Search Results for author: Qin Wang

Found 35 papers, 15 papers with code

Is Your AI Truly Yours? Leveraging Blockchain for Copyrights, Provenance, and Lineage

1 code implementation9 Apr 2024 Yilin Sai, Qin Wang, Guangsheng Yu, H. M. N. Dilum Bandara, Shiping Chen

As Artificial Intelligence (AI) integrates into diverse areas, particularly in content generation, ensuring rightful ownership and ethical use becomes paramount.

Management

From Beginner to Expert: Modeling Medical Knowledge into General LLMs

no code implementations2 Dec 2023 Qiang Li, Xiaoyan Yang, Haowen Wang, Qin Wang, Lei Liu, Junjie Wang, Yang Zhang, Mingyuan Chu, Sen Hu, Yicheng Chen, Yue Shen, Cong Fan, Wangshu Zhang, Teng Xu, Jinjie Gu, Jing Zheng, Guannan Zhang Ant Group

(3) Specifically for multi-choice questions in the medical domain, we propose a novel Verification-of-Choice approach for prompting engineering, which significantly enhances the reasoning ability of LLMs.

Language Modelling Large Language Model +3

Cryptocurrency in the Aftermath: Unveiling the Impact of the SVB Collapse

no code implementations15 Sep 2023 Qin Wang, Guangsheng Yu, Shiping Chen

We conduct a multi-dimensional investigation, which includes a factual summary, analysis of user sentiment, and examination of market performance.

DARE-GRAM : Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matrices

1 code implementation23 Mar 2023 Ismail Nejjar, Qin Wang, Olga Fink

Unsupervised Domain Adaptation Regression (DAR) aims to bridge the domain gap between a labeled source dataset and an unlabelled target dataset for regression problems.

regression Unsupervised Domain Adaptation

Blockchain-Empowered Trustworthy Data Sharing: Fundamentals, Applications, and Challenges

no code implementations12 Mar 2023 Linh T. Nguyen, Lam Duc Nguyen, Thong Hoang, Dilum Bandara, Qin Wang, Qinghua Lu, Xiwei Xu, Liming Zhu, Petar Popovski, Shiping Chen

Second, we focus on the convergence of blockchain and data sharing to give a clear picture of this landscape and propose a reference architecture for blockchain-based data sharing.

IronForge: An Open, Secure, Fair, Decentralized Federated Learning

no code implementations7 Jan 2023 Guangsheng Yu, Xu Wang, Caijun Sun, Qin Wang, Ping Yu, Wei Ni, Ren Ping Liu, Xiwei Xu

Federated learning (FL) provides an effective machine learning (ML) architecture to protect data privacy in a distributed manner.

Fairness Federated Learning

DARE-GRAM: Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matrices

1 code implementation CVPR 2023 Ismail Nejjar, Qin Wang, Olga Fink

Unsupervised Domain Adaptation Regression (DAR) aims to bridge the domain gap between a labeled source dataset and an unlabelled target dataset for regression problems.

regression Unsupervised Domain Adaptation

Continuous Pseudo-Label Rectified Domain Adaptive Semantic Segmentation With Implicit Neural Representations

no code implementations CVPR 2023 Rui Gong, Qin Wang, Martin Danelljan, Dengxin Dai, Luc van Gool

Unsupervised domain adaptation (UDA) for semantic segmentation aims at improving the model performance on the unlabeled target domain by leveraging a labeled source domain.

Pseudo Label Semantic Segmentation +1

One-Shot Domain Adaptive and Generalizable Semantic Segmentation with Class-Aware Cross-Domain Transformers

no code implementations14 Dec 2022 Rui Gong, Qin Wang, Dengxin Dai, Luc van Gool

Thus, we aim to relieve this need on a large number of real data, and explore the one-shot unsupervised sim-to-real domain adaptation (OSUDA) and generalization (OSDG) problem, where only one real-world data sample is available.

Autonomous Driving Domain Adaptation +1

Towards Interpretable Video Super-Resolution via Alternating Optimization

1 code implementation21 Jul 2022 JieZhang Cao, Jingyun Liang, Kai Zhang, Wenguan Wang, Qin Wang, Yulun Zhang, Hao Tang, Luc van Gool

These issues can be alleviated by a cascade of three separate sub-tasks, including video deblurring, frame interpolation, and super-resolution, which, however, would fail to capture the spatial and temporal correlations among video sequences.

Deblurring Space-time Video Super-resolution +2

Multi-agent Actor-Critic with Time Dynamical Opponent Model

no code implementations12 Apr 2022 Yuan Tian, Klaus-Rudolf Kladny, Qin Wang, Zhiwu Huang, Olga Fink

In this paper, we propose to exploit the fact that the agents seek to improve their expected cumulative reward and introduce a novel \textit{Time Dynamical Opponent Model} (TDOM) to encode the knowledge that the opponent policies tend to improve over time.

Multi-agent Reinforcement Learning

Continual Test-Time Domain Adaptation

2 code implementations CVPR 2022 Qin Wang, Olga Fink, Luc van Gool, Dengxin Dai

However, real-world machine perception systems are running in non-stationary and continually changing environments where the target domain distribution can change over time.

Test-time Adaptation

Revisiting Deep Semi-supervised Learning: An Empirical Distribution Alignment Framework and Its Generalization Bound

no code implementations13 Mar 2022 Feiyu Wang, Qin Wang, Wen Li, Dong Xu, Luc van Gool

Benefited from this new perspective, we first propose a new deep semi-supervised learning framework called Semi-supervised Learning by Empirical Distribution Alignment (SLEDA), in which existing technologies from the domain adaptation community can be readily used to address the semi-supervised learning problem through reducing the empirical distribution distance between labeled and unlabeled data.

Data Augmentation Domain Adaptation

Improving Semi-Supervised and Domain-Adaptive Semantic Segmentation with Self-Supervised Depth Estimation

1 code implementation28 Aug 2021 Lukas Hoyer, Dengxin Dai, Qin Wang, Yuhua Chen, Luc van Gool

Training deep networks for semantic segmentation requires large amounts of labeled training data, which presents a major challenge in practice, as labeling segmentation masks is a highly labor-intensive process.

Data Augmentation Domain Adaptation +5

Colorectal Polyp Classification from White-light Colonoscopy Images via Domain Alignment

no code implementations5 Aug 2021 Qin Wang, Hui Che, Weizhen Ding, Li Xiang, Guanbin Li, Zhen Li, Shuguang Cui

Thus, we propose a novel framework based on a teacher-student architecture for the accurate colorectal polyp classification (CPC) through directly using white-light (WL) colonoscopy images in the examination.

Contrastive Learning

Shallow Feature Matters for Weakly Supervised Object Localization

1 code implementation CVPR 2021 Jun Wei, Qin Wang, Zhen Li, Sheng Wang, S. Kevin Zhou, Shuguang Cui

In practice, our SPOL model first generates the CAMs through a novel element-wise multiplication of shallow and deep feature maps, which filters the background noise and generates sharper boundaries robustly.

Object Pseudo Label +1

Integrating Expert Knowledge with Domain Adaptation for Unsupervised Fault Diagnosis

1 code implementation5 Jul 2021 Qin Wang, Cees Taal, Olga Fink

In this paper, we aim to overcome this limitation by integrating expert knowledge with domain adaptation in a synthetic-to-real framework for unsupervised fault diagnosis.

Domain Adaptation

Both qubits of the singlet state can be steered simultaneously by multiple independent observers via sequential measurement

no code implementations24 Feb 2021 Kun Liu, Tongjun Liu, Wei Fang, Jian Li, Qin Wang

Quantum correlation is a fundamental property which distinguishes quantum systems from classical ones, and it is also a fragile resource under projective measurement.

Quantum Physics

A Weak Consensus Algorithm and Its Application to High-Performance Blockchain

no code implementations1 Feb 2021 Qin Wang, Rujia Li

We apply this consensus algorithm to construct a high-performance blockchain system, called \textit{Sphinx}.

Distributed, Parallel, and Cluster Computing

Off-Policy Reinforcement Learning for Efficient and Effective GAN Architecture Search

1 code implementation ECCV 2020 Yuan Tian, Qin Wang, Zhiwu Huang, Wen Li, Dengxin Dai, Minghao Yang, Jun Wang, Olga Fink

In this paper, we introduce a new reinforcement learning (RL) based neural architecture search (NAS) methodology for effective and efficient generative adversarial network (GAN) architecture search.

Generative Adversarial Network Image Generation +3

Potential, Challenges and Future Directions for Deep Learning in Prognostics and Health Management Applications

no code implementations5 May 2020 Olga Fink, Qin Wang, Markus Svensén, Pierre Dersin, Wan-Jui Lee, Melanie Ducoffe

Deep learning applications have been thriving over the last decade in many different domains, including computer vision and natural language understanding.

Management Natural Language Understanding

Missing-Class-Robust Domain Adaptation by Unilateral Alignment for Fault Diagnosis

3 code implementations7 Jan 2020 Qin Wang, Gabriel Michau, Olga Fink

We demonstrate in this paper that the performance of domain adversarial methods can be vulnerable to an incomplete target label space during training.

Domain Adaptation

Nanoscale Microscopy Images Colorization Using Neural Networks

1 code implementation17 Dec 2019 Israel Goytom, Qin Wang, Tianxiang Yu, Kunjie Dai, Kris Sankaran, Xinfei Zhou, Dongdong Lin

Microscopy images are powerful tools and widely used in the majority of research areas, such as biology, chemistry, physics and materials fields by various microscopies (scanning electron microscope (SEM), atomic force microscope (AFM) and the optical microscope, et al.).

Colorization Image Colorization +1

Scale- and Context-Aware Convolutional Non-intrusive Load Monitoring

no code implementations17 Nov 2019 Kunjin Chen, Yu Zhang, Qin Wang, Jun Hu, Hang Fan, Jinliang He

Non-intrusive load monitoring addresses the challenging task of decomposing the aggregate signal of a household's electricity consumption into appliance-level data without installing dedicated meters.

Management Non-Intrusive Load Monitoring

Semi-Supervised Learning by Augmented Distribution Alignment

1 code implementation ICCV 2019 Qin Wang, Wen Li, Luc van Gool

We reveal that an essential sampling bias exists in semi-supervised learning due to the limited number of labeled samples, which often leads to a considerable empirical distribution mismatch between labeled data and unlabeled data.

Domain Adaptation Semi-Supervised Image Classification

Domain Adaptive Transfer Learning for Fault Diagnosis

no code implementations15 May 2019 Qin Wang, Gabriel Michau, Olga Fink

Thanks to digitization of industrial assets in fleets, the ambitious goal of transferring fault diagnosis models fromone machine to the other has raised great interest.

Domain Adaptation Transfer Learning

Convolutional Sequence to Sequence Non-intrusive Load Monitoring

no code implementations6 Jun 2018 Kunjin Chen, Qin Wang, Ziyu He, Kunlong Chen, Jun Hu, Jinliang He

A convolutional sequence to sequence non-intrusive load monitoring model is proposed in this paper.

Non-Intrusive Load Monitoring

Short-term Load Forecasting with Deep Residual Networks

1 code implementation30 May 2018 Kunjin Chen, Kunlong Chen, Qin Wang, Ziyu He, Jun Hu, Jinliang He

We present in this paper a model for forecasting short-term power loads based on deep residual networks.

Load Forecasting

Substation Signal Matching with a Bagged Token Classifier

no code implementations13 Feb 2018 Qin Wang, Sandro Schoenborn, Yvonne-Anne Pignolet, Theo Widmer, Carsten Franke

Currently, engineers at substation service providers match customer data with the corresponding internally used signal names manually.

BIG-bench Machine Learning

ContextVP: Fully Context-Aware Video Prediction

no code implementations ECCV 2018 Wonmin Byeon, Qin Wang, Rupesh Kumar Srivastava, Petros Koumoutsakos

Video prediction models based on convolutional networks, recurrent networks, and their combinations often result in blurry predictions.

Video Prediction

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