b'Nan Wu'

research

∙ 03/14/2023

Gamora: Graph Learning based Symbolic Reasoning for Large-Scale Boolean Networks

Reasoning high-level abstractions from bit-blasted Boolean networks (BNs...

0 Nan Wu, et al. ∙

research

∙ 01/21/2023

Improving Accuracy of Zero-Shot Action Recognition with Handcrafted Features

With the development of machine learning, datasets for models are gettin...

0 Nan Wu, et al. ∙

research

∙ 01/09/2023

Privacy-Preserving Record Linkage for Cardinality Counting

Several applications require counting the number of distinct items in th...

0 Nan Wu, et al. ∙

research

∙ 12/02/2022

A Closed-Form EVSI Expression for a Multinomial Data-Generating Process

This paper derives analytic expressions for the expected value of sample...

0 Adam Fleischhacker, et al. ∙

research

∙ 09/02/2022

GReS: Graphical Cross-domain Recommendation for Supply Chain Platform

Supply Chain Platforms (SCPs) provide downstream industries with numerou...

1 Zhiwen Jing, et al. ∙

research

∙ 09/01/2022

Heterogeneous Graph Tree Networks

Heterogeneous graph neural networks (HGNNs) have attracted increasing re...

9 Nan Wu, et al. ∙

research

∙ 07/13/2022

Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation

Using machine learning to solve combinatorial optimization (CO) problems...

11 Haoyu Wang, et al. ∙

research

∙ 06/30/2022

Fairness and Cost Constrained Privacy-Aware Record Linkage

Record linkage algorithms match and link records from different database...

0 Nan Wu, et al. ∙

research

∙ 06/01/2022

Dog nose print matching with dual global descriptor based on Contrastive Learning

Recent studies in biometric-based identification tasks have shown that d...

3 Bin Li, et al. ∙

research

∙ 05/19/2022

Neural network topological snake models for locating general phase diagrams

Machine learning for locating phase diagram has received intensive resea...

13 Wanzhou Zhang, et al. ∙

research

∙ 04/27/2022

GTNet: A Tree-Based Deep Graph Learning Architecture

We propose Graph Tree Networks (GTNets), a deep graph learning architect...

13 Nan Wu, et al. ∙

research

∙ 02/10/2022

Characterizing and overcoming the greedy nature of learning in multi-modal deep neural networks

We hypothesize that due to the greedy nature of learning in multi-modal ...

0 Nan Wu, et al. ∙

research

∙ 01/30/2022

Will Metaverse be NextG Internet? Vision, Hype, and Reality

Metaverse, with the combination of the prefix "meta" (meaning transcendi...

0 Ruizhi Cheng, et al. ∙

research

∙ 01/20/2022

Hybrid Graph Models for Logic Optimization via Spatio-Temporal Information

Despite the stride made by machine learning (ML) based performance model...

5 Nan Wu, et al. ∙

research

∙ 01/18/2022

High-Level Synthesis Performance Prediction using GNNs: Benchmarking, Modeling, and Advancing

Agile hardware development requires fast and accurate circuit quality ev...

6 Nan Wu, et al. ∙

research

∙ 01/15/2022

Realtime 3D Object Detection for Headsets

Mobile headsets should be capable of understanding 3D physical environme...

5 Yongjie Guan, et al. ∙

research

∙ 10/20/2021

SLAM: A Unified Encoder for Speech and Language Modeling via Speech-Text Joint Pre-Training

Unsupervised pre-training is now the predominant approach for both text ...

26 Ankur Bapna, et al. ∙

research

∙ 10/15/2021

Cooperative Localization in Massive Networks

Network localization is capable of providing accurate and ubiquitous pos...

0 Yifeng Xiong, et al. ∙

research

∙ 10/14/2021

Inferring Manifolds From Noisy Data Using Gaussian Processes

In analyzing complex datasets, it is often of interest to infer lower di...

9 David B. Dunson, et al. ∙

research

∙ 09/13/2021

Program-to-Circuit: Exploiting GNNs for Program Representation and Circuit Translation

Circuit design is complicated and requires extensive domain-specific exp...

6 Nan Wu, et al. ∙

research

∙ 06/13/2021

Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis

In the last few years, deep learning classifiers have shown promising re...

13 Kangning Liu, et al. ∙

research

∙ 02/16/2021

IronMan: GNN-assisted Design Space Exploration in High-Level Synthesis via Reinforcement Learning

Despite the great success of High-Level Synthesis (HLS) tools, we observ...

11 Nan Wu, et al. ∙

research

∙ 02/16/2021

A Survey of Machine Learning for Computer Architecture and Systems

It has been a long time that computer architecture and systems are optim...

47 Nan Wu, et al. ∙

research

∙ 01/25/2021

Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolation

This work studies the spectral convergence of graph Laplacian to the Lap...

15 Xiuyuan Cheng, et al. ∙

research

∙ 11/13/2020

Phoebe: Reuse-Aware Online Caching with Reinforcement Learning for Emerging Storage Models

With data durability, high access speed, low power efficiency and byte a...

3 Nan Wu, et al. ∙

research

∙ 10/14/2020

Diffusion Based Gaussian Processes on Restricted Domains

In nonparametric regression and spatial process modeling, it is common f...

9 David B. Dunson, et al. ∙

research

∙ 09/19/2020

Reducing false-positive biopsies with deep neural networks that utilize local and global information in screening mammograms

Breast cancer is the most common cancer in women, and hundreds of thousa...

17 Nan Wu, et al. ∙

research

∙ 08/04/2020

An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department

During the COVID-19 pandemic, rapid and accurate triage of patients at t...

71 Farah E Shamout, et al. ∙

research

∙ 07/13/2020

Strong Uniform Consistency with Rates for Kernel Density Estimators with General Kernels on Manifolds

We provide a strong uniform consistency result with the convergence rate...

1 Hau-tieng Wu, et al. ∙

research

∙ 05/22/2020

Data-driven Efficient Solvers and Predictions of Conformational Transitions for Langevin Dynamics on Manifold in High Dimensions

We work on dynamic problems with collected data {x_i} that distributed o...

6 Yuan Gao, et al. ∙

research

∙ 02/13/2020

An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization

Medical images differ from natural images in significantly higher resolu...

13 Yiqiu Shen, et al. ∙

research

∙ 01/20/2020

Memristor Hardware-Friendly Reinforcement Learning

Recently, significant progress has been made in solving sophisticated pr...

0 Nan Wu, et al. ∙

research

∙ 12/11/2019

Diffusion based Gaussian process regression via heat kernel reconstruction

We propose an algorithm for Gaussian Process regression on an unknown em...

0 David B. Dunson, et al. ∙

research

∙ 08/01/2019

Improving localization-based approaches for breast cancer screening exam classification

We trained and evaluated a localization-based deep CNN for breast cancer...

13 Thibault Févry, et al. ∙

research

∙ 07/30/2019

Screening Mammogram Classification with Prior Exams

Radiologists typically compare a patient's most recent breast cancer scr...

3 Jungkyu Park, et al. ∙

research

∙ 06/24/2019

The Value of Collaboration in Convex Machine Learning with Differential Privacy

In this paper, we apply machine learning to distributed private data own...

6 Nan Wu, et al. ∙

research

∙ 06/07/2019

Globally-Aware Multiple Instance Classifier for Breast Cancer Screening

Deep learning models designed for visual classification tasks on natural...

5 Yiqiu Shen, et al. ∙

research

∙ 03/20/2019

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening

We present a deep convolutional neural network for breast cancer screeni...

3 Nan Wu, et al. ∙

research

∙ 11/11/2018

When Locally Linear Embedding Hits Boundary

Based on the Riemannian manifold model, we study the asymptotical behavi...

0 Hau-tieng Wu, et al. ∙

research

∙ 10/01/2018

Network Modeling and Pathway Inference from Incomplete Data ("PathInf")

In this work, we developed a network inference method from incomplete da...

0 Xiang Li, et al. ∙

research

∙ 04/09/2018

Connecting Dots -- from Local Covariance to Empirical Intrinsic Geometry and Locally Linear Embedding

Local covariance structure under the manifold setup has been widely appl...

0 John Malik, et al. ∙

research

∙ 11/10/2017

Breast density classification with deep convolutional neural networks

Breast density classification is an essential part of breast cancer scre...

0 Nan Wu, et al. ∙

research

∙ 03/07/2016

A Real-Time and Energy-Efficient Implementation of Difference-of-Gaussian with Flexible Thin-Film Transistors

With many advantageous features, softness and better biocompatibility, f...

0 Nan Wu, et al. ∙

Nan Wu

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