Search Results for author: Peng Zhou

Found 57 papers, 21 papers with code

Unsupervised Feature Selection Algorithm Based on Dual Manifold Re-ranking

no code implementations27 Oct 2024 Yunhui Liang, Jianwen Gan, Yan Chen, Peng Zhou, Liang Du

By comparing DMRR with three original unsupervised feature selection algorithms and two unsupervised feature selection post-processing algorithms, experimental results confirm that the importance information of different samples and the dual relationship between sample and feature are beneficial for achieving better feature selection.

feature selection Re-Ranking

Hierarchical Multiple Kernel K-Means Algorithm Based on Sparse Connectivity

no code implementations27 Oct 2024 Lei Wang, Liang Du, Peng Zhou

Multiple kernel learning (MKL) aims to find an optimal, consistent kernel function.

Diversity

Multiple Kernel Clustering via Local Regression Integration

no code implementations20 Oct 2024 Liang Du, Xin Ren, Haiying Zhang, Peng Zhou

It captures the local structure of kernel data and employs kernel regression on the local region to predict the clustering results.

Clustering regression

Symmetry Nonnegative Matrix Factorization Algorithm Based on Self-paced Learning

no code implementations20 Oct 2024 Lei Wang, Liang Du, Peng Zhou, Peng Wu

A symmetric nonnegative matrix factorization algorithm based on self-paced learning was proposed to improve the clustering performance of the model.

Clustering

Y-Mol: A Multiscale Biomedical Knowledge-Guided Large Language Model for Drug Development

no code implementations15 Oct 2024 Tengfei Ma, Xuan Lin, Tianle Li, Chaoyi Li, Long Chen, Peng Zhou, Xibao Cai, Xinyu Yang, Daojian Zeng, Dongsheng Cao, Xiangxiang Zeng

Besides, Y-Mol offers a set of LLM paradigms that can autonomously execute the downstream tasks across the entire process of drug development, including virtual screening, drug design, pharmacological properties prediction, and drug-related interaction prediction.

Knowledge Graphs Language Modelling

FLIER: Few-shot Language Image Models Embedded with Latent Representations

no code implementations10 Oct 2024 Zhinuo Zhou, Peng Zhou, Xiaoyong Pan

In this paper, we propose a Few-shot Language Image model Embedded with latent Representations (FLIER) for image recognition by introducing a latent encoder jointly trained with CLIP's image encoder, it incorporates pre-trained vision-language knowledge of CLIP and the latent representations from Stable Diffusion.

Image Generation

AlignBot: Aligning VLM-powered Customized Task Planning with User Reminders Through Fine-Tuning for Household Robots

no code implementations18 Sep 2024 Zhaxizhuoma, Pengan Chen, Ziniu Wu, Jiawei Sun, Dong Wang, Peng Zhou, Nieqing Cao, Yan Ding, Bin Zhao, Xuelong Li

To validate the effectiveness of AlignBot, experiments are conducted in real-world household environments, which are constructed within the laboratory to replicate typical household settings.

Gated Slot Attention for Efficient Linear-Time Sequence Modeling

1 code implementation11 Sep 2024 Yu Zhang, Songlin Yang, Ruijie Zhu, Yue Zhang, Leyang Cui, Yiqiao Wang, Bolun Wang, Freda Shi, Bailin Wang, Wei Bi, Peng Zhou, Guohong Fu

Linear attention Transformers and their gated variants, celebrated for enabling parallel training and efficient recurrent inference, still fall short in recall-intensive tasks compared to traditional Transformers and demand significant resources for training from scratch.

Blockchain-based Federated Recommendation with Incentive Mechanism

no code implementations3 Sep 2024 Jianhai Chen, Yanlin Wu, Dazhong Rong, Guoyao Yu, Lingqi Jiang, Zhenguang Liu, Peng Zhou, Rui Shen

The experimental results show that our proposed incentive mechanism can attract clients with superior training data to engage in the federal recommendation at a lower cost, which can increase the economic benefit of federal recommendation by 54. 9\% while improve the recommendation performance.

Data Poisoning Recommendation Systems

ETGuard: Malicious Encrypted Traffic Detection in Blockchain-based Power Grid Systems

1 code implementation20 Aug 2024 Peng Zhou, Yongdong Liu, Lixun Ma, Weiye Zhang, Haohan Tan, Zhenguang Liu, Butian Huang

The escalating prevalence of encryption protocols has led to a concomitant surge in the number of malicious attacks that hide in encrypted traffic.

Incremental Learning

Scalable MatMul-free Language Modeling

1 code implementation4 Jun 2024 Rui-Jie Zhu, Yu Zhang, Ethan Sifferman, Tyler Sheaves, Yiqiao Wang, Dustin Richmond, Peng Zhou, Jason K. Eshraghian

Our experiments show that our proposed MatMul-free models achieve performance on-par with state-of-the-art Transformers that require far more memory during inference at a scale up to at least 2. 7B parameters.

Language Modelling

Puff-Net: Efficient Style Transfer with Pure Content and Style Feature Fusion Network

no code implementations CVPR 2024 Sizhe Zheng, Pan Gao, Peng Zhou, Jie Qin

In order to achieve better stylization, we design a content feature extractor and a style feature extractor, based on which pure content and style images can be fed to the transformer.

Style Transfer

Sparse Sampling is All You Need for Fast Wrong-way Cycling Detection in CCTV Videos

no code implementations12 May 2024 Jing Xu, Wentao Shi, Sheng Ren, Pan Gao, Peng Zhou, Jie Qin

In the field of transportation, it is of paramount importance to address and mitigate illegal actions committed by both motor and non-motor vehicles.

Learning to Rank Patches for Unbiased Image Redundancy Reduction

1 code implementation CVPR 2024 Yang Luo, Zhineng Chen, Peng Zhou, Zuxuan Wu, Xieping Gao, Yu-Gang Jiang

The results demonstrate that LTRP outperforms both supervised and other self-supervised methods due to the fair assessment of image content.

Image Reconstruction Inductive Bias +1

Instruction Multi-Constraint Molecular Generation Using a Teacher-Student Large Language Model

1 code implementation20 Mar 2024 Peng Zhou, Jianmin Wang, Chunyan Li, Zixu Wang, Yiping Liu, Siqi Sun, Jianxin Lin, Leyi Wei, Xibao Cai, Houtim Lai, Wei Liu, Longyue Wang, Yuansheng Liu, Xiangxiang Zeng

While various models and computational tools have been proposed for structure and property analysis of molecules, generating molecules that conform to all desired structures and properties remains a challenge.

Drug Discovery Knowledge Distillation +2

MV2MAE: Multi-View Video Masked Autoencoders

no code implementations29 Jan 2024 Ketul Shah, Robert Crandall, Jie Xu, Peng Zhou, Marian George, Mayank Bansal, Rama Chellappa

We report state-of-the-art results on the NTU-60, NTU-120 and ETRI datasets, as well as in the transfer learning setting on NUCLA, PKU-MMD-II and ROCOG-v2 datasets, demonstrating the robustness of our approach.

Action Recognition Decoder +2

Neuromorphic Intermediate Representation: A Unified Instruction Set for Interoperable Brain-Inspired Computing

1 code implementation24 Nov 2023 Jens E. Pedersen, Steven Abreu, Matthias Jobst, Gregor Lenz, Vittorio Fra, Felix C. Bauer, Dylan R. Muir, Peng Zhou, Bernhard Vogginger, Kade Heckel, Gianvito Urgese, Sadasivan Shankar, Terrence C. Stewart, Sadique Sheik, Jason K. Eshraghian

By abstracting away assumptions around discretization and hardware constraints, NIR faithfully captures the computational model, while bridging differences between the evaluated implementation and the underlying mathematical formalism.

Neuromorphic Hebbian learning with magnetic tunnel junction synapses

no code implementations21 Aug 2023 Peng Zhou, Alexander J. Edwards, Frederick B. Mancoff, Sanjeev Aggarwal, Stephen K. Heinrich-Barna, Joseph S. Friedman

Neuromorphic computing aims to mimic both the function and structure of biological neural networks to provide artificial intelligence with extreme efficiency.

Handwritten Digit Recognition

FocalDreamer: Text-driven 3D Editing via Focal-fusion Assembly

no code implementations21 Aug 2023 Yuhan Li, Yishun Dou, Yue Shi, Yu Lei, Xuanhong Chen, Yi Zhang, Peng Zhou, Bingbing Ni

While text-3D editing has made significant strides in leveraging score distillation sampling, emerging approaches still fall short in delivering separable, precise and consistent outcomes that are vital to content creation.

Fair Causal Feature Selection

no code implementations17 Jun 2023 Zhaolong Ling, Enqi Xu, Peng Zhou, Liang Du, Kui Yu, Xindong Wu

Fair feature selection for classification decision tasks has recently garnered significant attention from researchers.

Fairness feature selection

Gradient-based Neuromorphic Learning on Dynamical RRAM Arrays

no code implementations26 Jun 2022 Peng Zhou, Jason K. Eshraghian, Dong-Uk Choi, Wei D. Lu, Sung-Mo Kang

We present MEMprop, the adoption of gradient-based learning to train fully memristive spiking neural networks (MSNNs).

A Fully Memristive Spiking Neural Network with Unsupervised Learning

no code implementations2 Mar 2022 Peng Zhou, Dong-Uk Choi, Jason K. Eshraghian, Sung-Mo Kang

We present a fully memristive spiking neural network (MSNN) consisting of physically-realizable memristive neurons and memristive synapses to implement an unsupervised Spiking Time Dependent Plasticity (STDP) learning rule.

Multi-class Classification Retrieval

SPICEprop: Backpropagating Errors Through Memristive Spiking Neural Networks

no code implementations2 Mar 2022 Peng Zhou, Jason K. Eshraghian, Dong-Uk Choi, Sung-Mo Kang

The natural spiking dynamics of the MIF neuron model are fully differentiable, eliminating the need for gradient approximations that are prevalent in the spiking neural network literature.

Synchronous Unsupervised STDP Learning with Stochastic STT-MRAM Switching

no code implementations10 Dec 2021 Peng Zhou, Julie A. Smith, Laura Deremo, Stephen K. Heinrich-Barna, Joseph S. Friedman

The use of analog resistance states for storing weights in neuromorphic systems is impeded by fabrication imprecision and device stochasticity that limit the precision of synapse weights.

Experimental Demonstration of Neuromorphic Network with STT MTJ Synapses

no code implementations9 Dec 2021 Peng Zhou, Alexander J. Edwards, Fred B. Mancoff, Dimitri Houssameddine, Sanjeev Aggarwal, Joseph S. Friedman

We present the first experimental demonstration of a neuromorphic network with magnetic tunnel junction (MTJ) synapses, which performs image recognition via vector-matrix multiplication.

Handwritten Digit Recognition

Prediction of Fund Net Value Based on ARIMA-LSTM Hybrid Model

no code implementations19 Nov 2021 Peng Zhou, Fangyi Li

The net value of the fund is affected by performance and market, and the researchers try to quantify these effects to predict the future net value by establishing different models.

Improved Method of Stock Trading under Reinforcement Learning Based on DRQN and Sentiment Indicators ARBR

no code implementations19 Nov 2021 Peng Zhou, Jingling Tang

With the application of artificial intelligence in the financial field, quantitative trading is considered to be profitable.

An Improved Reinforcement Learning Model Based on Sentiment Analysis

no code implementations19 Nov 2021 Yizhuo Li, Peng Zhou, Fangyi Li, Xiao Yang

The authors combined the deep Q network in reinforcement learning with the sentiment quantitative indicator ARBR to build a high-frequency stock trading model for the share market.

reinforcement-learning Reinforcement Learning +2

CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesis

1 code implementation19 Oct 2021 Peng Zhou, Lingxi Xie, Bingbing Ni, Qi Tian

The style-based GAN (StyleGAN) architecture achieved state-of-the-art results for generating high-quality images, but it lacks explicit and precise control over camera poses.

3D-Aware Image Synthesis Transfer Learning

Deep Video Inpainting Detection

no code implementations26 Jan 2021 Peng Zhou, Ning Yu, Zuxuan Wu, Larry S. Davis, Abhinav Shrivastava, Ser-Nam Lim

This paper studies video inpainting detection, which localizes an inpainted region in a video both spatially and temporally.

Decoder Video Inpainting

Omni-GAN: On the Secrets of cGANs and Beyond

3 code implementations ICCV 2021 Peng Zhou, Lingxi Xie, Bingbing Ni, Cong Geng, Qi Tian

The conditional generative adversarial network (cGAN) is a powerful tool of generating high-quality images, but existing approaches mostly suffer unsatisfying performance or the risk of mode collapse.

Conditional Image Generation Generative Adversarial Network

Searching towards Class-Aware Generators for Conditional Generative Adversarial Networks

1 code implementation25 Jun 2020 Peng Zhou, Lingxi Xie, Xiaopeng Zhang, Bingbing Ni, Qi Tian

To learn the sampling policy, a Markov decision process is embedded into the search algorithm and a moving average is applied for better stability.

Image Generation

Inclusive GAN: Improving Data and Minority Coverage in Generative Models

1 code implementation ECCV 2020 Ning Yu, Ke Li, Peng Zhou, Jitendra Malik, Larry Davis, Mario Fritz

Generative Adversarial Networks (GANs) have brought about rapid progress towards generating photorealistic images.

DeepStrip: High Resolution Boundary Refinement

no code implementations25 Mar 2020 Peng Zhou, Brian Price, Scott Cohen, Gregg Wilensky, Larry S. Davis

In this paper, we target refining the boundaries in high resolution images given low resolution masks.

Vocal Bursts Intensity Prediction

Reservoir Computing with Planar Nanomagnet Arrays

no code implementations24 Mar 2020 Peng Zhou, Nathan R. McDonald, Alexander J. Edwards, Lisa Loomis, Clare D. Thiem, Joseph S. Friedman

Reservoir computing is an emerging methodology for neuromorphic computing that is especially well-suited for hardware implementations in size, weight, and power (SWaP) constrained environments.

Wasserstein-Bounded Generative Adversarial Networks

no code implementations ICLR 2020 Peng Zhou, Bingbing Ni, Lingxi Xie, Xiaopeng Zhang, Hang Wang, Cong Geng, Qi Tian

In the field of Generative Adversarial Networks (GANs), how to design a stable training strategy remains an open problem.

Revisiting Image Aesthetic Assessment via Self-Supervised Feature Learning

no code implementations26 Nov 2019 Kekai Sheng, Wei-Ming Dong, Menglei Chai, Guohui Wang, Peng Zhou, Feiyue Huang, Bao-Gang Hu, Rongrong Ji, Chongyang Ma

In this paper, we revisit the problem of image aesthetic assessment from the self-supervised feature learning perspective.

K-BERT: Enabling Language Representation with Knowledge Graph

2 code implementations arXiv 2019 Weijie Liu, Peng Zhou, Zhe Zhao, Zhiruo Wang, Qi Ju, Haotang Deng, Ping Wang

For machines to achieve this capability, we propose a knowledge-enabled language representation model (K-BERT) with knowledge graphs (KGs), in which triples are injected into the sentences as domain knowledge.

Knowledge Graphs Sentence

Sionnx: Automatic Unit Test Generator for ONNX Conformance

1 code implementation12 Jun 2019 Xinli Cai, Peng Zhou, Shuhan Ding, Guoyang Chen, Weifeng Zhang

Finally, through this easy-to-use specification language, we are able to build a full testing specification which leverages LLVM TableGen to automatically generate unit tests for ONNX operators with much large coverage.

M2KD: Multi-model and Multi-level Knowledge Distillation for Incremental Learning

no code implementations3 Apr 2019 Peng Zhou, Long Mai, Jianming Zhang, Ning Xu, Zuxuan Wu, Larry S. Davis

Instead of sequentially distilling knowledge only from the last model, we directly leverage all previous model snapshots.

Incremental Learning Knowledge Distillation

Generate, Segment and Refine: Towards Generic Manipulation Segmentation

1 code implementation24 Nov 2018 Peng Zhou, Bor-Chun Chen, Xintong Han, Mahyar Najibi, Abhinav Shrivastava, Ser Nam Lim, Larry S. Davis

The advent of image sharing platforms and the easy availability of advanced photo editing software have resulted in a large quantities of manipulated images being shared on the internet.

Detecting Image Manipulation Image Generation +3

Pose Transferrable Person Re-Identification

no code implementations CVPR 2018 Jinxian Liu, Bingbing Ni, Yichao Yan, Peng Zhou, Shuo Cheng, Jianguo Hu

On the other hand, in addition to the conventional discriminator of GAN (i. e., to distinguish between REAL/FAKE samples), we propose a novel guider sub-network which encourages the generated sample (i. e., with novel pose) towards better satisfying the ReID loss (i. e., cross-entropy ReID loss, triplet ReID loss).

Person Re-Identification Triplet

Learning Rich Features for Image Manipulation Detection

2 code implementations CVPR 2018 Peng Zhou, Xintong Han, Vlad I. Morariu, Larry S. Davis

Image manipulation detection is different from traditional semantic object detection because it pays more attention to tampering artifacts than to image content, which suggests that richer features need to be learned.

Image Manipulation Image Manipulation Detection +3

Text Classification Improved by Integrating Bidirectional LSTM with Two-dimensional Max Pooling

3 code implementations COLING 2016 Peng Zhou, Zhenyu Qi, Suncong Zheng, Jiaming Xu, Hongyun Bao, Bo Xu

To integrate the features on both dimensions of the matrix, this paper explores applying 2D max pooling operation to obtain a fixed-length representation of the text.

Binary Classification General Classification +2

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