Search Results for author: Yue Wu

Found 153 papers, 55 papers with code

Enhancing Text Authenticity: A Novel Hybrid Approach for AI-Generated Text Detection

no code implementations1 Jun 2024 Ye Zhang, Qian Leng, Mengran Zhu, Rui Ding, Yue Wu, Jintong Song, Yulu Gong

Our approach aims to address the challenges associated with detecting AI-generated text by leveraging the strengths of both traditional feature extraction methods and state-of-the-art deep learning models.

Misinformation Text Detection

DiM: Diffusion Mamba for Efficient High-Resolution Image Synthesis

1 code implementation23 May 2024 Yao Teng, Yue Wu, Han Shi, Xuefei Ning, Guohao Dai, Yu Wang, Zhenguo Li, Xihui Liu

In addition, to further improve training efficiency for high-resolution image generation with DiM, we investigate "weak-to-strong" training strategy that pretrains DiM on low-resolution images ($256\times 256$) and then finetune it on high-resolution images ($512 \times 512$).

Image Generation

Self-Play Preference Optimization for Language Model Alignment

1 code implementation1 May 2024 Yue Wu, Zhiqing Sun, Huizhuo Yuan, Kaixuan Ji, Yiming Yang, Quanquan Gu

Our method can effectively increase the log-likelihood of the chosen response and decrease that of the rejected response, which cannot be trivially achieved by symmetric pairwise loss such as Direct Preference Optimization (DPO) and Identity Preference Optimization (IPO).

Language Modelling

AgentKit: Flow Engineering with Graphs, not Coding

1 code implementation17 Apr 2024 Yue Wu, Yewen Fan, So Yeon Min, Shrimai Prabhumoye, Stephen Mcaleer, Yonatan Bisk, Ruslan Salakhutdinov, Yuanzhi Li, Tom Mitchell

The chains of nodes can be designed to explicitly enforce a naturally structured "thought process".

Automatic Controllable Colorization via Imagination

no code implementations CVPR 2024 Xiaoyan Cong, Yue Wu, Qifeng Chen, Chenyang Lei

Unlike most previous end-to-end automatic colorization algorithms, our framework allows for iterative and localized modifications of the colorization results because we explicitly model the coloring samples.

Colorization Image Generation

ROPO: Robust Preference Optimization for Large Language Models

no code implementations5 Apr 2024 Xize Liang, Chao Chen, Shuang Qiu, Jie Wang, Yue Wu, Zhihang Fu, Zhihao Shi, Feng Wu, Jieping Ye

Preference alignment is pivotal for empowering large language models (LLMs) to generate helpful and harmless responses.

Text Generation

Causal knowledge engineering: A case study from COVID-19

no code implementations21 Mar 2024 Steven Mascaro, Yue Wu, Ross Pearson, Owen Woodberry, Jessica Ramsay, Tom Snelling, Ann E. Nicholson

The unique challenges of the setting lead to experiments with the elicitation approach, and what emerged was a knowledge engineering method we call Causal Knowledge Engineering (CKE).

Protein Conformation Generation via Force-Guided SE(3) Diffusion Models

no code implementations21 Mar 2024 Yan Wang, Lihao Wang, Yuning Shen, Yiqun Wang, Huizhuo Yuan, Yue Wu, Quanquan Gu

The conformational landscape of proteins is crucial to understanding their functionality in complex biological processes.


Editing Massive Concepts in Text-to-Image Diffusion Models

1 code implementation20 Mar 2024 Tianwei Xiong, Enze Xie, Yue Wu, Zhenguo Li, Xihui Liu

We further propose a comprehensive benchmark, named ImageNet Concept Editing Benchmark (ICEB), for evaluating massive concept editing for T2I models with two subtasks, free-form prompts, massive concept categories, and extensive evaluation metrics.

Model Editing

PixArt-Σ: Weak-to-Strong Training of Diffusion Transformer for 4K Text-to-Image Generation

no code implementations7 Mar 2024 Junsong Chen, Chongjian Ge, Enze Xie, Yue Wu, Lewei Yao, Xiaozhe Ren, Zhongdao Wang, Ping Luo, Huchuan Lu, Zhenguo Li

In this paper, we introduce PixArt-\Sigma, a Diffusion Transformer model~(DiT) capable of directly generating images at 4K resolution.

4k Image Captioning +1

MiM-ISTD: Mamba-in-Mamba for Efficient Infrared Small Target Detection

1 code implementation4 Mar 2024 Tianxiang Chen, Zi Ye, Zhentao Tan, Tao Gong, Yue Wu, Qi Chu, Bin Liu, Nenghai Yu, Jieping Ye

By aggregating the visual word and visual sentence features, our MiM-ISTD can effectively explore both global and local information.


EyeGPT: Ophthalmic Assistant with Large Language Models

no code implementations29 Feb 2024 Xiaolan Chen, Ziwei Zhao, Weiyi Zhang, Pusheng Xu, Le Gao, Mingpu Xu, Yue Wu, Yinwen Li, Danli Shi, Mingguang He

Artificial intelligence (AI) has gained significant attention in healthcare consultation due to its potential to improve clinical workflow and enhance medical communication.

World Knowledge

Reliable Conflictive Multi-View Learning

1 code implementation24 Feb 2024 Cai Xu, Jiajun Si, Ziyu Guan, Wei Zhao, Yue Wu, Xiyue Gao

To solve this, we point out a new Reliable Conflictive Multi-view Learning (RCML) problem, which requires the model to provide decision results and attached reliabilities for conflictive multi-view data.


GCOF: Self-iterative Text Generation for Copywriting Using Large Language Model

no code implementations21 Feb 2024 Jianghui Zhou, Ya Gao, Jie Liu, Xuemin Zhao, Zhaohua Yang, Yue Wu, Lirong Shi

Large language models(LLM) such as ChatGPT have substantially simplified the generation of marketing copy, yet producing content satisfying domain specific requirements, such as effectively engaging customers, remains a significant challenge.

Feature Engineering Language Modelling +3

The practice of qualitative parameterisation in the development of Bayesian networks

no code implementations20 Feb 2024 Steven Mascaro, Owen Woodberry, Yue Wu, Ann E. Nicholson

Since the practice focuses on qualitative issues, despite being quantitative in nature, we call this step qualitative parameterisation and provide an outline of its role in the BN development process.

INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection

no code implementations6 Feb 2024 Chao Chen, Kai Liu, Ze Chen, Yi Gu, Yue Wu, Mingyuan Tao, Zhihang Fu, Jieping Ye

Knowledge hallucination have raised widespread concerns for the security and reliability of deployed LLMs.

Diversity Hallucination +1

Bootstrapping Audio-Visual Segmentation by Strengthening Audio Cues

no code implementations4 Feb 2024 Tianxiang Chen, Zhentao Tan, Tao Gong, Qi Chu, Yue Wu, Bin Liu, Le Lu, Jieping Ye, Nenghai Yu

This bidirectional interaction narrows the modality imbalance, facilitating more effective learning of integrated audio-visual representations.

Decoder Representation Learning

TCI-Former: Thermal Conduction-Inspired Transformer for Infrared Small Target Detection

no code implementations3 Feb 2024 Tianxiang Chen, Zhentao Tan, Qi Chu, Yue Wu, Bin Liu, Nenghai Yu

We abstract this process as the directional movement of feature map pixels to target areas through convolution, pooling and interactions with surrounding pixels, which can be analogous to the movement of thermal particles constrained by surrounding variables and particles.

MoMA: Model-based Mirror Ascent for Offline Reinforcement Learning

no code implementations21 Jan 2024 Mao Hong, Zhiyue Zhang, Yue Wu, Yanxun Xu

Model-based offline reinforcement learning methods (RL) have achieved state-of-the-art performance in many decision-making problems thanks to their sample efficiency and generalizability.

Decision Making Offline RL +1

PIXART-δ: Fast and Controllable Image Generation with Latent Consistency Models

1 code implementation10 Jan 2024 Junsong Chen, Yue Wu, Simian Luo, Enze Xie, Sayak Paul, Ping Luo, Hang Zhao, Zhenguo Li

As a state-of-the-art, open-source image generation model, PIXART-{\delta} offers a promising alternative to the Stable Diffusion family of models, contributing significantly to text-to-image synthesis.

Image Generation

Inlier Confidence Calibration for Point Cloud Registration

no code implementations CVPR 2024 Yongzhe Yuan, Yue Wu, Xiaolong Fan, Maoguo Gong, Qiguang Miao, Wenping Ma

Firstly we provide finely initial correspondences for ICC in order to generate high quality reference point cloud copy corresponding to the source point cloud.

Point Cloud Registration

Neural Gaussian Similarity Modeling for Differential Graph Structure Learning

no code implementations15 Dec 2023 Xiaolong Fan, Maoguo Gong, Yue Wu, Zedong Tang, Jieyi Liu

Graph Structure Learning (GSL) has demonstrated considerable potential in the analysis of graph-unknown non-Euclidean data across a wide range of domains.

Graph structure learning

SimAC: A Simple Anti-Customization Method for Protecting Face Privacy against Text-to-Image Synthesis of Diffusion Models

1 code implementation CVPR 2024 Feifei Wang, Zhentao Tan, Tianyi Wei, Yue Wu, Qidong Huang

Despite the success of diffusion-based customization methods on visual content creation, increasing concerns have been raised about such techniques from both privacy and political perspectives.

Denoising Image Generation

Fast Training of Diffusion Transformer with Extreme Masking for 3D Point Clouds Generation

no code implementations12 Dec 2023 Shentong Mo, Enze Xie, Yue Wu, Junsong Chen, Matthias Nießner, Zhenguo Li

Motivated by the inherent redundancy of 3D compared to 2D, we propose FastDiT-3D, a novel masked diffusion transformer tailored for efficient 3D point cloud generation, which greatly reduces training costs.

3D Generation Denoising +1

PCRDiffusion: Diffusion Probabilistic Models for Point Cloud Registration

no code implementations11 Dec 2023 Yue Wu, Yongzhe Yuan, Xiaolong Fan, Xiaoshui Huang, Maoguo Gong, Qiguang Miao

We propose a new framework that formulates point cloud registration as a denoising diffusion process from noisy transformation to object transformation.

Denoising Point Cloud Registration

M3SOT: Multi-frame, Multi-field, Multi-space 3D Single Object Tracking

2 code implementations11 Dec 2023 Jiaming Liu, Yue Wu, Maoguo Gong, Qiguang Miao, Wenping Ma, Can Qin

3D Single Object Tracking (SOT) stands a forefront task of computer vision, proving essential for applications like autonomous driving.

3D Single Object Tracking Autonomous Driving +1

Drag-A-Video: Non-rigid Video Editing with Point-based Interaction

no code implementations5 Dec 2023 Yao Teng, Enze Xie, Yue Wu, Haoyu Han, Zhenguo Li, Xihui Liu

In this paper, we propose a new diffusion-based method for interactive point-based video manipulation, called Drag-A-Video.

Denoising Point Tracking +1

Language Grounded QFormer for Efficient Vision Language Understanding

no code implementations13 Nov 2023 Moulik Choraria, Nitesh Sekhar, Yue Wu, Xu Zhang, Prateek Singhal, Lav R. Varshney

Large-scale pretraining and instruction tuning have been successful for training general-purpose language models with broad competencies.

Diversity Representation Learning

Open-Ended Instructable Embodied Agents with Memory-Augmented Large Language Models

no code implementations23 Oct 2023 Gabriel Sarch, Yue Wu, Michael J. Tarr, Katerina Fragkiadaki

Pre-trained and frozen large language models (LLMs) can effectively map simple scene rearrangement instructions to programs over a robot's visuomotor functions through appropriate few-shot example prompting.

Prompt Engineering Retrieval

Large Language Models Can Be Good Privacy Protection Learners

no code implementations3 Oct 2023 Yijia Xiao, Yiqiao Jin, Yushi Bai, Yue Wu, Xianjun Yang, Xiao Luo, Wenchao Yu, Xujiang Zhao, Yanchi Liu, Haifeng Chen, Wei Wang, Wei Cheng

To address this challenge, we introduce Privacy Protection Language Models (PPLM), a novel paradigm for fine-tuning LLMs that effectively injects domain-specific knowledge while safeguarding data privacy.

SmartPlay: A Benchmark for LLMs as Intelligent Agents

1 code implementation2 Oct 2023 Yue Wu, Xuan Tang, Tom M. Mitchell, Yuanzhi Li

We introduce SmartPlay: both a challenging benchmark and a methodology for evaluating LLMs as agents.

Variance-Aware Regret Bounds for Stochastic Contextual Dueling Bandits

no code implementations2 Oct 2023 Qiwei Di, Tao Jin, Yue Wu, Heyang Zhao, Farzad Farnoud, Quanquan Gu

Dueling bandits is a prominent framework for decision-making involving preferential feedback, a valuable feature that fits various applications involving human interaction, such as ranking, information retrieval, and recommendation systems.

Computational Efficiency Decision Making +2

PixArt-$α$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

3 code implementations30 Sep 2023 Junsong Chen, Jincheng Yu, Chongjian Ge, Lewei Yao, Enze Xie, Yue Wu, Zhongdao Wang, James Kwok, Ping Luo, Huchuan Lu, Zhenguo Li

We hope PIXART-$\alpha$ will provide new insights to the AIGC community and startups to accelerate building their own high-quality yet low-cost generative models from scratch.

Image Generation Language Modelling

AniPortraitGAN: Animatable 3D Portrait Generation from 2D Image Collections

no code implementations5 Sep 2023 Yue Wu, Sicheng Xu, Jianfeng Xiang, Fangyun Wei, Qifeng Chen, Jiaolong Yang, Xin Tong

For the new task, we base our method on the generative radiance manifold representation and equip it with learnable facial and head-shoulder deformations.

FashionNTM: Multi-turn Fashion Image Retrieval via Cascaded Memory

no code implementations ICCV 2023 Anwesan Pal, Sahil Wadhwa, Ayush Jaiswal, Xu Zhang, Yue Wu, Rakesh Chada, Pradeep Natarajan, Henrik I. Christensen

Extensive evaluation results show that our proposed method outperforms the previous state-of-the-art algorithm by 50. 5%, on Multi-turn FashionIQ -- the only existing multi-turn fashion dataset currently, in addition to having a relative improvement of 12. 6% on Multi-turn Shoes -- an extension of the single-turn Shoes dataset that we created in this work.

Image Retrieval Retrieval

Optimal battery thermal management for electric vehicles with battery degradation minimization

no code implementations6 Aug 2023 Yue Wu, Zhiwu Huang, Dongjun Li, Heng Li, Jun Peng, Daniel Stroe, Ziyou Song

A control-oriented onboard BTMS model is proposed and verified under different speed profiles and temperatures.


One-Nearest Neighborhood Guides Inlier Estimation for Unsupervised Point Cloud Registration

no code implementations26 Jul 2023 Yongzhe Yuan, Yue Wu, Maoguo Gong, Qiguang Miao, A. K. Qin

In this paper, we propose an effective inlier estimation method for unsupervised point cloud registration by capturing geometric structure consistency between the source point cloud and its corresponding reference point cloud copy.

Model Optimization Point Cloud Registration

Emotional Intelligence of Large Language Models

no code implementations18 Jul 2023 Xuena Wang, Xueting Li, Zi Yin, Yue Wu, Liu Jia

Specifically, we first developed a novel psychometric assessment focusing on Emotion Understanding (EU), a core component of EI, suitable for both humans and LLMs.

Emotional Intelligence Emotion Recognition +1

Stability Analysis Framework for Particle-based Distance GANs with Wasserstein Gradient Flow

no code implementations4 Jul 2023 Chuqi Chen, Yue Wu, Yang Xiang

In this paper, we analyze the stability of the training process of these GANs from the perspective of probability density dynamics.

Preserving Commonsense Knowledge from Pre-trained Language Models via Causal Inference

2 code implementations19 Jun 2023 Junhao Zheng, Qianli Ma, Shengjie Qiu, Yue Wu, Peitian Ma, Junlong Liu, Huawen Feng, Xichen Shang, Haibin Chen

Intriguingly, the unified objective can be seen as the sum of the vanilla fine-tuning objective, which learns new knowledge from target data, and the causal objective, which preserves old knowledge from PLMs.

Attribute Causal Inference

Exploring the Application of Large-scale Pre-trained Models on Adverse Weather Removal

no code implementations15 Jun 2023 Zhentao Tan, Yue Wu, Qiankun Liu, Qi Chu, Le Lu, Jieping Ye, Nenghai Yu

Inspired by the various successful applications of large-scale pre-trained models (e. g, CLIP), in this paper, we explore the potential benefits of them for this task through both spatial feature representation learning and semantic information embedding aspects: 1) for spatial feature representation learning, we design a Spatially-Adaptive Residual (\textbf{SAR}) Encoder to extract degraded areas adaptively.

Image Restoration Representation Learning

A Neural RDE-based model for solving path-dependent PDEs

no code implementations1 Jun 2023 Bowen Fang, Hao Ni, Yue Wu

The concept of the path-dependent partial differential equation (PPDE) was first introduced in the context of path-dependent derivatives in financial markets.

DNA-GPT: Divergent N-Gram Analysis for Training-Free Detection of GPT-Generated Text

1 code implementation27 May 2023 Xianjun Yang, Wei Cheng, Yue Wu, Linda Petzold, William Yang Wang, Haifeng Chen

However, this progress also presents a significant challenge in detecting the origin of a given text, and current research on detection methods lags behind the rapid evolution of LLMs.

NODE-ImgNet: a PDE-informed effective and robust model for image denoising

1 code implementation18 May 2023 Xinheng Xie, Yue Wu, Hao Ni, Cuiyu He

Inspired by the traditional partial differential equation (PDE) approach for image denoising, we propose a novel neural network architecture, referred as NODE-ImgNet, that combines neural ordinary differential equations (NODEs) with convolutional neural network (CNN) blocks.

Image Denoising

Multi-spectral Class Center Network for Face Manipulation Detection and Localization

1 code implementation18 May 2023 Changtao Miao, Qi Chu, Zhentao Tan, Zhenchao Jin, Tao Gong, Wanyi Zhuang, Yue Wu, Bin Liu, Honggang Hu, Nenghai Yu

To this end, a novel Multi-Spectral Class Center Network (MSCCNet) is proposed for face manipulation detection and localization.

Face Swapping

Uniform-PAC Guarantees for Model-Based RL with Bounded Eluder Dimension

no code implementations15 May 2023 Yue Wu, Jiafan He, Quanquan Gu

Recently, there has been remarkable progress in reinforcement learning (RL) with general function approximation.

Open-Ended Question Answering Reinforcement Learning (RL)

Personalized Federated Learning under Mixture of Distributions

1 code implementation1 May 2023 Yue Wu, Shuaicheng Zhang, Wenchao Yu, Yanchi Liu, Quanquan Gu, Dawei Zhou, Haifeng Chen, Wei Cheng

The recent trend towards Personalized Federated Learning (PFL) has garnered significant attention as it allows for the training of models that are tailored to each client while maintaining data privacy.

Personalized Federated Learning Uncertainty Quantification

Score-based Transport Modeling for Mean-Field Fokker-Planck Equations

no code implementations21 Apr 2023 Jianfeng Lu, Yue Wu, Yang Xiang

We use the score-based transport modeling method to solve the mean-field Fokker-Planck equations, which we call MSBTM.

Elastic Interaction Energy-Based Generative Model: Approximation in Feature Space

no code implementations19 Mar 2023 Chuqi Chen, Yue Wu, Yang Xiang

We adopt the GAN framework and replace the discriminator with a feature transformation network to map the data into a latent space.

Borda Regret Minimization for Generalized Linear Dueling Bandits

no code implementations15 Mar 2023 Yue Wu, Tao Jin, Hao Lou, Farzad Farnoud, Quanquan Gu

To attain this lower bound, we propose an explore-then-commit type algorithm for the stochastic setting, which has a nearly matching regret upper bound $\tilde{O}(d^{2/3} T^{2/3})$.

Recommendation Systems

Video Waterdrop Removal via Spatio-Temporal Fusion in Driving Scenes

1 code implementation12 Feb 2023 Qiang Wen, Yue Wu, Qifeng Chen

The waterdrops on windshields during driving can cause severe visual obstructions, which may lead to car accidents.

Autonomous Driving

Avoiding spurious correlations via logit correction

1 code implementation2 Dec 2022 Sheng Liu, Xu Zhang, Nitesh Sekhar, Yue Wu, Prateek Singhal, Carlos Fernandez-Granda

Empirical studies suggest that machine learning models trained with empirical risk minimization (ERM) often rely on attributes that may be spuriously correlated with the class labels.


How to Describe Images in a More Funny Way? Towards a Modular Approach to Cross-Modal Sarcasm Generation

no code implementations20 Nov 2022 Jie Ruan, Yue Wu, Xiaojun Wan, Yuesheng Zhu

Sarcasm generation has been investigated in previous studies by considering it as a text-to-text generation problem, i. e., generating a sarcastic sentence for an input sentence.

Descriptive Sentence +1

Bayesian Layer Graph Convolutioanl Network for Hyperspetral Image Classification

no code implementations14 Nov 2022 Mingyang Zhang, Ziqi Di, Maoguo Gong, Yue Wu, Hao Li, Xiangming Jiang

In recent years, research on hyperspectral image (HSI) classification has continuous progress on introducing deep network models, and recently the graph convolutional network (GCN) based models have shown impressive performance.

Classification Generative Adversarial Network +1

Sybil-Proof Diffusion Auction in Social Networks

no code implementations3 Nov 2022 Hongyin Chen, Xiaotie Deng, Ying Wang, Yue Wu, Dengji Zhao

A diffusion auction is a market to sell commodities over a social network, where the challenge is to incentivize existing buyers to invite their neighbors in the network to join the market.

AniFaceGAN: Animatable 3D-Aware Face Image Generation for Video Avatars

1 code implementation12 Oct 2022 Yue Wu, Yu Deng, Jiaolong Yang, Fangyun Wei, Qifeng Chen, Xin Tong

To achieve meaningful control over facial expressions via deformation, we propose a 3D-level imitative learning scheme between the generator and a parametric 3D face model during adversarial training of the 3D-aware GAN.

Disentanglement Face Model +1

Towards Consistency and Complementarity: A Multiview Graph Information Bottleneck Approach

1 code implementation11 Oct 2022 Xiaolong Fan, Maoguo Gong, Yue Wu, Mingyang Zhang, Hao Li, Xiangming Jiang

In this paper, we propose a novel Multiview Variational Graph Information Bottleneck (MVGIB) principle to maximize the agreement for common representations and the disagreement for view-specific representations.

Towards Understanding Mixture of Experts in Deep Learning

2 code implementations4 Aug 2022 Zixiang Chen, Yihe Deng, Yue Wu, Quanquan Gu, Yuanzhi Li

To our knowledge, this is the first result towards formally understanding the mechanism of the MoE layer for deep learning.

Graph Generative Model for Benchmarking Graph Neural Networks

1 code implementation10 Jul 2022 Minji Yoon, Yue Wu, John Palowitch, Bryan Perozzi, Ruslan Salakhutdinov

As the field of Graph Neural Networks (GNN) continues to grow, it experiences a corresponding increase in the need for large, real-world datasets to train and test new GNN models on challenging, realistic problems.

Benchmarking Graph Generation +1

Optimizing Video Prediction via Video Frame Interpolation

1 code implementation CVPR 2022 Yue Wu, Qiang Wen, Qifeng Chen

Extensive experiments on the Cityscapes, KITTI, DAVIS, Middlebury, and Vimeo90K datasets show that our video prediction results are robust in general scenarios, and our approach outperforms other video prediction methods that require a large amount of training data or extra semantic information.

Open-Ended Question Answering Video Frame Interpolation +1

Geometric Policy Iteration for Markov Decision Processes

no code implementations12 Jun 2022 Yue Wu, Jesús A. De Loera

GPI updates the policy of a single state by switching to an action that is mapped to the boundary of the value function polytope, followed by an immediate update of the value function.

Computational Efficiency

Prompt-aligned Gradient for Prompt Tuning

1 code implementation ICCV 2023 Beier Zhu, Yulei Niu, Yucheng Han, Yue Wu, Hanwang Zhang

Thanks to the large pre-trained vision-language models (VLMs) like CLIP, we can craft a zero-shot classifier by "prompt", e. g., the confidence score of an image being "[CLASS]" can be obtained by using the VLM provided similarity measure between the image and the prompt sentence "a photo of a [CLASS]".

Domain Adaptation Few-Shot Learning +2

Real-time Online Multi-Object Tracking in Compressed Domain

no code implementations5 Apr 2022 Qiankun Liu, Bin Liu, Yue Wu, Weihai Li, Nenghai Yu

Recent online Multi-Object Tracking (MOT) methods have achieved desirable tracking performance.

Multi-Object Tracking Object +1

The China Trade Shock and the ESG Performances of US firms

no code implementations28 Jan 2022 Hui Xu, Yue Wu

Exploiting a trade policy in which US congress granted China the Permanent Normal Trade Relations and the resulting change in expected tariff rates on Chinese imports, we find that greater import competition from China leads to an increase in the US company's ESG performance.

FashionVLP: Vision Language Transformer for Fashion Retrieval With Feedback

no code implementations CVPR 2022 Sonam Goenka, Zhaoheng Zheng, Ayush Jaiswal, Rakesh Chada, Yue Wu, Varsha Hedau, Pradeep Natarajan

Fashion image retrieval based on a query pair of reference image and natural language feedback is a challenging task that requires models to assess fashion related information from visual and textual modalities simultaneously.

Image Retrieval Retrieval

Unsupervised cross domain learning with applications to 7 layer segmentation of OCTs

no code implementations23 Nov 2021 Yue Wu, Abraham Olvera Barrios, Ryan Yanagihara, Irene Leung, Marian Blazes, Adnan Tufail, Aaron Lee

Unsupervised cross domain adaptation for OCT 7 layer segmentation and other medical applications where labeled training data is only available in a source domain and unavailable in the target domain.

Domain Adaptation

ADDS: Adaptive Differentiable Sampling for Robust Multi-Party Learning

no code implementations29 Oct 2021 Maoguo Gong, Yuan Gao, Yue Wu, A. K. Qin

Inspired by the idea of dropout in neural networks, we introduce a network sampling strategy in the multi-party setting, which distributes different subnets of the central model to clients for updating, and the differentiable sampling rates allow each client to extract optimal local architecture from the supernet according to its private data distribution.

Adaptive Sampling for Heterogeneous Rank Aggregation from Noisy Pairwise Comparisons

no code implementations8 Oct 2021 Yue Wu, Tao Jin, Hao Lou, Pan Xu, Farzad Farnoud, Quanquan Gu

In heterogeneous rank aggregation problems, users often exhibit various accuracy levels when comparing pairs of items.

Causal Triple Attention Time Series Forecasting

no code implementations29 Sep 2021 Zhixuan Chu, Tan Yan, Yue Wu, Yi Xu, Cheng Zhang, Yulin kang

Time series forecasting has historically been a key area of academic research and industrial applications.

Causal Inference Time Series +1

Embedding Novel Views in a Single JPEG Image

1 code implementation ICCV 2021 Yue Wu, Guotao Meng, Qifeng Chen

We propose a novel approach for embedding novel views in a single JPEG image while preserving the perceptual fidelity of the modified JPEG image and the restored novel views.

Novel View Synthesis

Towards Photorealistic Colorization by Imagination

no code implementations20 Aug 2021 Chenyang Lei, Yue Wu, Qifeng Chen

We present a novel approach to automatic image colorization by imitating the imagination process of human experts.

Colorization Image Colorization +1

Demonstration-Guided Reinforcement Learning with Learned Skills

no code implementations ICLR Workshop SSL-RL 2021 Karl Pertsch, Youngwoon Lee, Yue Wu, Joseph J. Lim

Prior approaches for demonstration-guided RL treat every new task as an independent learning problem and attempt to follow the provided demonstrations step-by-step, akin to a human trying to imitate a completely unseen behavior by following the demonstrator's exact muscle movements.

reinforcement-learning Reinforcement Learning (RL) +1

Video Super-Resolution with Long-Term Self-Exemplars

no code implementations24 Jun 2021 Guotao Meng, Yue Wu, Sijin Li, Qifeng Chen

Existing video super-resolution methods often utilize a few neighboring frames to generate a higher-resolution image for each frame.

Video Super-Resolution

SKFAC: Training Neural Networks With Faster Kronecker-Factored Approximate Curvature

1 code implementation CVPR 2021 Zedong Tang, Fenlong Jiang, Maoguo Gong, Hao Li, Yue Wu, Fan Yu, Zidong Wang, Min Wang

For the fully connected layers, by utilizing the low-rank property of Kronecker factors of Fisher information matrix, our method only requires inverting a small matrix to approximate the curvature with desirable accuracy.

Dimensionality Reduction

Feature Flow Regularization: Improving Structured Sparsity in Deep Neural Networks

no code implementations5 Jun 2021 Yue Wu, Yuan Lan, Luchan Zhang, Yang Xiang

Pruning is a model compression method that removes redundant parameters in deep neural networks (DNNs) while maintaining accuracy.

Model Compression

SKFAC:Training Neural Networks with Faster Kronecker-Factored Approximate Curvature

1 code implementation Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2021 Zedong Tang, Fenlong Jiang, Maoguo Gong, Hao Li, Yue Wu, Fan Yu, Zidong Wang, Min Wang

For the fully connected layers, by utilizing the low-rank property of Kronecker factors of Fisher information matrix, our method only requires inverting a small matrix to approximate the curvature with desirable accuracy.

Dimensionality Reduction

CRT-Net: A Generalized and Scalable Framework for the Computer-Aided Diagnosis of Electrocardiogram Signals

no code implementations28 May 2021 Jingyi Liu, Zhongyu Li, Xiayue Fan, Jintao Yan, Bolin Li, Xuemeng Hu, Qing Xia, Yue Wu

Subsequently, a novel deep neural network, namely CRT-Net, is designed for the fine-grained and comprehensive representation and recognition of 1-D ECG signals.

LineCounter: Learning Handwritten Text Line Segmentation by Counting

1 code implementation24 May 2021 Deng Li, Yue Wu, Yicong Zhou

In this paper, we propose a novel Line Counting formulation for HTLS -- that involves counting the number of text lines from the top at every pixel location.

Handwritten Text Recognition object-detection +3

Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning

2 code implementations17 May 2021 Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh

Offline Reinforcement Learning promises to learn effective policies from previously-collected, static datasets without the need for exploration.

Offline RL Q-Learning +2

Maximizing Mutual Information Across Feature and Topology Views for Learning Graph Representations

1 code implementation14 May 2021 Xiaolong Fan, Maoguo Gong, Yue Wu, Hao Li

Specifically, we first utilize a multi-view representation learning module to better capture both local and global information content across feature and topology views on graphs.

Diversity Graph Representation Learning +1

SauvolaNet: Learning Adaptive Sauvola Network for Degraded Document Binarization

1 code implementation12 May 2021 Deng Li, Yue Wu, Yicong Zhou

The AST module further consolidates the outputs from MWS and PWA and predicts the final adaptive threshold for each pixel location.


Spatially Self-Paced Convolutional Networks for Change Detection in Heterogeneous Images

no code implementations IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021 Hao Li, Maoguo Gong, Mingyang Zhang, Yue Wu

Change detection in heterogeneous remote sensing images is a challenging problem because it is hard to make a direct comparison in the original observation spaces, and most methods rely on a set of manually labeled samples.

Change Detection

Style-Aware Normalized Loss for Improving Arbitrary Style Transfer

1 code implementation CVPR 2021 Jiaxin Cheng, Ayush Jaiswal, Yue Wu, Pradeep Natarajan, Prem Natarajan

Neural Style Transfer (NST) has quickly evolved from single-style to infinite-style models, also known as Arbitrary Style Transfer (AST).

Style Transfer

Modelling Paralinguistic Properties in Conversational Speech to Detect Bipolar Disorder and Borderline Personality Disorder

no code implementations18 Feb 2021 Bo wang, Yue Wu, Nemanja Vaci, Maria Liakata, Terry Lyons, Kate E A Saunders

Bipolar disorder (BD) and borderline personality disorder (BPD) are two chronic mental health conditions that clinicians find challenging to distinguish based on clinical interviews, due to their overlapping symptoms.

Nearly Minimax Optimal Regret for Learning Infinite-horizon Average-reward MDPs with Linear Function Approximation

no code implementations15 Feb 2021 Yue Wu, Dongruo Zhou, Quanquan Gu

We study reinforcement learning in an infinite-horizon average-reward setting with linear function approximation, where the transition probability function of the underlying Markov Decision Process (MDP) admits a linear form over a feature mapping of the current state, action, and next state.

VideoFlow: A Framework for Building Visual Analysis Pipelines

no code implementations1 Jan 2021 Yue Wu, Jianqiang Huang, Jiangjie Zhen, Guokun Wang, Chen Shen, Chang Zhou, Xian-Sheng Hua

The past years have witnessed an explosion of deep learning frameworks like PyTorch and TensorFlow since the success of deep neural networks.

Uncertainty Weighted Offline Reinforcement Learning

no code implementations1 Jan 2021 Yue Wu, Shuangfei Zhai, Nitish Srivastava, Joshua M. Susskind, Jian Zhang, Ruslan Salakhutdinov, Hanlin Goh

Offline Reinforcement Learning promises to learn effective policies from previously-collected, static datasets without the need for exploration.

Offline RL Q-Learning +2

A Finite-Time Analysis of Two Time-Scale Actor-Critic Methods

no code implementations NeurIPS 2020 Yue Wu, Weitong Zhang, Pan Xu, Quanquan Gu

In this work, we provide a non-asymptotic analysis for two time-scale actor-critic methods under non-i. i. d.

Vocal Bursts Valence Prediction

Class-agnostic Object Detection

no code implementations28 Nov 2020 Ayush Jaiswal, Yue Wu, Pradeep Natarajan, Premkumar Natarajan

Finally, we propose (1) baseline methods and (2) a new adversarial learning framework for class-agnostic detection that forces the model to exclude class-specific information from features used for predictions.

Ranked #100 on Image Classification on ObjectNet (using extra training data)

Benchmarking Class-agnostic Object Detection +5

Claw U-Net: A Unet-based Network with Deep Feature Concatenation for Scleral Blood Vessel Segmentation

no code implementations20 Oct 2020 Chang Yao, Jingyu Tang, Menghan Hu, Yue Wu, Wenyi Guo, Qingli Li, Xiao-Ping Zhang

Sturge-Weber syndrome (SWS) is a vascular malformation disease, and it may cause blindness if the patient's condition is severe.


1 code implementation11 Aug 2020 Gang Chen, Yi Ding, Hugo Edwards, Chong Hin Chau, Sai Hou, Grace Johnson, Mohammed Sharukh Syed, Haoyuan Tang, Yue Wu, Ye Yan, Gil Tidhar, Nir Lipovetzky

Planimation is a modular and extensible open source framework to visualise sequential solutions of planning problems specified in PDDL.

Improving GAN Training with Probability Ratio Clipping and Sample Reweighting

1 code implementation NeurIPS 2020 Yue Wu, Pan Zhou, Andrew Gordon Wilson, Eric P. Xing, Zhiting Hu

Despite success on a wide range of problems related to vision, generative adversarial networks (GANs) often suffer from inferior performance due to unstable training, especially for text generation.

Image Generation Style Transfer +1

Self-supervised Learning from a Multi-view Perspective

1 code implementation ICLR 2021 Yao-Hung Hubert Tsai, Yue Wu, Ruslan Salakhutdinov, Louis-Philippe Morency

In particular, we propose a composite objective that bridges the gap between prior contrastive and predictive learning objectives, and introduce an additional objective term to discard task-irrelevant information.

Image Captioning Language Modelling +4

A Finite Time Analysis of Two Time-Scale Actor Critic Methods

no code implementations4 May 2020 Yue Wu, Weitong Zhang, Pan Xu, Quanquan Gu

In this work, we provide a non-asymptotic analysis for two time-scale actor-critic methods under non-i. i. d.

Vocal Bursts Valence Prediction

Signature features with the visibility transformation

no code implementations8 Apr 2020 Yue Wu, Hao Ni, Terence J. Lyons, Robin L. Hudson

In this paper we put the visibility transformation on a clear theoretical footing and show that this transform is able to embed the effect of the absolute position of the data stream into signature features in a unified and efficient way.


Future Video Synthesis with Object Motion Prediction

1 code implementation CVPR 2020 Yue Wu, Rongrong Gao, Jaesik Park, Qifeng Chen

We present an approach to predict future video frames given a sequence of continuous video frames in the past.

Ranked #2 on Video Prediction on Cityscapes (using extra training data)

motion prediction Object +1

Game Theoretic Consequences of Resident Matching

no code implementations12 Mar 2020 Yue Wu

The resident matching algorithm, Gale-Shapley, currently used by SF Match and the National Residency Match Program (NRMP), has been in use for over 50 years without fundamental alteration.

Cross-modality Person re-identification with Shared-Specific Feature Transfer

no code implementations CVPR 2020 Yan Lu, Yue Wu, Bin Liu, Tianzhu Zhang, Baopu Li, Qi Chu, Nenghai Yu

In this paper, we tackle the above limitation by proposing a novel cross-modality shared-specific feature transfer algorithm (termed cm-SSFT) to explore the potential of both the modality-shared information and the modality-specific characteristics to boost the re-identification performance.

Cross-Modality Person Re-identification Person Re-Identification

Towards Understanding the Spectral Bias of Deep Learning

no code implementations3 Dec 2019 Yuan Cao, Zhiying Fang, Yue Wu, Ding-Xuan Zhou, Quanquan Gu

An intriguing phenomenon observed during training neural networks is the spectral bias, which states that neural networks are biased towards learning less complex functions.

Coverage-based Outlier Explanation

no code implementations6 Nov 2019 Yue Wu, Leman Akoglu, Ian Davidson

Existing algorithms are primarily focused on detection, that is the identification of outliers in a given dataset.

Outlier Detection

ManTra-Net: Manipulation Tracing Network for Detection and Localization of Image Forgeries With Anomalous Features

3 code implementations CVPR 2019 Yue Wu, Wael AbdAlmageed, Premkumar Natarajan

To fight against real-life image forgery, which commonly involves different types and combined manipulations, we propose a unified deep neural architecture called ManTra-Net.

Fake Image Detection Image Forensics +3

Large Scale Incremental Learning

4 code implementations CVPR 2019 Yue Wu, Yinpeng Chen, Lijuan Wang, Yuancheng Ye, Zicheng Liu, Yandong Guo, Yun Fu

We believe this is because of the combination of two factors: (a) the data imbalance between the old and new classes, and (b) the increasing number of visually similar classes.

Class Incremental Learning Incremental Learning

Spatially Constrained GAN for Face and Fashion Synthesis

1 code implementation7 May 2019 Songyao Jiang, Hongfu Liu, Yue Wu, Yun Fu

Besides, a segmentor network is constructed to impose spatial constraints on the generator.

Attribute Conditional Image Generation +3

Unified Adversarial Invariance

no code implementations7 May 2019 Ayush Jaiswal, Yue Wu, Wael Abd-Almageed, Premkumar Natarajan

We present a unified invariance framework for supervised neural networks that can induce independence to nuisance factors of data without using any nuisance annotations, but can additionally use labeled information about biasing factors to force their removal from the latent embedding for making fair predictions.

Disentanglement Fairness

Rethinking Classification and Localization for Object Detection

2 code implementations CVPR 2020 Yue Wu, Yinpeng Chen, Lu Yuan, Zicheng Liu, Lijuan Wang, Hongzhi Li, Yun Fu

Two head structures (i. e. fully connected head and convolution head) have been widely used in R-CNN based detectors for classification and localization tasks.

Classification General Classification +3

QATM: Quality-Aware Template Matching For Deep Learning

2 code implementations CVPR 2019 Jiaxin Cheng, Yue Wu, Wael Abd-Almageed, Premkumar Natarajan

Finding a template in a search image is one of the core problems many computer vision, such as semantic image semantic, image-to-GPS verification \etc.

Image-To-Gps Verification Template Matching

AIRD: Adversarial Learning Framework for Image Repurposing Detection

1 code implementation CVPR 2019 Ayush Jaiswal, Yue Wu, Wael Abd-Almageed, Iacopo Masi, Premkumar Natarajan

Image repurposing is a commonly used method for spreading misinformation on social media and online forums, which involves publishing untampered images with modified metadata to create rumors and further propaganda.


Image-to-GPS Verification Through A Bottom-Up Pattern Matching Network

no code implementations18 Nov 2018 Jiaxin Cheng, Yue Wu, Wael Abd-Almageed, Prem Natarajan

The image-to-GPS verification problem asks whether a given image is taken at a claimed GPS location.

Image-To-Gps Verification

Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation

1 code implementation NeurIPS 2018 Liwei Wang, Lunjia Hu, Jiayuan Gu, Yue Wu, Zhiqiang Hu, Kun He, John Hopcroft

The theory gives a complete characterization of the structure of neuron activation subspace matches, where the core concepts are maximum match and simple match which describe the overall and the finest similarity between sets of neurons in two networks respectively.

Unsupervised Adversarial Invariance

no code implementations NeurIPS 2018 Ayush Jaiswal, Yue Wu, Wael Abd-Almageed, Premkumar Natarajan

Data representations that contain all the information about target variables but are invariant to nuisance factors benefit supervised learning algorithms by preventing them from learning associations between these factors and the targets, thus reducing overfitting.

Data Augmentation Disentanglement +3

VelocityGAN: Data-Driven Full-Waveform Inversion Using Conditional Adversarial Networks

1 code implementation26 Sep 2018 Zhongping Zhang, Yue Wu, Zheng Zhou, Youzuo Lin

Acoustic- and elastic-waveform inversion is an important and widely used method to reconstruct subsurface velocity image.

BusterNet: Detecting Copy-Move Image Forgery with Source/Target Localization

1 code implementation ECCV 2018 Yue Wu, Wael Abd-Almageed, Prem Natarajan

We introduce a novel deep neural architecture for image copy-move forgery detection (CMFD), code-named BusterNet.

Deep Multimodal Image-Repurposing Detection

1 code implementation20 Aug 2018 Ekraam Sabir, Wael Abd-Almageed, Yue Wu, Prem Natarajan

Nefarious actors on social media and other platforms often spread rumors and falsehoods through images whose metadata (e. g., captions) have been modified to provide visual substantiation of the rumor/falsehood.

Predictive Local Smoothness for Stochastic Gradient Methods

no code implementations ICLR 2019 Jun Li, Hongfu Liu, Bineng Zhong, Yue Wu, Yun Fu

To address this problem, we propose a simple yet effective method for improving stochastic gradient methods named predictive local smoothness (PLS).

Facial Landmark Detection: a Literature Survey

no code implementations15 May 2018 Yue Wu, Qiang Ji

The regression-based methods implicitly capture facial shape and appearance information.

Facial Landmark Detection regression

Machine Learning for Exam Triage

1 code implementation30 Apr 2018 Xinyu Guan, Jessica Lee, Peter Wu, Yue Wu

In this project, we extend the state-of-the-art CheXNet (Rajpurkar et al. [2017]) by making use of the additional non-image features in the dataset.

BIG-bench Machine Learning

Forecasting Future Humphrey Visual Fields Using Deep Learning

2 code implementations2 Apr 2018 Joanne C. Wen, Cecilia S. Lee, Pearse A. Keane, Sa Xiao, Yue Wu, Ariel Rokem, Philip P. Chen, Aaron Y. Lee

Methods: All datapoints from consecutive 24-2 HVFs from 1998 to 2018 were extracted from a University of Washington database.

Transfer Learning

Generating retinal flow maps from structural optical coherence tomography with artificial intelligence

no code implementations24 Feb 2018 Cecilia S. Lee, Ariel J. Tyring, Yue Wu, Sa Xiao, Ariel S. Rokem, Nicolaas P. Deruyter, Qinqin Zhang, Adnan Tufail, Ruikang K. Wang, Aaron Y. Lee

Despite significant advances in artificial intelligence (AI) for computer vision, its application in medical imaging has been limited by the burden and limits of expert-generated labels.

CapsuleGAN: Generative Adversarial Capsule Network

1 code implementation17 Feb 2018 Ayush Jaiswal, Wael Abd-Almageed, Yue Wu, Premkumar Natarajan

We provide guidelines for designing CapsNet discriminators and the updated GAN objective function, which incorporates the CapsNet margin loss, for training CapsuleGAN models.

General Classification Generative Adversarial Network +1

Incremental Classifier Learning with Generative Adversarial Networks

no code implementations2 Feb 2018 Yue Wu, Yinpeng Chen, Lijuan Wang, Yuancheng Ye, Zicheng Liu, Yandong Guo, Zhengyou Zhang, Yun Fu

To address these problems, we propose (a) a new loss function to combine the cross-entropy loss and distillation loss, (b) a simple way to estimate and remove the unbalance between the old and new classes , and (c) using Generative Adversarial Networks (GANs) to generate historical data and select representative exemplars during generation.

General Classification

MRI Tumor Segmentation with Densely Connected 3D CNN

3 code implementations18 Jan 2018 Lele Chen, Yue Wu, Adora M. DSouza, Anas Z. Abidin, Axel Wismuller, Chenliang Xu

The major difficulty of our segmentation model comes with the fact that the location, structure, and shape of gliomas vary significantly among different patients.

Tumor Segmentation

Seismic-Net: A Deep Densely Connected Neural Network to Detect Seismic Events

no code implementations17 Jan 2018 Yue Wu, Youzuo Lin, Zheng Zhou, Andrew Delorey

In particular, we demonstrate the efficacy of our Seismic-Net by formulating our detection problem as an event detection problem with time series data.

Event Detection Time Series +1

Clustering with Outlier Removal

no code implementations5 Jan 2018 Hongfu Liu, Jun Li, Yue Wu, Yun Fu

Then an objective function based Holoentropy is designed to enhance the compactness of each cluster with a few outliers removed.

Clustering Outlier Detection

Bidirectional Conditional Generative Adversarial Networks

no code implementations20 Nov 2017 Ayush Jaiswal, Wael Abd-Almageed, Yue Wu, Premkumar Natarajan

Conditional Generative Adversarial Networks (cGANs) are generative models that can produce data samples ($x$) conditioned on both latent variables ($z$) and known auxiliary information ($c$).

Constrained Deep Transfer Feature Learning and its Applications

no code implementations CVPR 2016 Yue Wu, Qiang Ji

Furthermore, we propose to exploit the target domain knowledge and incorporate such prior knowledge as a constraint during transfer learning to ensure that the transferred data satisfies certain properties of the target domain.

Facial Expression Recognition Facial Expression Recognition (FER) +1

Robust Facial Landmark Detection under Significant Head Poses and Occlusion

no code implementations ICCV 2015 Yue Wu, Qiang Ji

In this work, we propose a unified robust cascade regression framework that can handle both images with severe occlusion and images with large head poses.

Facial Landmark Detection Occlusion Estimation +1

Constrained Joint Cascade Regression Framework for Simultaneous Facial Action Unit Recognition and Facial Landmark Detection

no code implementations CVPR 2016 Yue Wu, Qiang Ji

Experimental results demonstrate that the intertwined relationships of facial action units and face shapes boost the performances of both facial action unit recognition and facial landmark detection.

Facial Action Unit Detection Facial Landmark Detection +1

Simultaneous Facial Landmark Detection, Pose and Deformation Estimation under Facial Occlusion

no code implementations CVPR 2017 Yue Wu, Chao Gou, Qiang Ji

Facial landmark detection, head pose estimation, and facial deformation analysis are typical facial behavior analysis tasks in computer vision.

Facial Landmark Detection Head Pose Estimation

A Hierarchical Probabilistic Model for Facial Feature Detection

no code implementations CVPR 2014 Yue Wu, Ziheng Wang, Qiang Ji

Facial feature detection from facial images has attracted great attention in the field of computer vision.

Facial Feature Tracking under Varying Facial Expressions and Face Poses based on Restricted Boltzmann Machines

no code implementations CVPR 2013 Yue Wu, Zuoguan Wang, Qiang Ji

To handle pose variations, the frontal face shape prior model is incorporated into a 3-way RBM model that could capture the relationship between frontal face shapes and non-frontal face shapes.

Cascaded Region-based Densely Connected Network for Event Detection: A Seismic Application

no code implementations12 Sep 2017 Yue Wu, Youzuo Lin, Zheng Zhou, David Chas Bolton, Ji Liu, Paul Johnson

Because of the fact that some positive events are not correctly annotated, we further formulate the detection problem as a learning-from-noise problem.

Abnormal Event Detection In Video Event Detection +4

Deep Matching and Validation Network -- An End-to-End Solution to Constrained Image Splicing Localization and Detection

no code implementations27 May 2017 Yue Wu, Wael Abd-Almageed, Prem Natarajan

Here the task is to estimate the probability that the donor image has been used to splice the query image, and obtain the splicing masks for both the query and donor images.

Image Manipulation

SOL: A Library for Scalable Online Learning Algorithms

1 code implementation28 Oct 2016 Yue Wu, Steven C. H. Hoi, Chenghao Liu, Jing Lu, Doyen Sahoo, Nenghai Yu

SOL is an open-source library for scalable online learning algorithms, and is particularly suitable for learning with high-dimensional data.

BIG-bench Machine Learning General Classification +1

Families in the Wild (FIW): Large-Scale Kinship Image Database and Benchmarks

no code implementations7 Apr 2016 Joseph P. Robinson, Ming Shao, Yue Wu, Yun Fu

Motivated by the lack of a single, unified dataset for kinship recognition, we aim to provide a dataset that captivates the interest of the research community.

Kinship Verification Metric Learning

Relaxing From Vocabulary: Robust Weakly-Supervised Deep Learning for Vocabulary-Free Image Tagging

no code implementations ICCV 2015 Jianlong Fu, Yue Wu, Tao Mei, Jinqiao Wang, Hanqing Lu, Yong Rui

The development of deep learning has empowered machines with comparable capability of recognizing limited image categories to human beings.

LOGO-Net: Large-scale Deep Logo Detection and Brand Recognition with Deep Region-based Convolutional Networks

no code implementations8 Nov 2015 Steven C. H. Hoi, Xiongwei Wu, Hantang Liu, Yue Wu, Huiqiong Wang, Hui Xue, Qiang Wu

In this paper, we introduce "LOGO-Net", a large-scale logo image database for logo detection and brand recognition from real-world product images.

Logo Recognition object-detection +1

Learning Document Image Binarization from Data

no code implementations4 May 2015 Yue Wu, Stephen Rawls, Wael Abd-Almageed, Premkumar Natarajan

In this paper we present a fully trainable binarization solution for degraded document images.


Large-scale Online Feature Selection for Ultra-high Dimensional Sparse Data

no code implementations27 Sep 2014 Yue Wu, Steven C. H. Hoi, Tao Mei, Nenghai Yu

However, unlike many second-order learning methods that often suffer from extra high computational cost, we devise a novel smart algorithm for second-order online feature selection using a MaxHeap-based approach, which is not only more effective than the existing first-order approaches, but also significantly more efficient and scalable for large-scale feature selection with ultra-high dimensional sparse data, as validated from our extensive experiments.

feature selection Vocal Bursts Intensity Prediction

Gaussian Process Volatility Model

no code implementations NeurIPS 2014 Yue Wu, Jose Miguel Hernandez Lobato, Zoubin Ghahramani

A Gaussian Process (GP) defines a distribution over functions, which allows us to capture highly flexible functional relationships for the variances.

Gaussian Processes

Blockwise SURE Shrinkage for Non-Local Means

no code implementations18 May 2013 Yue Wu, Brian Tracey, Premkumar Natarajan, Joseph P. Noonan

In this letter, we investigate the shrinkage problem for the non-local means (NLM) image denoising.

Image Denoising SSIM

Dynamic Covariance Models for Multivariate Financial Time Series

no code implementations18 May 2013 Yue Wu, José Miguel Hernández-Lobato, Zoubin Ghahramani

The accurate prediction of time-changing covariances is an important problem in the modeling of multivariate financial data.

Time Series Time Series Analysis

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