/2023
Online fair division with arbitrary entitlements
The division of goods in the online realm poses opportunities and challe...
research
∙
02/07/2023
Multi-Task Deep Recommender Systems: A Survey
Multi-task learning (MTL) aims at learning related tasks in a unified mo...
research
∙
12/26/2022
TextBox 2.0: A Text Generation Library with Pre-trained Language Models
To facilitate research on text generation, this paper presents a compreh...
research
∙
11/29/2022
Residual Permutation Test for High-Dimensional Regression Coefficient Testing
We consider the problem of testing whether a single coefficient is equal...
research
∙
11/25/2022
Generative Modeling in Sinogram Domain for Sparse-view CT Reconstruction
The radiation dose in computed tomography (CT) examinations is harmful f...
research
∙
11/25/2022
Generative Modeling in Structural-Hankel Domain for Color Image Inpainting
In recent years, some researchers focused on using a single image to obt...
research
∙
11/21/2022
Self adaptive global-local feature enhancement for radiology report generation
Automated radiology report generation aims at automatically generating a...
research
∙
06/24/2022
Risk-averse Contextual Multi-armed Bandit Problem with Linear Payoffs
In this paper we consider the contextual multi-armed bandit problem for ...
research
∙
02/15/2022
Long-term Causal Inference Under Persistent Confounding via Data Combination
We study the identification and estimation of long-term treatment effect...
research
∙
01/19/2022
Virtual Coil Augmentation Technology for MRI via Deep Learning
Magnetic resonance imaging (MRI) is a widely used medical imaging modali...
research
∙
01/19/2022
Variable Augmented Network for Invertible MR Coil Compression
A large number of coils are able to provide enhanced signal-to-noise rat...
research
∙
09/07/2021
MRI Reconstruction Using Deep Energy-Based Model
Purpose: Although recent deep energy-based generative models (EBMs) have...
research
∙
09/06/2021
Rerandomization with Diminishing Covariate Imbalance and Diverging Number of Covariates
Completely randomized experiments have been the gold standard for drawin...
research
∙
09/02/2021
Variable Augmented Network for Invertible Modality Synthesis-Fusion
As an effective way to integrate the information contained in multiple m...
research
∙
08/16/2021
Robust Beamforming Design for Rate Splitting Multiple Access-Aided MISO Visible Light Communications
This paper addresses robust beamforming design for rate splitting multip...
research
∙
08/14/2021
High-dimensional Assisted Generative Model for Color Image Restoration
This work presents an unsupervised deep learning scheme that exploiting ...
research
∙
07/22/2021
Learning Sparse Fixed-Structure Gaussian Bayesian Networks
Gaussian Bayesian networks (a.k.a. linear Gaussian structural equation m...
research
∙
07/09/2021
Wavelet Transform-assisted Adaptive Generative Modeling for Colorization
Unsupervised deep learning has recently demonstrated the promise to prod...
research
∙
06/17/2021
Identifiability of AMP chain graph models
We study identifiability of Andersson-Madigan-Perlman (AMP) chain graph ...
research
∙
04/19/2021
Direction-Aggregated Attack for Transferable Adversarial Examples
Deep neural networks are vulnerable to adversarial examples that are cra...
research
∙
04/03/2021
Sparse Code Multiple Access for 6G Wireless Communication Networks: Recent Advances and Future Directions
As 5G networks rolling out in many different countries nowadays, the tim...
research
∙
12/28/2020
Joint Intensity-Gradient Guided Generative Modeling for Colorization
This paper proposes an iterative generative model for solving the automa...
research
∙
11/17/2020
Debiased Inverse Propensity Score Weighting for Estimation of Average Treatment Effects with High-Dimensional Confounders
We consider estimation of average treatment effects given observational ...
research
∙
11/03/2020
Amortized Variational Deep Q Network
Efficient exploration is one of the most important issues in deep reinfo...
research
∙
10/26/2020
Estimation of the l_2-norm and testing in sparse linear regression with unknown variance
We consider the related problems of estimating the l_2-norm and the squa...
research
∙
10/16/2020
Joint Inference of Multiple Graphs from Matrix Polynomials
Inferring graph structure from observations on the nodes is an important...
research
∙
02/27/2020
Learning in the Frequency Domain
Deep neural networks have achieved remarkable success in computer vision...
research
∙
01/15/2020
Causal Discovery from Incomplete Data: A Deep Learning Approach
As systems are getting more autonomous with the development of artificia...
research
∙
11/19/2019
DARB: A Density-Aware Regular-Block Pruning for Deep Neural Networks
The rapidly growing parameter volume of deep neural networks (DNNs) hind...
research
∙
11/18/2019
FFDNet-Based Channel Estimation for Massive MIMO Visible Light Communication Systems
Channel estimation is of crucial importance in massive multiple-input mu...
research
∙
11/17/2019
Subcarrier Assignment Schemes Based on Q-Learning in Wideband Cognitive Radio Networks
Subcarrier assignment is of crucial importance in wideband cognitive rad...
research
∙
10/24/2019
Computation Efficiency Maximization in OFDMA-Based Mobile Edge Computing Networks
Computation-efficient resource allocation strategies are of crucial impo...
research
∙
10/23/2019
Learning Priors in High-frequency Domain for Inverse Imaging Reconstruction
Ill-posed inverse problems in imaging remain an active research topic in...
research
∙
10/20/2019
Permutation-Based Causal Structure Learning with Unknown Intervention Targets
We consider the problem of estimating causal DAG models from a mix of ob...
research
∙
10/12/2019
Performance Analysis on Visible Light Communications With Multi-Eavesdroppers and Practical Amplitude Constraint
In this paper the secure performance for the visible light communication...
research
∙
10/12/2019
Mobile Edge Computing in Unmanned Aerial Vehicle Networks
Unmanned aerial vehicle (UAV)-enabled communication networks are promisi...
research
∙
06/12/2019
Learning High-Dimensional Gaussian Graphical Models under Total Positivity without Tuning Parameters
We consider the problem of estimating an undirected Gaussian graphical m...
research
∙
06/03/2019
Anchored Causal Inference in the Presence of Measurement Error
We consider the problem of learning a causal graph in the presence of me...
research
∙
06/22/2018
Robust Resource Allocation for MISO Cognitive Radio Networks Under Two Practical Non-Linear Energy Harvesting Models
To achieve a good tradeoff between the consumed power and the harvested ...
research
∙
04/17/2018
Minimax rate of testing in sparse linear regression
We consider the problem of testing the hypothesis that the parameter of ...
research
∙
04/03/2018
High-Dimensional Joint Estimation of Multiple Directed Gaussian Graphical Models
We consider the problem of jointly estimating multiple related directed ...
research
∙
02/15/2018
Direct Estimation of Differences in Causal Graphs
We consider the problem of estimating the differences between two causal...
research
∙
01/06/2018