Search Results for author: Qing Li

Found 80 papers, 23 papers with code

Collaborative Learning of Bidirectional Decoders for Unsupervised Text Style Transfer

1 code implementation EMNLP 2021 Yun Ma, Yangbin Chen, Xudong Mao, Qing Li

In this paper, we propose a collaborative learning framework for unsupervised text style transfer using a pair of bidirectional decoders, one decoding from left to right while the other decoding from right to left.

Knowledge Distillation Style Transfer +2

Task-oriented Domain-specific Meta-Embedding for Text Classification

no code implementations EMNLP 2020 Xin Wu, Yi Cai, Yang Kai, Tao Wang, Qing Li

Meta-embedding learning, which combines complementary information in different word embeddings, have shown superior performances across different Natural Language Processing tasks.

General Classification Text Classification +1

Conditional Causal Relationships between Emotions and Causes in Texts

no code implementations EMNLP 2020 Xinhong Chen, Qing Li, JianPing Wang

The causal relationships between emotions and causes in text have recently received a lot of attention.

Exploring Non-Autoregressive Text Style Transfer

1 code implementation EMNLP 2021 Yun Ma, Qing Li

In this paper, we explore Non-AutoRegressive (NAR) decoding for unsupervised text style transfer.

Contrastive Learning Knowledge Distillation +3

Stock Movement Prediction Based on Bi-typed and Hybrid-relational Market Knowledge Graph via Dual Attention Networks

no code implementations11 Jan 2022 Yu Zhao, Huaming Du, Ying Liu, Shaopeng Wei, Xingyan Chen, Huali Feng, Qinghong Shuai, Qing Li, Fuzhen Zhuang, Gang Kou

Stock Movement Prediction (SMP) aims at predicting listed companies' stock future price trend, which is a challenging task due to the volatile nature of financial markets.

Stock Prediction

Towards a Unified Foundation Model: Jointly Pre-Training Transformers on Unpaired Images and Text

no code implementations14 Dec 2021 Qing Li, Boqing Gong, Yin Cui, Dan Kondratyuk, Xianzhi Du, Ming-Hsuan Yang, Matthew Brown

The experiments show that the resultant unified foundation transformer works surprisingly well on both the vision-only and text-only tasks, and the proposed knowledge distillation and gradient masking strategy can effectively lift the performance to approach the level of separately-trained models.

Knowledge Distillation Natural Language Understanding

Self-Ensemling for 3D Point Cloud Domain Adaption

no code implementations10 Dec 2021 Qing Li, Xiaojiang Peng, Qi Hao

In SEN, a student network is kept in a collaborative manner with supervised learning and self-supervised learning, and a teacher network conducts temporal consistency to learn useful representations and ensure the quality of point clouds reconstruction.

Autonomous Driving Self-Supervised Learning +1

Deep Keyphrase Completion

no code implementations29 Oct 2021 Yu Zhao, Jia Song, Huali Feng, Fuzhen Zhuang, Qing Li, Xiaojie Wang, Ji Liu

Keyphrase provides accurate information of document content that is highly compact, concise, full of meanings, and widely used for discourse comprehension, organization, and text retrieval.

Keyphrase Extraction

Towards General Deep Leakage in Federated Learning

no code implementations18 Oct 2021 Jiahui Geng, Yongli Mou, Feifei Li, Qing Li, Oya Beyan, Stefan Decker, Chunming Rong

We find that image restoration fails even if there is only one incorrectly inferred label in the batch; we also find that when batch images have the same label, the corresponding image is restored as a fusion of that class of images.

Federated Learning Image Restoration

Benchmark Problems for CEC2021 Competition on Evolutionary Transfer Multiobjectve Optimization

1 code implementation15 Oct 2021 Songbai Liu, Qiuzhen Lin, Kay Chen Tan, Qing Li

Evolutionary transfer multiobjective optimization (ETMO) has been becoming a hot research topic in the field of evolutionary computation, which is based on the fact that knowledge learning and transfer across the related optimization exercises can improve the efficiency of others.

Multiobjective Optimization Transfer Learning

SpeechT5: Unified-Modal Encoder-Decoder Pre-training for Spoken Language Processing

no code implementations14 Oct 2021 Junyi Ao, Rui Wang, Long Zhou, Shujie Liu, Shuo Ren, Yu Wu, Tom Ko, Qing Li, Yu Zhang, Zhihua Wei, Yao Qian, Jinyu Li, Furu Wei

Motivated by the success of T5 (Text-To-Text Transfer Transformer) in pre-training natural language processing models, we propose a unified-modal SpeechT5 framework that explores the encoder-decoder pre-training for self-supervised speech/text representation learning.

Quantization Representation Learning +3

Multi-View Self-Attention Based Transformer for Speaker Recognition

no code implementations11 Oct 2021 Rui Wang, Junyi Ao, Long Zhou, Shujie Liu, Zhihua Wei, Tom Ko, Qing Li, Yu Zhang

In this work, we propose a novel multi-view self-attention mechanism and present an empirical study of different Transformer variants with or without the proposed attention mechanism for speaker recognition.

Speaker Recognition

DM-CT: Consistency Training with Data and Model Perturbation

no code implementations29 Sep 2021 Xiaobo Liang, Runze Mao, Lijun Wu, Juntao Li, Weiqing Liu, Qing Li, Min Zhang

The common approach of consistency training is performed on the data-level, which typically utilizes the data augmentation strategy (or adversarial training) to make the predictions from the augmented input and the original input to be consistent, so that the model is more robust and attains better generalization ability.

Data Augmentation Image Classification +2

YouRefIt: Embodied Reference Understanding with Language and Gesture

no code implementations ICCV 2021 Yixin Chen, Qing Li, Deqian Kong, Yik Lun Kei, Song-Chun Zhu, Tao Gao, Yixin Zhu, Siyuan Huang

To the best of our knowledge, this is the first embodied reference dataset that allows us to study referring expressions in daily physical scenes to understand referential behavior, human communication, and human-robot interaction.

Human robot interaction

Graph Trend Networks for Recommendations

no code implementations12 Aug 2021 Wenqi Fan, Xiaorui Liu, Wei Jin, Xiangyu Zhao, Jiliang Tang, Qing Li

Recommender systems aim to provide personalized services to users and are playing an increasingly important role in our daily lives.

Graph Representation Learning Recommendation Systems

DGEM: A New Dual-modal Graph Embedding Method in Recommendation System

no code implementations9 Aug 2021 Huimin Zhou, Qing Li, Yong Jiang, Rongwei Yang, Zhuyun Qi

In the current deep learning based recommendation system, the embedding method is generally employed to complete the conversion from the high-dimensional sparse feature vector to the low-dimensional dense feature vector.

Graph Embedding

Jointly Attacking Graph Neural Network and its Explanations

no code implementations7 Aug 2021 Wenqi Fan, Wei Jin, Xiaorui Liu, Han Xu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, JianPing Wang, Charu Aggarwal

Despite the great success, recent studies have shown that GNNs are highly vulnerable to adversarial attacks, where adversaries can mislead the GNNs' prediction by modifying graphs.

Multiple-criteria Based Active Learning with Fixed-size Determinantal Point Processes

no code implementations4 Jul 2021 Xueying Zhan, Qing Li, Antoni B. Chan

In this paper, we introduce a multiple-criteria based active learning algorithm, which incorporates three complementary criteria, i. e., informativeness, representativeness and diversity, to make appropriate selections in the active learning rounds under different data types.

Active Learning Point Processes

Intent Disentanglement and Feature Self-supervision for Novel Recommendation

no code implementations28 Jun 2021 Tieyun Qian, Yile Liang, Qing Li, Xuan Ma, Ke Sun, Zhiyong Peng

Improving the recommendation of tail items can promote novelty and bring positive effects to both users and providers, and thus is a desirable property of recommender systems.

Recommendation Systems Self-Supervised Learning

Unsupervised Person Re-Identification with Multi-Label Learning Guided Self-Paced Clustering

no code implementations8 Mar 2021 Qing Li, Xiaojiang Peng, Yu Qiao, Qi Hao

The multi-label learning module leverages a memory feature bank and assigns each image with a multi-label vector based on the similarities between the image and feature bank.

Multi-Label Learning Unsupervised Person Re-Identification

A HINT from Arithmetic: On Systematic Generalization of Perception, Syntax, and Semantics

no code implementations2 Mar 2021 Qing Li, Siyuan Huang, Yining Hong, Yixin Zhu, Ying Nian Wu, Song-Chun Zhu

Inspired by humans' remarkable ability to master arithmetic and generalize to unseen problems, we present a new dataset, HINT, to study machines' capability of learning generalizable concepts at three different levels: perception, syntax, and semantics.

Program Synthesis Systematic Generalization

Tips and Tricks for Webly-Supervised Fine-Grained Recognition: Learning from the WebFG 2020 Challenge

no code implementations29 Dec 2020 Xiu-Shen Wei, Yu-Yan Xu, Yazhou Yao, Jia Wei, Si Xi, Wenyuan Xu, Weidong Zhang, Xiaoxin Lv, Dengpan Fu, Qing Li, Baoying Chen, Haojie Guo, Taolue Xue, Haipeng Jing, Zhiheng Wang, Tianming Zhang, Mingwen Zhang

WebFG 2020 is an international challenge hosted by Nanjing University of Science and Technology, University of Edinburgh, Nanjing University, The University of Adelaide, Waseda University, etc.

SMART: A Situation Model for Algebra Story Problems via Attributed Grammar

no code implementations27 Dec 2020 Yining Hong, Qing Li, Ran Gong, Daniel Ciao, Siyuan Huang, Song-Chun Zhu

Solving algebra story problems remains a challenging task in artificial intelligence, which requires a detailed understanding of real-world situations and a strong mathematical reasoning capability.

Mathematical Reasoning

Learning by Fixing: Solving Math Word Problems with Weak Supervision

1 code implementation19 Dec 2020 Yining Hong, Qing Li, Daniel Ciao, Siyuan Huang, Song-Chun Zhu

To generate more diverse solutions, \textit{tree regularization} is applied to guide the efficient shrinkage and exploration of the solution space, and a \textit{memory buffer} is designed to track and save the discovered various fixes for each problem.

 Ranked #1 on Math Word Problem Solving on Math23K (weakly-supervised metric)

Multi Scale Temporal Graph Networks For Skeleton-based Action Recognition

no code implementations5 Dec 2020 Tingwei Li, Ruiwen Zhang, Qing Li

To appropriately describe the relations between joints in the skeleton graph, we propose a multi-scale graph strategy, adopting a full-scale graph, part-scale graph, and core-scale graph to capture the local features of each joint and the contour features of important joints.

Action Recognition Skeleton Based Action Recognition

A Unified Sequence Labeling Model for Emotion Cause Pair Extraction

no code implementations COLING 2020 Xinhong Chen, Qing Li, JianPing Wang

Existing approaches address the task by first extracting emotion and cause clauses via two binary classifiers separately, and then training another binary classifier to pair them up.

Emotion Cause Pair Extraction Emotion-Cause Pair Extraction

Deep Learning based Monocular Depth Prediction: Datasets, Methods and Applications

no code implementations9 Nov 2020 Qing Li, Jiasong Zhu, Jun Liu, Rui Cao, Qingquan Li, Sen Jia, Guoping Qiu

Despite the rapid progress in this topic, there are lacking of a comprehensive review, which is needed to summarize the current progress and provide the future directions.

Indoor Localization Monocular Depth Estimation +1

Suppressing Mislabeled Data via Grouping and Self-Attention

1 code implementation ECCV 2020 Xiaojiang Peng, Kai Wang, Zhaoyang Zeng, Qing Li, Jianfei Yang, Yu Qiao

Specifically, this plug-and-play AFM first leverages a \textit{group-to-attend} module to construct groups and assign attention weights for group-wise samples, and then uses a \textit{mixup} module with the attention weights to interpolate massive noisy-suppressed samples.

Image Classification

MetaMix: Improved Meta-Learning with Interpolation-based Consistency Regularization

no code implementations29 Sep 2020 Yangbin Chen, Yun Ma, Tom Ko, Jian-Ping Wang, Qing Li

MetaMix can be integrated with any of the MAML-based algorithms and learn the decision boundaries generalizing better to new tasks.

Few-Shot Learning Transfer Learning

Object-aware Multimodal Named Entity Recognition in Social Media Posts with Adversarial Learning

1 code implementation3 Aug 2020 Changmeng Zheng, Zhiwei Wu, Tao Wang, Cai Yi, Qing Li

To better exploit visual and textual information in NER, we propose an adversarial gated bilinear attention neural network (AGBAN).

Named Entity Recognition NER

Physical properties revealed by transport measurements on superconducting Nd$_{0.8}$Sr$_{0.2}$NiO$_{2}$ thin films

no code implementations9 Jul 2020 Ying Xiang, Qing Li, Yueying Li, Huan Yang, Yuefeng Nie, Hai-Hu Wen

The angle dependent resistivity at a fixed temperature and different magnetic fields cannot be scaled to one curve, which deviates from the prediction of the anisotropic Ginzburg-Landau theory.

Superconductivity Materials Science Strongly Correlated Electrons

Neural Mixed Counting Models for Dispersed Topic Discovery

no code implementations ACL 2020 Jiemin Wu, Yanghui Rao, Zusheng Zhang, Haoran Xie, Qing Li, Fu Lee Wang, Ziye Chen

Mixed counting models that use the negative binomial distribution as the prior can well model over-dispersed and hierarchically dependent random variables; thus they have attracted much attention in mining dispersed document topics.

Variational Inference

MiniNet: An extremely lightweight convolutional neural network for real-time unsupervised monocular depth estimation

no code implementations27 Jun 2020 Jun Liu, Qing Li, Rui Cao, Wenming Tang, Guoping Qiu

To the best of our knowledge, this work is the first extremely lightweight neural network trained on monocular video sequences for real-time unsupervised monocular depth estimation, which opens up the possibility of implementing deep learning-based real-time unsupervised monocular depth prediction on low-cost embedded devices.

Monocular Depth Estimation

PoseGAN: A Pose-to-Image Translation Framework for Camera Localization

no code implementations23 Jun 2020 Kanglin Liu, Qing Li, Guoping Qiu

We present PoseGANs, a conditional generative adversarial networks (cGANs) based framework for the implementation of pose-to-image translation.

Camera Localization Pose Estimation +1

Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning

1 code implementation ICML 2020 Qing Li, Siyuan Huang, Yining Hong, Yixin Chen, Ying Nian Wu, Song-Chun Zhu

In this paper, we address these issues and close the loop of neural-symbolic learning by (1) introducing the \textbf{grammar} model as a \textit{symbolic prior} to bridge neural perception and symbolic reasoning, and (2) proposing a novel \textbf{back-search} algorithm which mimics the top-down human-like learning procedure to propagate the error through the symbolic reasoning module efficiently.

Question Answering Visual Question Answering

Attacking Black-box Recommendations via Copying Cross-domain User Profiles

no code implementations17 May 2020 Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jian-Ping Wang, Jiliang Tang, Qing Li

In this work, we present our framework CopyAttack, which is a reinforcement learning based black-box attack method that harnesses real users from a source domain by copying their profiles into the target domain with the goal of promoting a subset of items.

Data Poisoning Recommendation Systems

Incorporating Effective Global Information via Adaptive Gate Attention for Text Classification

no code implementations22 Feb 2020 Xianming Li, Zongxi Li, Yingbin Zhao, Haoran Xie, Qing Li

The dominant text classification studies focus on training classifiers using textual instances only or introducing external knowledge (e. g., hand-craft features and domain expert knowledge).

General Classification Text Classification

Solving Cold Start Problem in Recommendation with Attribute Graph Neural Networks

no code implementations28 Dec 2019 Tieyun Qian, Yile Liang, Qing Li

More importantly, for a cold start user/item that does not have any interactions, such methods are unable to learn the preference embedding of the user/item since there is no link to this user/item in the graph.

Matrix Completion Recommendation Systems

Point2Node: Correlation Learning of Dynamic-Node for Point Cloud Feature Modeling

no code implementations23 Dec 2019 Wenkai Han, Chenglu Wen, Cheng Wang, Xin Li, Qing Li

Point2Node can dynamically explore correlation among all graph nodes from different levels, and adaptively aggregate the learned features.

Effective Semi-Supervised Node Classification on Few-Labeled Graph Data

1 code implementation7 Oct 2019 Ziang Zhou, Jieming Shi, Shengzhong Zhang, Zengfeng Huang, Qing Li

Graph neural networks (GNNs) are designed for semi-supervised node classification on graphs where only a small subset of nodes have class labels.

Graph Convolutional Network Model Selection +1

Learning Category Correlations for Multi-label Image Recognition with Graph Networks

no code implementations28 Sep 2019 Qing Li, Xiaojiang Peng, Yu Qiao, Qiang Peng

In this paper, instead of using a pre-defined graph which is inflexible and may be sub-optimal for multi-label classification, we propose the A-GCN, which leverages the popular Graph Convolutional Networks with an Adaptive label correlation graph to model label dependencies.

Multi-Label Classification Word Embeddings

Product Image Recognition with Guidance Learning and Noisy Supervision

no code implementations26 Jul 2019 Qing Li, Xiaojiang Peng, Liangliang Cao, Wenbin Du, Hao Xing, Yu Qiao

Instead of collecting product images by labor-and time-intensive image capturing, we take advantage of the web and download images from the reviews of several e-commerce websites where the images are casually captured by consumers.

Deep Social Collaborative Filtering

1 code implementation16 Jul 2019 Wenqi Fan, Yao Ma, Dawei Yin, Jian-Ping Wang, Jiliang Tang, Qing Li

Meanwhile, most of these models treat neighbors' information equally without considering the specific recommendations.

Collaborative Filtering Recommendation Systems

Deep Adversarial Social Recommendation

1 code implementation30 May 2019 Wenqi Fan, Tyler Derr, Yao Ma, JianPing Wang, Jiliang Tang, Qing Li

Recent years have witnessed rapid developments on social recommendation techniques for improving the performance of recommender systems due to the growing influence of social networks to our daily life.

Recommendation Systems Representation Learning

Virtual Mixup Training for Unsupervised Domain Adaptation

4 code implementations10 May 2019 Xudong Mao, Yun Ma, Zhenguo Yang, Yangbin Chen, Qing Li

Existing methods only impose the locally-Lipschitz constraint around the training points while miss the other areas, such as the points in-between training data.

Unsupervised Domain Adaptation

MMED: A Multi-domain and Multi-modality Event Dataset

1 code implementation4 Apr 2019 Zhenguo Yang, Zehang Lin, Min Cheng, Qing Li, Wenyin Liu

In this work, we construct and release a multi-domain and multi-modality event dataset (MMED), containing 25, 165 textual news articles collected from hundreds of news media sites (e. g., Yahoo News, Google News, CNN News.)

Question Answering Visual Question Answering

pyLLE: a Fast and User Friendly Lugiato-Lefever Equation Solver

1 code implementation22 Mar 2019 Gregory Moille, Qing Li, Xiyuan Lu, Kartik Srinivasan

We present the development of pyLLE, a freely accessible and cross-platform Lugiato-Lefever equation solver programmed in Python and Julia and optimized for the simulation of microresonator frequency combs.

Mathematical Software Optics

Graph Neural Networks for Social Recommendation

6 code implementations19 Feb 2019 Wenqi Fan, Yao Ma, Qing Li, Yuan He, Eric Zhao, Jiliang Tang, Dawei Yin

These advantages of GNNs provide great potential to advance social recommendation since data in social recommender systems can be represented as user-user social graph and user-item graph; and learning latent factors of users and items is the key.

Ranked #3 on Recommendation Systems on Epinions (using extra training data)

Recommendation Systems

Enhancing Remote Sensing Image Retrieval with Triplet Deep Metric Learning Network

no code implementations15 Feb 2019 Rui Cao, Qian Zhang, Jiasong Zhu, Qing Li, Qingquan Li, Bozhi Liu, Guoping Qiu

With the rapid growing of remotely sensed imagery data, there is a high demand for effective and efficient image retrieval tools to manage and exploit such data.

Image Retrieval Metric Learning

Learning Shared Semantic Space with Correlation Alignment for Cross-modal Event Retrieval

1 code implementation14 Jan 2019 Zhenguo Yang, Zehang Lin, Peipei Kang, Jianming Lv, Qing Li, Wenyin Liu

In this paper, we propose to learn shared semantic space with correlation alignment (${S}^{3}CA$) for multimodal data representations, which aligns nonlinear correlations of multimodal data distributions in deep neural networks designed for heterogeneous data.

Single Bitmap Block Truncation Coding of Color Images Using Hill Climbing Algorithm

no code implementations13 Jul 2018 Lige Zhang, Xiaolin Qin, Qing Li, Haoyue Peng, Yu Hou

Compared with various schemes, the simulation results of the proposed scheme are better than that of the reference schemes in visual quality and time consumption.

Unpaired Multi-Domain Image Generation via Regularized Conditional GANs

1 code implementation7 May 2018 Xudong Mao, Qing Li

To tackle this problem, we propose Regularized Conditional GAN (RegCGAN) which is capable of learning to generate corresponding images in the absence of paired training data.

Image Generation Unsupervised Domain Adaptation

VQA-E: Explaining, Elaborating, and Enhancing Your Answers for Visual Questions

no code implementations ECCV 2018 Qing Li, Qingyi Tao, Shafiq Joty, Jianfei Cai, Jiebo Luo

Most existing works in visual question answering (VQA) are dedicated to improving the accuracy of predicted answers, while disregarding the explanations.

Multi-Task Learning Question Answering +1

Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatial-Temporal Patterns

1 code implementation CVPR 2018 Jianming Lv, Weihang Chen, Qing Li, Can Yang

Most of the proposed person re-identification algorithms conduct supervised training and testing on single labeled datasets with small size, so directly deploying these trained models to a large-scale real-world camera network may lead to poor performance due to underfitting.

Incremental Learning Learning-To-Rank +2

VizWiz Grand Challenge: Answering Visual Questions from Blind People

no code implementations CVPR 2018 Danna Gurari, Qing Li, Abigale J. Stangl, Anhong Guo, Chi Lin, Kristen Grauman, Jiebo Luo, Jeffrey P. Bigham

The study of algorithms to automatically answer visual questions currently is motivated by visual question answering (VQA) datasets constructed in artificial VQA settings.

Question Answering Visual Question Answering

Tell-and-Answer: Towards Explainable Visual Question Answering using Attributes and Captions

no code implementations EMNLP 2018 Qing Li, Jianlong Fu, Dongfei Yu, Tao Mei, Jiebo Luo

Most existing approaches adopt the pipeline of representing an image via pre-trained CNNs, and then using the uninterpretable CNN features in conjunction with the question to predict the answer.

Image Captioning Question Answering +1

On the Effectiveness of Least Squares Generative Adversarial Networks

2 code implementations18 Dec 2017 Xudong Mao, Qing Li, Haoran Xie, Raymond Y. K. Lau, Zhen Wang, Stephen Paul Smolley

To overcome such a problem, we propose in this paper the Least Squares Generative Adversarial Networks (LSGANs) which adopt the least squares loss for both the discriminator and the generator.

AlignGAN: Learning to Align Cross-Domain Images with Conditional Generative Adversarial Networks

no code implementations5 Jul 2017 Xudong Mao, Qing Li, Haoran Xie

Recently, several methods based on generative adversarial network (GAN) have been proposed for the task of aligning cross-domain images or learning a joint distribution of cross-domain images.

A Network Framework for Noisy Label Aggregation in Social Media

no code implementations ACL 2017 Xueying Zhan, Yao-Wei Wang, Yanghui Rao, Haoran Xie, Qing Li, Fu Lee Wang, Tak-Lam Wong

This paper focuses on the task of noisy label aggregation in social media, where users with different social or culture backgrounds may annotate invalid or malicious tags for documents.

Image Classification Learning-To-Rank +1

Multiple VLAD encoding of CNNs for image classification

no code implementations30 Jun 2017 Qing Li, Qiang Peng, Chuan Yan

In this paper, we propose a special framework, which is the multiple VLAD encoding method with the CNNs features for image classification.

General Classification Image Classification

T-CONV: A Convolutional Neural Network For Multi-scale Taxi Trajectory Prediction

no code implementations23 Nov 2016 Jianming Lv, Qing Li, Xintong Wang

Precise destination prediction of taxi trajectories can benefit many intelligent location based services such as accurate ad for passengers.

Trajectory Prediction

Least Squares Generative Adversarial Networks

23 code implementations ICCV 2017 Xudong Mao, Qing Li, Haoran Xie, Raymond Y. K. Lau, Zhen Wang, Stephen Paul Smolley

To overcome such a problem, we propose in this paper the Least Squares Generative Adversarial Networks (LSGANs) which adopt the least squares loss function for the discriminator.

HCRS: A hybrid clothes recommender system based on user ratings and product features

no code implementations25 Nov 2014 Xiaosong Hu, Wen Zhu, Qing Li

Nowadays, online clothes-selling business has become popular and extremely attractive because of its convenience and cheap-and-fine price.

Recommendation Systems

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