Search Results for author: Rui Chen

Found 35 papers, 5 papers with code

ActiveZero: Mixed Domain Learning for Active Stereovision with Zero Annotation

no code implementations6 Dec 2021 Isabella Liu, Edward Yang, Jianyu Tao, Rui Chen, Xiaoshuai Zhang, Qing Ran, Zhu Liu, Hao Su

First, we demonstrate the transferability of our method to out-of-distribution real data by using a mixed domain learning strategy.

Radio-Frequency Multi-Mode OAM Detection Based on UCA Samples Learning

no code implementations29 Nov 2021 Jiabei Fan, Rui Chen, Wen-Xuan Long, Marco Moretti, Jiandong Li

Orbital angular momentum (OAM) at radio-frequency provides a novel approach of multiplexing a set of orthogonal modes on the same frequency channel to achieve high spectral efficiencies.

AoA Estimation for OAM Communication Systems With Mode-Frequency Multi-Time ESPRIT Method

no code implementations18 Oct 2021 Wen-Xuan Long, Rui Chen, Marco Moretti, Jiandong Li

Radio orbital angular momentum (OAM) communications require accurate alignment between the transmit and receive beam directions.

Adaptive Label Smoothing To Regularize Large-Scale Graph Training

no code implementations30 Aug 2021 Kaixiong Zhou, Ninghao Liu, Fan Yang, Zirui Liu, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu

Graph neural networks (GNNs), which learn the node representations by recursively aggregating information from its neighbors, have become a predominant computational tool in many domains.

Node Clustering

Dirichlet Energy Constrained Learning for Deep Graph Neural Networks

no code implementations NeurIPS 2021 Kaixiong Zhou, Xiao Huang, Daochen Zha, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu

To this end, we analyze the bottleneck of deep GNNs by leveraging the Dirichlet energy of node embeddings, and propose a generalizable principle to guide the training of deep GNNs.

HyperNP: Interactive Visual Exploration of Multidimensional Projection Hyperparameters

no code implementations25 Jun 2021 Gabriel Appleby, Mateus Espadoto, Rui Chen, Samuel Goree, Alexandru Telea, Erik W Anderson, Remco Chang

Projection algorithms such as t-SNE or UMAP are useful for the visualization of high dimensional data, but depend on hyperparameters which must be tuned carefully.

Robust Sample Weighting to Facilitate Individualized Treatment Rule Learning for a Target Population

no code implementations3 May 2021 Rui Chen, Jared D. Huling, Guanhua Chen, Menggang Yu

Although adjusting for differences between source and target populations can potentially lead to an improved ITR for the target population, it can substantially increase the variability in ITR estimation.

Integer Programming for Causal Structure Learning in the Presence of Latent Variables

1 code implementation5 Feb 2021 Rui Chen, Sanjeeb Dash, Tian Gao

The problem of finding an ancestral acyclic directed mixed graph (ADMG) that represents the causal relationships between a set of variables is an important area of research on causal inference.

Causal Inference

Hidden-charm pentaquarks with triple strangeness due to the $Ω_{c}^{(*)}\bar{D}_s^{(*)}$ interactions

no code implementations27 Jan 2021 Fu-Lai Wang, Xin-Dian Yang, Rui Chen, Xiang Liu

Our results suggest that the $\Omega_{c}\bar D_s^*$ state with $J^P={3}/{2}^{-}$ and the $\Omega_{c}^{*}\bar D_s^*$ state with $J^P={5}/{2}^{-}$ can be recommended as the candidates of the hidden-charm molecular pentaquark with triple strangeness.

High Energy Physics - Phenomenology High Energy Physics - Experiment

Towards Energy Efficient Federated Learning over 5G+ Mobile Devices

no code implementations13 Jan 2021 Dian Shi, Liang Li, Rui Chen, Pavana Prakash, Miao Pan, Yuguang Fang

The continuous convergence of machine learning algorithms, 5G and beyond (5G+) wireless communications, and artificial intelligence (AI) hardware implementation hastens the birth of federated learning (FL) over 5G+ mobile devices, which pushes AI functions to mobile devices and initiates a new era of on-device AI applications.

Federated Learning Quantization

To Talk or to Work: Energy Efficient Federated Learning over Mobile Devices via the Weight Quantization and 5G Transmission Co-Design

no code implementations21 Dec 2020 Rui Chen, Liang Li, Kaiping Xue, Chi Zhang, Lingjia Liu, Miao Pan

Observed the fact that the energy consumption of local computing is comparable to that of the model updates via 5G transmissions, we formulate the energy efficient FL problem into a mixed-integer programming problem to elaborately determine the quantization strategies and allocate the wireless bandwidth for heterogeneous 5G mobile devices.

Edge-computing Federated Learning +1

Offline Meta-level Model-based Reinforcement Learning Approach for Cold-Start Recommendation

no code implementations4 Dec 2020 Yanan Wang, Yong Ge, Li Li, Rui Chen, Tong Xu

To improve adaptation efficiency, we learn to recover the user policy and reward from only a few interactions via an inverse reinforcement learning method to assist a meta-level recommendation agent.

Model-based Reinforcement Learning Recommendation Systems

Explainable Recommender Systems via Resolving Learning Representations

no code implementations21 Aug 2020 Ninghao Liu, Yong Ge, Li Li, Xia Hu, Rui Chen, Soo-Hyun Choi

Different from previous work, in our model, factor discovery and representation learning are simultaneously conducted, and we are able to handle extra attribute information and knowledge.

Recommendation Systems Representation Learning

Multi-mode OAM Radio Waves: Generation, Angle of Arrival Estimation and Reception With UCAs

no code implementations2 Jul 2020 Rui Chen, Wen-Xuan Long, Xiaodong Wang, Jiandong Li

To solve these problems, we propose an overall scheme of the line-of-sight multi-carrier and multi-mode OAM (LoS MCMM-OAM) communication based on uniform circular arrays (UCAs).

Towards Deeper Graph Neural Networks with Differentiable Group Normalization

1 code implementation NeurIPS 2020 Kaixiong Zhou, Xiao Huang, Yuening Li, Daochen Zha, Rui Chen, Xia Hu

Graph neural networks (GNNs), which learn the representation of a node by aggregating its neighbors, have become an effective computational tool in downstream applications.

Sex Differences in Severity and Mortality Among Patients With COVID-19: Evidence from Pooled Literature Analysis and Insights from Integrated Bioinformatic Analysis

no code implementations30 Mar 2020 Xiyi Wei, Yu-Tian Xiao, Jian Wang, Rui Chen, Wei zhang, Yue Yang, Daojun Lv, Chao Qin, Di Gu, Bo Zhang, Weidong Chen, Jianquan Hou, Ninghong Song, Guohua Zeng, Shancheng Ren

Objective: To conduct a meta-analysis of current studies that examined sex differences in severity and mortality in patients with COVID-19, and identify potential mechanisms underpinning these differences.

Developing Multi-Task Recommendations with Long-Term Rewards via Policy Distilled Reinforcement Learning

no code implementations27 Jan 2020 Xi Liu, Li Li, Ping-Chun Hsieh, Muhe Xie, Yong Ge, Rui Chen

With the explosive growth of online products and content, recommendation techniques have been considered as an effective tool to overcome information overload, improve user experience, and boost business revenue.

Knowledge Distillation Multi-Task Learning

Normal Assisted Stereo Depth Estimation

no code implementations CVPR 2020 Uday Kusupati, Shuo Cheng, Rui Chen, Hao Su

We couple the learning of a multi-view normal estimation module and a multi-view depth estimation module.

Stereo Depth Estimation

S4G: Amodal Single-view Single-Shot SE(3) Grasp Detection in Cluttered Scenes

no code implementations31 Oct 2019 Yuzhe Qin, Rui Chen, Hao Zhu, Meng Song, Jing Xu, Hao Su

Grasping is among the most fundamental and long-lasting problems in robotics study.

Learning Lightweight Pedestrian Detector with Hierarchical Knowledge Distillation

no code implementations20 Sep 2019 Rui Chen, Haizhou Ai, Chong Shang, Long Chen, Zijie Zhuang

It remains very challenging to build a pedestrian detection system for real world applications, which demand for both accuracy and speed.

Knowledge Distillation Pedestrian Detection

Active Learning for Risk-Sensitive Inverse Reinforcement Learning

no code implementations14 Sep 2019 Rui Chen, Wenshuo Wang, Zirui Zhao, Ding Zhao

One typical assumption in inverse reinforcement learning (IRL) is that human experts act to optimize the expected utility of a stochastic cost with a fixed distribution.

Active Learning

Point-Based Multi-View Stereo Network

1 code implementation ICCV 2019 Rui Chen, Songfang Han, Jing Xu, Hao Su

More specifically, our method predicts the depth in a coarse-to-fine manner.

Deep Shape from Polarization

no code implementations ECCV 2020 Yunhao Ba, Alex Ross Gilbert, Franklin Wang, Jinfa Yang, Rui Chen, Yiqin Wang, Lei Yan, Boxin Shi, Achuta Kadambi

This paper makes a first attempt to bring the Shape from Polarization (SfP) problem to the realm of deep learning.

GRIP: Generative Robust Inference and Perception for Semantic Robot Manipulation in Adversarial Environments

no code implementations20 Mar 2019 Xiaotong Chen, Rui Chen, Zhiqiang Sui, Zhefan Ye, Yanqi Liu, R. Iris Bahar, Odest Chadwicke Jenkins

In this work, we propose Generative Robust Inference and Perception (GRIP) as a two-stage object detection and pose estimation system that aims to combine relative strengths of discriminative CNNs and generative inference methods to achieve robust estimation.

Object Detection Pose Estimation

Micro- and Macro-Level Churn Analysis of Large-Scale Mobile Games

no code implementations14 Jan 2019 Xi Liu, Muhe Xie, Xidao Wen, Rui Chen, Yong Ge, Nick Duffield, Na Wang

In this paper, we present the first large-scale churn analysis for mobile games that supports both micro-level churn prediction and macro-level churn ranking.

Streaming Network Embedding through Local Actions

no code implementations14 Nov 2018 Xi Liu, Ping-Chun Hsieh, Nick Duffield, Rui Chen, Muhe Xie, Xidao Wen

Thus the approach of adapting the existing methods to the streaming environment faces non-trivial technical challenges.

Multi-class Classification Network Embedding

A Semi-Supervised and Inductive Embedding Model for Churn Prediction of Large-Scale Mobile Games

no code implementations20 Aug 2018 Xi Liu, Muhe Xie, Xidao Wen, Rui Chen, Yong Ge, Nick Duffield, Na Wang

To evaluate the performance of our solution, we collect real-world data from the Samsung Game Launcher platform that includes tens of thousands of games and hundreds of millions of user-app interactions.

Extreme Scale FMM-Accelerated Boundary Integral Equation Solver for Wave Scattering

1 code implementation27 Mar 2018 Mustafa Abduljabbar, Mohammed Al Farhan, Noha Al-Harthi, Rui Chen, Rio Yokota, Hakan Bagci, David Keyes

With distributed memory optimizations, on the other hand, we report near-optimal efficiency in the weak scalability study with respect to both the logarithmic communication complexity as well as the theoretical scaling complexity of FMM.

Performance Computational Engineering, Finance, and Science Mathematical Software

Noise Level Estimation for Overcomplete Dictionary Learning Based on Tight Asymptotic Bounds

no code implementations9 Dec 2017 Rui Chen, Changshui Yang, Huizhu Jia, Xiaodong Xie

In this letter, we address the problem of estimating Gaussian noise level from the trained dictionaries in update stage.

Dictionary Learning

Bayer Demosaicking Using Optimized Mean Curvature over RGB channels

no code implementations17 May 2017 Rui Chen, Huizhu Jia, Xiange Wen, Xiaodong Xie

Color artifacts of demosaicked images are often found at contours due to interpolation across edges and cross-channel aliasing.

Demosaicking

Correlation Preserving Sparse Coding Over Multi-level Dictionaries for Image Denoising

no code implementations23 Dec 2016 Rui Chen, Huizhu Jia, Xiaodong Xie, Wen Gao

In this letter, we propose a novel image denoising method based on correlation preserving sparse coding.

Image Denoising

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