Search Results for author: Wei Xiong

Found 41 papers, 12 papers with code

A Multi-modal one-class generative adversarial network for anomaly detection in manufacturing

no code implementations ICLR 2019 Shuhui Qu, Janghwan Lee, Wei Xiong, Wonhyouk Jang, Jie Wang

Since the generated samples simulate the low density area for each modal, the discriminator could directly detect anomalies from normal data.

One-Class Classification

ZhichunRoad at SemEval-2022 Task 2: Adversarial Training and Contrastive Learning for Multiword Representations

no code implementations SemEval (NAACL) 2022 Xuange Cui, Wei Xiong, Songlin Wang

This paper presents our contribution to the SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embedding. We explore the impact of three different pre-trained multilingual language models in the SubTaskA. By enhancing the model generalization and robustness, we use the exponential moving average (EMA) method and the adversarial attack strategy. In SubTaskB, we add an effective cross-attention module for modeling the relationships of two sentences. We jointly train the model with a contrastive learning objective and employ a momentum contrast to enlarge the number of negative pairs. Additionally, we use the alignment and uniformity properties to measure the quality of sentence embeddings. Our approach obtained competitive results in both subtasks.

Adversarial Attack Contrastive Learning

Windformer:Bi-Directional Long-Distance Spatio-Temporal Network For Wind Speed Prediction

1 code implementation24 Nov 2023 XueWei Li, Zewen Shang, Zhiqiang Liu, Jian Yu, Wei Xiong, Mei Yu

History and future time information includes the trend of airflow changes, whether this dynamic information can be utilized will also affect the prediction effect.

Management Time Series

AI-GOMS: Large AI-Driven Global Ocean Modeling System

no code implementations6 Aug 2023 Wei Xiong, Yanfei Xiang, Hao Wu, Shuyi Zhou, Yuze Sun, Muyuan Ma, Xiaomeng Huang

Here, we present AI-GOMS, a large AI-driven global ocean modeling system, for accurate and efficient global ocean daily prediction.

LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models

1 code implementation21 Jun 2023 Shizhe Diao, Rui Pan, Hanze Dong, Ka Shun Shum, Jipeng Zhang, Wei Xiong, Tong Zhang

As the number of available models and specialized tasks keeps growing, the job of general finetuning becomes highly nontrivial.

Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources

no code implementations14 Jun 2023 Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang

Then, a novel HetPEVI algorithm is proposed, which simultaneously considers the sample uncertainties from a finite number of data samples per data source and the source uncertainties due to a finite number of available data sources.

Offline RL reinforcement-learning +1

Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration

1 code implementation NeurIPS 2023 Zhihan Liu, Miao Lu, Wei Xiong, Han Zhong, Hao Hu, Shenao Zhang, Sirui Zheng, Zhuoran Yang, Zhaoran Wang

To achieve this, existing sample-efficient online RL algorithms typically consist of three components: estimation, planning, and exploration.

PastNet: Introducing Physical Inductive Biases for Spatio-temporal Video Prediction

1 code implementation19 May 2023 Hao Wu, Wei Xiong, Fan Xu, Xiao Luo, Chong Chen, Xian-Sheng Hua, Haixin Wang

In this paper, we investigate the challenge of spatio-temporal video prediction, which involves generating future videos based on historical data streams.

Video Prediction

Reward Teaching for Federated Multi-armed Bandits

no code implementations3 May 2023 Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang

Rigorous analyses demonstrate that when facing clients with UCB1, TWL outperforms TAL in terms of the dependencies on sub-optimality gaps thanks to its adaptive design.

Multi-Armed Bandits

RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment

1 code implementation13 Apr 2023 Hanze Dong, Wei Xiong, Deepanshu Goyal, Yihan Zhang, Winnie Chow, Rui Pan, Shizhe Diao, Jipeng Zhang, Kashun Shum, Tong Zhang

Utilizing a reward model and a sufficient number of samples, our approach selects the high-quality samples, discarding those that exhibit undesired behavior, and subsequently enhancing the model by fine-tuning on these filtered samples.


InstantBooth: Personalized Text-to-Image Generation without Test-Time Finetuning

no code implementations6 Apr 2023 Jing Shi, Wei Xiong, Zhe Lin, Hyun Joon Jung

First, we learn the general concept of the input images by converting them to a textual token with a learnable image encoder.


ZhichunRoad at Amazon KDD Cup 2022: MultiTask Pre-Training for E-Commerce Product Search

1 code implementation31 Jan 2023 Xuange Cui, Wei Xiong, Songlin Wang

In this paper, we propose a robust multilingual model to improve the quality of search results.

Contrastive Learning

Koopman neural operator as a mesh-free solver of non-linear partial differential equations

1 code implementation24 Jan 2023 Wei Xiong, Xiaomeng Huang, Ziyang Zhang, Ruixuan Deng, Pei Sun, Yang Tian

In machine learning, numerous latest advances of solver designs are accomplished in developing neural operators, a kind of mesh-free approximators of the infinite-dimensional operators that map between different parameterization spaces of equation solutions.

KoopmanLab: machine learning for solving complex physics equations

1 code implementation3 Jan 2023 Wei Xiong, Muyuan Ma, Xiaomeng Huang, Ziyang Zhang, Pei Sun, Yang Tian

To overcome this challenge, we present KoopmanLab, an efficient module of the Koopman neural operator family, for learning PDEs without analytic solutions or closed forms.

Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes

no code implementations12 Dec 2022 Chenlu Ye, Wei Xiong, Quanquan Gu, Tong Zhang

In this paper, we consider the contextual bandit with general function approximation and propose a computationally efficient algorithm to achieve a regret of $\tilde{O}(\sqrt{T}+\zeta)$.

Multi-Armed Bandits Reinforcement Learning (RL)

GEC: A Unified Framework for Interactive Decision Making in MDP, POMDP, and Beyond

no code implementations3 Nov 2022 Han Zhong, Wei Xiong, Sirui Zheng, LiWei Wang, Zhaoran Wang, Zhuoran Yang, Tong Zhang

The proposed algorithm modifies the standard posterior sampling algorithm in two aspects: (i) we use an optimistic prior distribution that biases towards hypotheses with higher values and (ii) a loglikelihood function is set to be the empirical loss evaluated on the historical data, where the choice of loss function supports both model-free and model-based learning.

Decision Making Reinforcement Learning (RL)

A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games

no code implementations4 Oct 2022 Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, Tong Zhang

Existing studies on provably efficient algorithms for Markov games (MGs) almost exclusively build on the "optimism in the face of uncertainty" (OFU) principle.

Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game

no code implementations31 May 2022 Wei Xiong, Han Zhong, Chengshuai Shi, Cong Shen, LiWei Wang, Tong Zhang

We also extend our techniques to the two-player zero-sum Markov games (MGs), and establish a new performance lower bound for MGs, which tightens the existing result, and verifies the nearly minimax optimality of the proposed algorithm.

Offline RL Reinforcement Learning (RL)

NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

2 code implementations11 May 2022 Yawei Li, Kai Zhang, Radu Timofte, Luc van Gool, Fangyuan Kong, Mingxi Li, Songwei Liu, Zongcai Du, Ding Liu, Chenhui Zhou, Jingyi Chen, Qingrui Han, Zheyuan Li, Yingqi Liu, Xiangyu Chen, Haoming Cai, Yu Qiao, Chao Dong, Long Sun, Jinshan Pan, Yi Zhu, Zhikai Zong, Xiaoxiao Liu, Zheng Hui, Tao Yang, Peiran Ren, Xuansong Xie, Xian-Sheng Hua, Yanbo Wang, Xiaozhong Ji, Chuming Lin, Donghao Luo, Ying Tai, Chengjie Wang, Zhizhong Zhang, Yuan Xie, Shen Cheng, Ziwei Luo, Lei Yu, Zhihong Wen, Qi Wu1, Youwei Li, Haoqiang Fan, Jian Sun, Shuaicheng Liu, Yuanfei Huang, Meiguang Jin, Hua Huang, Jing Liu, Xinjian Zhang, Yan Wang, Lingshun Long, Gen Li, Yuanfan Zhang, Zuowei Cao, Lei Sun, Panaetov Alexander, Yucong Wang, Minjie Cai, Li Wang, Lu Tian, Zheyuan Wang, Hongbing Ma, Jie Liu, Chao Chen, Yidong Cai, Jie Tang, Gangshan Wu, Weiran Wang, Shirui Huang, Honglei Lu, Huan Liu, Keyan Wang, Jun Chen, Shi Chen, Yuchun Miao, Zimo Huang, Lefei Zhang, Mustafa Ayazoğlu, Wei Xiong, Chengyi Xiong, Fei Wang, Hao Li, Ruimian Wen, Zhijing Yang, Wenbin Zou, Weixin Zheng, Tian Ye, Yuncheng Zhang, Xiangzhen Kong, Aditya Arora, Syed Waqas Zamir, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Dandan Gaoand Dengwen Zhouand Qian Ning, Jingzhu Tang, Han Huang, YuFei Wang, Zhangheng Peng, Haobo Li, Wenxue Guan, Shenghua Gong, Xin Li, Jun Liu, Wanjun Wang, Dengwen Zhou, Kun Zeng, Hanjiang Lin, Xinyu Chen, Jinsheng Fang

The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29. 00dB on DIV2K validation set.

Image Super-Resolution

Breast Cancer Induced Bone Osteolysis Prediction Using Temporal Variational Auto-Encoders

no code implementations20 Mar 2022 Wei Xiong, Neil Yeung, Shubo Wang, Haofu Liao, Liyun Wang, Jiebo Luo

Its ability of predicting the development of bone lesions in cancer-invading bones can assist in assessing the risk of impending fractures and choosing proper treatments in breast cancer bone metastasis.

Computed Tomography (CT)

Pessimistic Minimax Value Iteration: Provably Efficient Equilibrium Learning from Offline Datasets

no code implementations15 Feb 2022 Han Zhong, Wei Xiong, Jiyuan Tan, LiWei Wang, Tong Zhang, Zhaoran Wang, Zhuoran Yang

When the dataset does not have uniform coverage over all policy pairs, finding an approximate NE involves challenges in three aspects: (i) distributional shift between the behavior policy and the optimal policy, (ii) function approximation to handle large state space, and (iii) minimax optimization for equilibrium solving.

(Almost) Free Incentivized Exploration from Decentralized Learning Agents

1 code implementation NeurIPS 2021 Chengshuai Shi, Haifeng Xu, Wei Xiong, Cong Shen

In this work, we break this barrier and study incentivized exploration with multiple and long-term strategic agents, who have more complicated behaviors that often appear in real-world applications.

Multi-Armed Bandits

Distributional Reinforcement Learning for Multi-Dimensional Reward Functions

no code implementations NeurIPS 2021 Pushi Zhang, Xiaoyu Chen, Li Zhao, Wei Xiong, Tao Qin, Tie-Yan Liu

To fully inherit the benefits of distributional RL and hybrid reward architectures, we introduce Multi-Dimensional Distributional DQN (MD3QN), which extends distributional RL to model the joint return distribution from multiple reward sources.

Distributional Reinforcement Learning reinforcement-learning +1

GANet: Glyph-Attention Network for Few-Shot Font Generation

no code implementations29 Sep 2021 Mingtao Guo, Wei Xiong, Zheng Wang, Yong Tang, Ting Wu

Font generation is a valuable but challenging task, it is time consuming and costly to design font libraries which cover all glyphs with various styles.

Font Generation

Heterogeneous Network Embedding for Deep Semantic Relevance Match in E-commerce Search

no code implementations13 Jan 2021 Ziyang Liu, Zhaomeng Cheng, Yunjiang Jiang, Yue Shang, Wei Xiong, Sulong Xu, Bo Long, Di Jin

We propose in this paper a novel Second-order Relevance, which is fundamentally different from the previous First-order Relevance, to improve result relevance prediction.

Network Embedding

Image Sentiment Transfer

no code implementations19 Jun 2020 Tianlang Chen, Wei Xiong, Haitian Zheng, Jiebo Luo

In this paper, we propose an effective and flexible framework that performs image sentiment transfer at the object level.

Disentanglement Image-to-Image Translation +1

LinksIQ: Robust and Efficient Modulation Recognition with Imperfect Spectrum Scans

no code implementations7 May 2020 Wei Xiong, Karyn Doke, Petko Bogdanov, Mariya Zheleva

While critical for the practical progress of spectrum sharing, modulation recognition has so far been investigated under unrealistic assumptions: (i) a transmitter's bandwidth must be scanned alone and in full, (ii) prior knowledge of the technology must be available and (iii) a transmitter must be trustworthy.

Unsupervised Low-light Image Enhancement with Decoupled Networks

no code implementations6 May 2020 Wei Xiong, Ding Liu, Xiaohui Shen, Chen Fang, Jiebo Luo

In this paper, we tackle the problem of enhancing real-world low-light images with significant noise in an unsupervised fashion.

Image-to-Image Translation Low-Light Image Enhancement

Decentralized Multi-player Multi-armed Bandits with No Collision Information

no code implementations29 Feb 2020 Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang

The decentralized stochastic multi-player multi-armed bandit (MP-MAB) problem, where the collision information is not available to the players, is studied in this paper.

Multi-Armed Bandits

Fine-grained Image-to-Image Transformation towards Visual Recognition

no code implementations CVPR 2020 Wei Xiong, Yutong He, Yixuan Zhang, Wenhan Luo, Lin Ma, Jiebo Luo

In this paper, we aim at transforming an image with a fine-grained category to synthesize new images that preserve the identity of the input image, which can thereby benefit the subsequent fine-grained image recognition and few-shot learning tasks.

Few-Shot Learning Fine-Grained Image Recognition

Foreground-aware Image Inpainting

no code implementations CVPR 2019 Wei Xiong, Jiahui Yu, Zhe Lin, Jimei Yang, Xin Lu, Connelly Barnes, Jiebo Luo

We show that by such disentanglement, the contour completion model predicts reasonable contours of objects, and further substantially improves the performance of image inpainting.

Disentanglement Image Inpainting

CariGAN: Caricature Generation through Weakly Paired Adversarial Learning

no code implementations1 Nov 2018 Wenbin Li, Wei Xiong, Haofu Liao, Jing Huo, Yang Gao, Jiebo Luo

Furthermore, an attention mechanism is introduced to encourage our model to focus on the key facial parts so that more vivid details in these regions can be generated.


Regional Interactive Image Segmentation Networks

no code implementations ICCV 2017 Jun Hao Liew, Yunchao Wei, Wei Xiong, Sim-Heng Ong, Jiashi Feng

The interactive image segmentation model allows users to iteratively add new inputs for refinement until a satisfactory result is finally obtained.

Ranked #9 on Interactive Segmentation on SBD (NoC@85 metric)

Image Segmentation Interactive Segmentation +2

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