Search Results for author: Wang

Found 27 papers, 6 papers with code

SuperLoRA: Parameter-Efficient Unified Adaptation of Multi-Layer Attention Modules

no code implementations18 Mar 2024 Xiangyu Chen, Jing Liu, Ye Wang, Pu, Wang, Matthew Brand, Guanghui Wang, Toshiaki Koike-Akino

Low-rank adaptation (LoRA) and its variants are widely employed in fine-tuning large models, including large language models for natural language processing and diffusion models for computer vision.

Transfer Learning

Towards Enabling Cardiac Digital Twins of Myocardial Infarction Using Deep Computational Models for Inverse Inference

no code implementations10 Jul 2023 Lei LI, Julia Camps, Zhinuo, Wang, Abhirup Banerjee, Marcel Beetz, Blanca Rodriguez, Vicente Grau

In this work, we investigate the feasibility of inferring myocardial tissue properties from the electrocardiogram (ECG) within a CDT platform.

MOPO-LSI: A User Guide

no code implementations4 Jul 2023 Yong Zheng, Kumar Neelotpal Shukla, Jasmine Xu, David, Wang, Michael O'Leary

MOPO-LSI is an open-source Multi-Objective Portfolio Optimization Library for Sustainable Investments.

Portfolio Optimization

A Cross-direction Task Decoupling Network for Small Logo Detection

no code implementations4 May 2023 Hou, Sujuan, Xingzhuo, Min, Weiqing, Li, Jiacheng, Wang, Jing, Zheng, Yuanjie, Jiang, Shuqiang

The aggregation of small logos also brings a great challenge to the classification and localization of logos.

Influence of Myocardial Infarction on QRS Properties: A Simulation Study

no code implementations4 Apr 2023 Lei LI, Julia Camps, Zhinuo, Wang, Abhirup Banerjee, Blanca Rodriguez, Vicente Grau

However, the influence of various MI properties on the QRS is not intuitively predictable. In this work, we have systematically investigated the effects of 17 post-MI scenarios, varying the location, size, transmural extent, and conductive level of scarring and border zone area, on the forward-calculated QRS.

The Best of Both Worlds: Accurate Global and Personalized Models through Federated Learning with Data-Free Hyper-Knowledge Distillation

no code implementations21 Jan 2023 Huancheng Chen, Johnny, Wang, Haris Vikalo

In particular, each client extracts and sends to the server the means of local data representations and the corresponding soft predictions -- information that we refer to as ``hyper-knowledge".

Knowledge Distillation Personalized Federated Learning

Modeling Human Eye Movements with Neural Networks in a Maze-Solving Task

1 code implementation20 Dec 2022 Jason Li, Nicholas Watters, Yingting, Wang, Hansem Sohn, Mehrdad Jazayeri

This not only provides a generative model of eye movements in this task but also suggests a computational theory for how humans solve the task, namely that humans use mental simulation.

Adversarial Bi-Regressor Network for Domain Adaptive Regression

no code implementations20 Sep 2022 Haifeng Xia, Pu, Wang, Toshiaki Koike-Akino, Ye Wang, Philip Orlik, Zhengming Ding

Domain adaptation (DA) aims to transfer the knowledge of a well-labeled source domain to facilitate unlabeled target learning.

Domain Adaptation regression

Masked Co-attentional Transformer reconstructs 100x ultra-fast/low-dose whole-body PET from longitudinal images and anatomically guided MRI

no code implementations9 May 2022 Yan-Ran, Wang, Liangqiong Qu, Natasha Diba Sheybani, Xiaolong Luo, Jiangshan Wang, Kristina Elizabeth Hawk, Ashok Joseph Theruvath, Sergios Gatidis, Xuerong Xiao, Allison Pribnow, Daniel Rubin, Heike E. Daldrup-Link

In this study, we utilize the global similarity between baseline and follow-up PET and magnetic resonance (MR) images to develop Masked-LMCTrans, a longitudinal multi-modality co-attentional CNN-Transformer that provides interaction and joint reasoning between serial PET/MRs of the same patient.

Dynamic Structure in Four-strategy Game: Theory and Experiment

no code implementations28 Mar 2022 Zhijian Wang, Shujie Zhou, Qinmei Yao, Yijia, Wang

Game dynamics theory, as a field of science, the consistency of theory and experiment is essential.

Multi-Modal Recurrent Fusion for Indoor Localization

no code implementations19 Feb 2022 Jianyuan Yu, Pu, Wang, Toshiaki Koike-Akino, Philip V. Orlik

This paper considers indoor localization using multi-modal wireless signals including Wi-Fi, inertial measurement unit (IMU), and ultra-wideband (UWB).

Indoor Localization regression

Multi-Band Wi-Fi Sensing with Matched Feature Granularity

no code implementations28 Dec 2021 Jianyuan Yu, Pu, Wang, Toshiaki Koike-Akino, Ye Wang, Philip V. Orlik, R. Michael Buehrer

The granularity matching is realized by pairing two feature maps from the CSI and beam SNR at different granularity levels and linearly combining all paired feature maps into a fused feature map with learnable weights.

Indoor Localization

LibFewShot: A Comprehensive Library for Few-shot Learning

1 code implementation10 Sep 2021 Wenbin Li, Ziyi, Wang, Xuesong Yang, Chuanqi Dong, Pinzhuo Tian, Tiexin Qin, Jing Huo, Yinghuan Shi, Lei Wang, Yang Gao, Jiebo Luo

Furthermore, based on LibFewShot, we provide comprehensive evaluations on multiple benchmarks with various backbone architectures to evaluate common pitfalls and effects of different training tricks.

Data Augmentation Few-Shot Image Classification +2

Multi-Objective Recommendations: A Tutorial

no code implementations13 Aug 2021 Yong Zheng, David, Wang

Recommender systems (RecSys) have been well developed to assist user decision making.

Decision Making Recommendation Systems

Cyber Intrusion Detection by Using Deep Neural Networks with Attack-sharing Loss

no code implementations17 Mar 2021 Boxiang Dong, Hui, Wang, Aparna S. Varde, Dawei Li, Bharath K. Samanthula, Weifeng Sun, Liang Zhao

To achieve high detection accuracy on imbalanced data, we design a novel attack-sharing loss function that can effectively move the decision boundary towards the attack classes and eliminates the bias towards the majority/benign class.

General Classification Intrusion Detection

A Light Transformer For Speech-To-Intent Applications

1 code implementation IEEE Spoken Language Technology Workshop (SLT) 2021 Wang, Pu; Van hamme, Hugo

Spoken language understanding (SLU) systems can make life more agreeable, safer (e. g. in a car) or can increase the independence of physically challenged users.

Spoken Language Understanding

High Dimensional Latent Panel Quantile Regression with an Application to Asset Pricing

no code implementations4 Dec 2019 Alexandre Belloni, Mingli Chen, Oscar Hernan Madrid Padilla, Zixuan, Wang

We propose a generalization of the linear panel quantile regression model to accommodate both \textit{sparse} and \textit{dense} parts: sparse means while the number of covariates available is large, potentially only a much smaller number of them have a nonzero impact on each conditional quantile of the response variable; while the dense part is represent by a low-rank matrix that can be approximated by latent factors and their loadings.


Man-in-the-Middle Attacks against Machine Learning Classifiers via Malicious Generative Models

no code implementations14 Oct 2019 Derui, Wang, Chaoran Li, Sheng Wen, Surya Nepal, Yang Xiang

First, such attacks must acquire the outputs from the models by multiple times before actually launching attacks, which is difficult for the MitM adversary in practice.

BIG-bench Machine Learning

Improved Super-Resolution Convolution Neural Network for Large Images

no code implementations26 Jul 2019 Junyu, Wang, Rong Song

Single image super-resolution (SISR) is a very popular topic nowadays, which has both research value and practical value.

Image Super-Resolution

Future Semantic Segmentation with Convolutional LSTM

no code implementations20 Jul 2018 Seyed shahabeddin Nabavi, Mrigank Rochan, Yang, Wang

We propose a novel model that uses convolutional LSTM (ConvLSTM) to encode the spatiotemporal information of observed frames for future prediction.

Autonomous Driving Decision Making +3

Alternative Objective Functions for Deep Clustering

1 code implementation ICASSP 2018 Wang, Z.-Q.; Le Roux, J.; Hershey, J.R

The recently proposed deep clustering framework represents a significant step towards solv-ing the cocktail party problem.

Clustering Deep Clustering +1

High Dimensional Data Modeling Techniques for Detection of Chemical Plumes and Anomalies in Hyperspectral Images and Movies

no code implementations24 Sep 2015 Yi, Wang, Guangliang Chen, Mauro Maggioni

We briefly review recent progress in techniques for modeling and analyzing hyperspectral images and movies, in particular for detecting plumes of both known and unknown chemicals.

Anomaly Detection

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