b'Peng Chen'

research

∙ 08/02/2022

Optimal design of chemoepitaxial guideposts for directed self-assembly of block copolymer systems using an inexact-Newton algorithm

Directed self-assembly (DSA) of block-copolymers (BCPs) is one of the mo...

Dingcheng Luo, et al. ∙

research

∙ 06/21/2022

Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning

Neural operators have gained significant attention recently due to their...

Thomas O'Leary-Roseberry, et al. ∙

research

∙ 05/25/2022

RIS-ADMM: An ADMM-Based Passive and Sparse Sensing Method with Interference Removal

The reconfigurable intelligent surface (RIS) has been a potential techno...

Peng Chen, et al. ∙

research

∙ 05/12/2022

Image Gradient Decomposition for Parallel and Memory-Efficient Ptychographic Reconstruction

Ptychography is a popular microscopic imaging modality for many scientif...

Xiao Wang, et al. ∙

research

∙ 05/06/2022

A Rapid Power-iterative Root-MUSIC Estimator for Massive/Ultra-massive MIMO Receiver

For a passive direction of arrival (DOA) measurement system using massiv...

Qijuan Jie, et al. ∙

research

∙ 04/05/2022

Persistent Kernels for Iterative Memory-bound GPU Applications

Iterative memory-bound solvers commonly occur in HPC codes. Typical GPU ...

Lingqi Zhang, et al. ∙

research

∙ 04/05/2022

Learning Video Salient Object Detection Progressively from Unlabeled Videos

Recent deep learning-based video salient object detection (VSOD) has ach...

Binwei Xu, et al. ∙

research

∙ 01/22/2022

Manifold Optimization Based Multi-user Rate Maximization Aided by Intelligent Reflecting Surface

In this work, two problems associated with a downlink multi-user system ...

Liyue Zhang, et al. ∙

research

∙ 01/20/2022

Derivative-informed projected neural network for large-scale Bayesian optimal experimental design

We address the solution of large-scale Bayesian optimal experimental des...

Keyi Wu, et al. ∙

research

∙ 11/22/2021

Mesa: A Memory-saving Training Framework for Transformers

There has been an explosion of interest in designing high-performance Tr...

Zizheng Pan, et al. ∙

research

∙ 10/14/2021

Looper: An end-to-end ML platform for product decisions

Modern software systems and products increasingly rely on machine learni...

Igor L. Markov, et al. ∙

research

∙ 09/12/2021

Efficient Re-parameterization Residual Attention Network For Nonhomogeneous Image Dehazing

This paper proposes an end-to-end Efficient Re-parameterizationResidual ...

Tian Ye, et al. ∙

research

∙ 09/06/2021

PermuteFormer: Efficient Relative Position Encoding for Long Sequences

A recent variation of Transformer, Performer, scales Transformer to long...

Peng Chen, et al. ∙

research

∙ 07/30/2021

A SPA-based Manifold Learning Framework for Motor Imagery EEG Data Classification

The electroencephalography (EEG) signal is a non-stationary, stochastic,...

Xiangyun Li, et al. ∙

research

∙ 05/08/2021

ABCNet v2: Adaptive Bezier-Curve Network for Real-time End-to-end Text Spotting

End-to-end text-spotting, which aims to integrate detection and recognit...

Yuliang Liu, et al. ∙

research

∙ 04/27/2021

Performance Portable Back-projection Algorithms on CPUs: Agnostic Data Locality and Vectorization Optimizations

Computed Tomography (CT) is a key 3D imaging technology that fundamental...

Peng Chen, et al. ∙

research

∙ 04/07/2021

LI-Net: Large-Pose Identity-Preserving Face Reenactment Network

Face reenactment is a challenging task, as it is difficult to maintain a...

Jin Liu, et al. ∙

research

∙ 04/05/2021

Robust optimization Design of a New Combined Median Barrier Based on Taguchi method and Grey Relational Analysis

Accidents that vehicles cross median and enter opposite lane happen freq...

Yupeng Huang, et al. ∙

research

∙ 03/01/2021

Towards Enhancing Database Education: Natural Language Generation Meets Query Execution Plans

The database systems course is offered as part of an undergraduate compu...

Weiguo Wang, et al. ∙

research

∙ 02/12/2021

A fast and scalable computational framework for goal-oriented linear Bayesian optimal experimental design: Application to optimal sensor placement

Optimal experimental design (OED) is a principled framework for maximizi...

Keyi Wu, et al. ∙

research

∙ 01/13/2021

ABS: Automatic Bit Sharing for Model Compression

We present Automatic Bit Sharing (ABS) to automatically search for optim...

Jing Liu, et al. ∙

research

∙ 12/31/2020

xERTE: Explainable Reasoning on Temporal Knowledge Graphs for Forecasting Future Links

Interest has been rising lately towards modeling time-evolving knowledge...

Zhen Han, et al. ∙

research

∙ 11/30/2020

Derivative-Informed Projected Neural Networks for High-Dimensional Parametric Maps Governed by PDEs

Many-query problems, arising from uncertainty quantification, Bayesian i...

Thomas O'Leary-Roseberry, et al. ∙

research

∙ 11/29/2020

Fully Quantized Image Super-Resolution Networks

With the rising popularity of intelligent mobile devices, it is of great...

Hu Wang, et al. ∙

research

∙ 11/23/2020

A sequential sensor selection strategy for hyper-parameterized linear Bayesian inverse problems

We consider optimal sensor placement for hyper-parameterized linear Baye...

Nicole Aretz-Nellesen, et al. ∙

research

∙ 11/19/2020

Taylor approximation for chance constrained optimization problems governed by partial differential equations with high-dimensional random parameters

We propose a fast and scalable optimization method to solve chance or pr...

Peng Chen, et al. ∙

research

∙ 11/18/2020

ArSMART: An Improved SMART NoC Design Supporting Arbitrary-Turn Transmission

SMART NoC, which transmits unconflicted flits to distant processing elem...

Hui Chen, et al. ∙

research

∙ 11/08/2020

DyERNIE: Dynamic Evolution of Riemannian Manifold Embeddings for Temporal Knowledge Graph Completion

There has recently been increasing interest in learning representations ...

Zhen Han, et al. ∙

research

∙ 11/02/2020

Bayesian inference of heterogeneous epidemic models: Application to COVID-19 spread accounting for long-term care facilities

We propose a high dimensional Bayesian inference framework for learning ...

Peng Chen, et al. ∙

research

∙ 10/28/2020

A fast and scalable computational framework for large-scale and high-dimensional Bayesian optimal experimental design

We develop a fast and scalable computational framework to solve large-sc...

Keyi Wu, et al. ∙

research

∙ 10/27/2020

Matrix Engines for High Performance Computing:A Paragon of Performance or Grasping at Straws?

Matrix engines or units, in different forms and affinities, are becoming...

Jens Domke, et al. ∙

research

∙ 09/16/2020

Tag and Correct: Question aware Open Information Extraction with Two-stage Decoding

Question Aware Open Information Extraction (Question aware Open IE) take...

Martin Kuo, et al. ∙

research

∙ 08/12/2020

FATNN: Fast and Accurate Ternary Neural Networks

Ternary Neural Networks (TNNs) have received much attention due to being...

Peng Chen, et al. ∙

research

∙ 07/14/2020

AQD: Towards Accurate Quantized Object Detection

Network quantization aims to lower the bitwidth of weights and activatio...

Jing Liu, et al. ∙

research

∙ 02/25/2020

Stein variational reduced basis Bayesian inversion

We propose and analyze a Stein variational reduced basis method (SVRB) t...

Peng Chen, et al. ∙

research

∙ 02/18/2020

An Efficient Secure Dynamic Skyline Query Model

It is now cost-effective to outsource large dataset and perform query ov...

Weiguo Wang, et al. ∙

research

∙ 02/18/2020

SCALE: An Efficient Framework for Secure Dynamic Skyline Query Processing in the Cloud

It is now cost-effective to outsource large dataset and perform query ov...

Weiguo Wang, et al. ∙

research

∙ 02/14/2020

Tensor train construction from tensor actions, with application to compression of large high order derivative tensors

We present a method for converting tensors into tensor train format base...

Nick Alger, et al. ∙

research

∙ 02/09/2020

Projected Stein Variational Gradient Descent

The curse of dimensionality is a critical challenge in Bayesian inferenc...

Peng Chen, et al. ∙

research

∙ 02/01/2020

Training-free Monocular 3D Event Detection System for Traffic Surveillance

We focus on the problem of detecting traffic events in a surveillance sc...

Lijun Yu, et al. ∙

research

∙ 12/24/2019

Audio-based automatic mating success prediction of giant pandas

Giant pandas, stereotyped as silent animals, make significantly more voc...

WeiRan Yan, et al. ∙

research

∙ 12/23/2019

One-Shot Imitation Filming of Human Motion Videos

Imitation learning has been applied to mimic the operation of a human ca...

Chong Huang, et al. ∙

research

∙ 11/05/2019

DLA: Dense-Layer-Analysis for Adversarial Example Detection

In recent years Deep Neural Networks (DNNs) have achieved remarkable res...

Philip Sperl, et al. ∙

research

∙ 09/29/2019

Futures-Based Resource Trading and Fair Pricing in Real-Time IoT Networks

Technology advancements on sensing, communications, and computing direct...

Shuran Sheng, et al. ∙

research

∙ 09/06/2019

iFDK: A Scalable Framework for Instant High-resolution Image Reconstruction

Computed Tomography (CT) is a widely used technology that requires compu...

Peng Chen, et al. ∙

research

∙ 08/16/2019

Learning Deep Representations by Mutual Information for Person Re-identification

Most existing person re-identification (ReID) methods have good feature ...

Peng Chen, et al. ∙

research

∙ 08/09/2019

Distinguishing Individual Red Pandas from Their Faces

Individual identification is essential to animal behavior and ecology re...

Qi He, et al. ∙

research

∙ 07/14/2019

A Versatile Software Systolic Execution Model for GPU Memory-Bound Kernels

This paper proposes a versatile high-performance execution model, inspir...

Peng Chen, et al. ∙

research

∙ 05/29/2019

Matryoshka: fuzzing deeply nested branches

Greybox fuzzing has made impressive progress in recent years, evolving f...

Peng Chen, et al. ∙

research

∙ 05/27/2019

Giant Panda Face Recognition Using Small Dataset

Giant panda (panda) is a highly endangered animal. Significant efforts a...

Wojciech Michal Matkowski, et al. ∙

Peng Chen

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