Search Results for author: Chunyan Miao

Found 91 papers, 37 papers with code

Toward Knowledge-Enriched Conversational Recommendation Systems

no code implementations NLP4ConvAI (ACL) 2022 Tong Zhang, Yong liu, Boyang Li, Peixiang Zhong, Chen Zhang, Hao Wang, Chunyan Miao

Conversational Recommendation Systems recommend items through language based interactions with users. In order to generate naturalistic conversations and effectively utilize knowledge graphs (KGs) containing background information, we propose a novel Bag-of-Entities loss, which encourages the generated utterances to mention concepts related to the item being recommended, such as the genre or director of a movie.

Knowledge Graphs Recommendation Systems +1

Improving Self-training for Cross-lingual Named Entity Recognition with Contrastive and Prototype Learning

no code implementations23 May 2023 Ran Zhou, Xin Li, Lidong Bing, Erik Cambria, Chunyan Miao

In cross-lingual named entity recognition (NER), self-training is commonly used to bridge the linguistic gap by training on pseudo-labeled target-language data.

Cross-Lingual NER named-entity-recognition +4

TranSG: Transformer-Based Skeleton Graph Prototype Contrastive Learning with Structure-Trajectory Prompted Reconstruction for Person Re-Identification

1 code implementation CVPR 2023 Haocong Rao, Chunyan Miao

Then, we propose the Graph Prototype Contrastive learning (GPC) to mine the most typical graph features (graph prototypes) of each identity, and contrast the inherent similarity between graph representations and different prototypes from both skeleton and sequence levels to learn discriminative graph representations.

Contrastive Learning Graph Reconstruction +2

Can ChatGPT Assess Human Personalities? A General Evaluation Framework

1 code implementation1 Mar 2023 Haocong Rao, Cyril Leung, Chunyan Miao

We further propose three evaluation metrics to measure the consistency, robustness, and fairness of assessment results from state-of-the-art LLMs including ChatGPT and InstructGPT.

Answer Generation Fairness

History-Aware Hierarchical Transformer for Multi-session Open-domain Dialogue System

no code implementations2 Feb 2023 Tong Zhang, Yong liu, Boyang Li, Zhiwei Zeng, Pengwei Wang, Yuan You, Chunyan Miao, Lizhen Cui

HAHT maintains a long-term memory of history conversations and utilizes history information to understand current conversation context and generate well-informed and context-relevant responses.

Multi-Aspect Explainable Inductive Relation Prediction by Sentence Transformer

1 code implementation4 Jan 2023 Zhixiang Su, Di Wang, Chunyan Miao, Lizhen Cui

Recent studies on knowledge graphs (KGs) show that path-based methods empowered by pre-trained language models perform well in the provision of inductive and explainable relation predictions.

Inductive Relation Prediction Knowledge Graphs

ConNER: Consistency Training for Cross-lingual Named Entity Recognition

1 code implementation17 Nov 2022 Ran Zhou, Xin Li, Lidong Bing, Erik Cambria, Luo Si, Chunyan Miao

We propose ConNER as a novel consistency training framework for cross-lingual NER, which comprises of: (1) translation-based consistency training on unlabeled target-language data, and (2) dropoutbased consistency training on labeled source-language data.

Cross-Lingual NER Knowledge Distillation +3

On Inferring User Socioeconomic Status with Mobility Records

1 code implementation15 Nov 2022 Zheng Wang, Mingrui Liu, Cheng Long, Qianru Zhang, Jiangneng Li, Chunyan Miao

The DeepSEI model incorporates two networks called deep network and recurrent network, which extract the features of the mobility records from three aspects, namely spatiality, temporality and activity, one at a coarse level and the other at a detailed level.

Management

Exploring Representation-Level Augmentation for Code Search

1 code implementation21 Oct 2022 Haochen Li, Chunyan Miao, Cyril Leung, Yanxian Huang, Yuan Huang, Hongyu Zhang, Yanlin Wang

In this paper, we explore augmentation methods that augment data (both code and query) at representation level which does not require additional data processing and training, and based on this we propose a general format of representation-level augmentation that unifies existing methods.

Code Search Contrastive Learning +1

Skeleton Prototype Contrastive Learning with Multi-Level Graph Relation Modeling for Unsupervised Person Re-Identification

1 code implementation25 Aug 2022 Haocong Rao, Chunyan Miao

Lastly, we propose a skeleton prototype contrastive learning scheme that clusters feature-correlative instances of unlabeled graph representations and contrasts their inherent similarity with representative skeleton features ("skeleton prototypes") to learn discriminative skeleton representations for person re-ID.

Contrastive Learning Unsupervised Person Re-Identification

Economics of Semantic Communication System: An Auction Approach

no code implementations2 Aug 2022 Zi Qin Liew, Hongyang Du, Wei Yang Bryan Lim, Zehui Xiong, Dusit Niyato, Chunyan Miao, Dong In Kim

The proposed incentive mechanism helps to maximize the revenue of semantic model providers in the semantic model trading, and effectively incentivizes model providers to participate in the development of semantic communication systems.

3D Cartoon Face Generation with Controllable Expressions from a Single GAN Image

no code implementations29 Jul 2022 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

To this end, we discover the semantic meanings of StyleGAN latent space, such that we are able to produce face images of various expressions, poses, and lighting by controlling the latent codes.

Face Generation Face Model

Paired Cross-Modal Data Augmentation for Fine-Grained Image-to-Text Retrieval

no code implementations29 Jul 2022 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

When we do online paired data augmentation, we first generate augmented text through random token replacement, then pass the augmented text into the latent space alignment module to output the latent codes, which are finally fed to StyleGAN2 to generate the augmented images.

Cross-Modal Retrieval Data Augmentation +3

Layer-refined Graph Convolutional Networks for Recommendation

1 code implementation22 Jul 2022 Xin Zhou, Donghui Lin, Yong liu, Chunyan Miao

Specifically, these models usually aggregate all layer embeddings for node updating and achieve their best recommendation performance within a few layers because of over-smoothing.

Bootstrap Latent Representations for Multi-modal Recommendation

2 code implementations13 Jul 2022 Xin Zhou, HongYu Zhou, Yong liu, Zhiwei Zeng, Chunyan Miao, Pengwei Wang, Yuan You, Feijun Jiang

Besides the user-item interaction graph, existing state-of-the-art methods usually use auxiliary graphs (e. g., user-user or item-item relation graph) to augment the learned representations of users and/or items.

Towards Counterfactual Image Manipulation via CLIP

1 code implementation6 Jul 2022 Yingchen Yu, Fangneng Zhan, Rongliang Wu, Jiahui Zhang, Shijian Lu, Miaomiao Cui, Xuansong Xie, Xian-Sheng Hua, Chunyan Miao

In addition, we design a simple yet effective scheme that explicitly maps CLIP embeddings (of target text) to the latent space and fuses them with latent codes for effective latent code optimization and accurate editing.

Image Manipulation

On Non-Random Missing Labels in Semi-Supervised Learning

1 code implementation ICLR 2022 Xinting Hu, Yulei Niu, Chunyan Miao, Xian-Sheng Hua, Hanwang Zhang

Our method is three-fold: 1) We propose Class-Aware Propensity (CAP) that exploits the unlabeled data to train an improved classifier using the biased labeled data.

Imputation Pseudo Label

Minimalist and High-performance Conversational Recommendation with Uncertainty Estimation for User Preference

no code implementations29 Jun 2022 Yinan Zhang, Boyang Li, Yong liu, You Yuan, Chunyan Miao

Multi-shot CRS is designed to make recommendations multiple times until the user either accepts the recommendation or leaves at the end of their patience.

Reinforcement Learning (RL)

Enhancing Sequential Recommendation with Graph Contrastive Learning

no code implementations30 May 2022 Yixin Zhang, Yong liu, Yonghui Xu, Hao Xiong, Chenyi Lei, wei he, Lizhen Cui, Chunyan Miao

Specifically, GCL4SR employs a Weighted Item Transition Graph (WITG), built based on interaction sequences of all users, to provide global context information for each interaction and weaken the noise information in the sequence data.

Auxiliary Learning Contrastive Learning +1

DualCF: Efficient Model Extraction Attack from Counterfactual Explanations

no code implementations13 May 2022 Yongjie Wang, Hangwei Qian, Chunyan Miao

We then propose DualCF strategy to circumvent the above issues, which is achieved by taking not only CF but also counterfactual explanation of CF (CCF) as pairs of training samples for the substitute model.

Counterfactual Explanation Model extraction

CCLF: A Contrastive-Curiosity-Driven Learning Framework for Sample-Efficient Reinforcement Learning

1 code implementation2 May 2022 Chenyu Sun, Hangwei Qian, Chunyan Miao

As a result, the agent can focus on more informative samples and learn representation invariances more efficiently, with significantly reduced augmented inputs.

Data Augmentation Q-Learning +2

SimMC: Simple Masked Contrastive Learning of Skeleton Representations for Unsupervised Person Re-Identification

1 code implementation21 Apr 2022 Haocong Rao, Chunyan Miao

Specifically, to fully exploit skeleton features within each skeleton sequence, we first devise a masked prototype contrastive learning (MPC) scheme to cluster the most typical skeleton features (skeleton prototypes) from different subsequences randomly masked from raw sequences, and contrast the inherent similarity between skeleton features and different prototypes to learn discriminative skeleton representations without using any label.

Contrastive Learning Representation Learning +1

SSD-KD: A Self-supervised Diverse Knowledge Distillation Method for Lightweight Skin Lesion Classification Using Dermoscopic Images

1 code implementation22 Mar 2022 Yongwei Wang, Yuheng Wang, Tim K. Lee, Chunyan Miao, Z. Jane Wang

In this case, knowledge distillation (KD) has been proven as an efficient tool to help improve the adaptability of lightweight models under limited resources, meanwhile keeping a high-level representation capability.

Knowledge Distillation Lesion Classification +1

What Makes Good Contrastive Learning on Small-Scale Wearable-based Tasks?

1 code implementation12 Feb 2022 Hangwei Qian, Tian Tian, Chunyan Miao

Self-supervised learning establishes a new paradigm of learning representations with much fewer or even no label annotations.

Activity Recognition Contrastive Learning +1

From Psychological Curiosity to Artificial Curiosity: Curiosity-Driven Learning in Artificial Intelligence Tasks

no code implementations20 Jan 2022 Chenyu Sun, Hangwei Qian, Chunyan Miao

Psychological curiosity plays a significant role in human intelligence to enhance learning through exploration and information acquisition.

Hierarchical Aspect-guided Explanation Generation for Explainable Recommendation

no code implementations20 Oct 2021 Yidan Hu, Yong liu, Chunyan Miao, Gongqi Lin, Yuan Miao

In this paper, we propose a novel explanation generation framework, named Hierarchical Aspect-guided explanation Generation (HAG), for explainable recommendation.

Explainable Recommendation Explanation Generation +1

Economics of Semantic Communication System in Wireless Powered Internet of Things

no code implementations4 Oct 2021 Zi Qin Liew, Yanyu Cheng, Wei Yang Bryan Lim, Dusit Niyato, Chunyan Miao, Sumei Sun

The semantic communication system enables wireless devices to communicate effectively with the semantic meaning of the data.

Learning Structural Representations for Recipe Generation and Food Retrieval

no code implementations4 Oct 2021 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

Our approach brings together several novel ideas in a systematic framework: (1) exploiting an unsupervised learning approach to obtain the sentence-level tree structure labels before training; (2) generating trees of target recipes from images with the supervision of tree structure labels learned from (1); and (3) integrating the learned tree structures into the recipe generation and food cross-modal retrieval procedure.

Cross-Modal Retrieval Image Captioning +2

Geometry-Entangled Visual Semantic Transformer for Image Captioning

no code implementations29 Sep 2021 Ling Cheng, Wei Wei, Feida Zhu, Yong liu, Chunyan Miao

However, those fusion-based models, they are still criticized for the lack of geometry information for inter and intra attention refinement.

Image Captioning

A Survey on Reinforcement Learning for Recommender Systems

no code implementations22 Sep 2021 Yuanguo Lin, Yong liu, Fan Lin, Lixin Zou, Pengcheng Wu, Wenhua Zeng, Huanhuan Chen, Chunyan Miao

To understand the challenges and relevant solutions, there should be a reference for researchers and practitioners working on RL-based recommender systems.

Explainable Recommendation reinforcement-learning +2

Cross-Modal Graph with Meta Concepts for Video Captioning

1 code implementation14 Aug 2021 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

Video captioning targets interpreting the complex visual contents as text descriptions, which requires the model to fully understand video scenes including objects and their interactions.

object-detection Object Detection +1

A Contract Theory based Incentive Mechanism for Federated Learning

no code implementations12 Aug 2021 Mengmeng Tian, Yuxin Chen, YuAn Liu, Zehui Xiong, Cyril Leung, Chunyan Miao

It is challenging to design proper incentives for the FL clients due to the fact that the task is privately trained by the clients.

Federated Learning

Cycle-Consistent Inverse GAN for Text-to-Image Synthesis

no code implementations3 Aug 2021 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

In this paper, we propose a novel unified framework of Cycle-consistent Inverse GAN (CI-GAN) for both text-to-image generation and text-guided image manipulation tasks.

Image Manipulation Text-to-Image Generation

Noise-Resistant Deep Metric Learning with Probabilistic Instance Filtering

no code implementations3 Aug 2021 Chang Liu, Han Yu, Boyang Li, Zhiqi Shen, Zhanning Gao, Peiran Ren, Xuansong Xie, Lizhen Cui, Chunyan Miao

Noisy labels are commonly found in real-world data, which cause performance degradation of deep neural networks.

Metric Learning

MulDA: A Multilingual Data Augmentation Framework for Low-Resource Cross-Lingual NER

no code implementations ACL 2021 Linlin Liu, Bosheng Ding, Lidong Bing, Shafiq Joty, Luo Si, Chunyan Miao

With the source-language data as well as the translated data, a generation-based multilingual data augmentation method is introduced to further increase diversity by generating synthetic labeled data in multiple languages.

Cross-Lingual NER Data Augmentation +5

WaveFill: A Wavelet-based Generation Network for Image Inpainting

1 code implementation ICCV 2021 Yingchen Yu, Fangneng Zhan, Shijian Lu, Jianxiong Pan, Feiying Ma, Xuansong Xie, Chunyan Miao

This paper presents WaveFill, a wavelet-based inpainting network that decomposes images into multiple frequency bands and fills the missing regions in each frequency band separately and explicitly.

Image Inpainting

SelfCF: A Simple Framework for Self-supervised Collaborative Filtering

2 code implementations7 Jul 2021 Xin Zhou, Aixin Sun, Yong liu, Jie Zhang, Chunyan Miao

Collaborative filtering (CF) is widely used to learn informative latent representations of users and items from observed interactions.

Collaborative Filtering Self-Supervised Learning

Bi-level Feature Alignment for Versatile Image Translation and Manipulation

2 code implementations7 Jul 2021 Fangneng Zhan, Yingchen Yu, Rongliang Wu, Jiahui Zhang, Kaiwen Cui, Aoran Xiao, Shijian Lu, Chunyan Miao

This paper presents a versatile image translation and manipulation framework that achieves accurate semantic and style guidance in image generation by explicitly building a correspondence.

Image Generation Translation

Initialization Matters: Regularizing Manifold-informed Initialization for Neural Recommendation Systems

no code implementations9 Jun 2021 Yinan Zhang, Boyang Li, Yong liu, Hao Wang, Chunyan Miao

In this work, we propose a new initialization scheme for user and item embeddings called Laplacian Eigenmaps with Popularity-based Regularization for Isolated Data (LEPORID).

Recommendation Systems

KECRS: Towards Knowledge-Enriched Conversational Recommendation System

no code implementations18 May 2021 Tong Zhang, Yong liu, Peixiang Zhong, Chen Zhang, Hao Wang, Chunyan Miao

The chit-chat-based conversational recommendation systems (CRS) provide item recommendations to users through natural language interactions.

Entity Embeddings Knowledge Graphs +3

Diverse Image Inpainting with Bidirectional and Autoregressive Transformers

no code implementations26 Apr 2021 Yingchen Yu, Fangneng Zhan, Rongliang Wu, Jianxiong Pan, Kaiwen Cui, Shijian Lu, Feiying Ma, Xuansong Xie, Chunyan Miao

With image-level attention, transformers enable to model long-range dependencies and generate diverse contents with autoregressive modeling of pixel-sequence distributions.

Image Inpainting Language Modelling

Latent-Optimized Adversarial Neural Transfer for Sarcasm Detection

1 code implementation NAACL 2021 Xu Guo, Boyang Li, Han Yu, Chunyan Miao

The existence of multiple datasets for sarcasm detection prompts us to apply transfer learning to exploit their commonality.

Meta-Learning Sarcasm Detection +1

Distilling Causal Effect of Data in Class-Incremental Learning

1 code implementation CVPR 2021 Xinting Hu, Kaihua Tang, Chunyan Miao, Xian-Sheng Hua, Hanwang Zhang

We propose a causal framework to explain the catastrophic forgetting in Class-Incremental Learning (CIL) and then derive a novel distillation method that is orthogonal to the existing anti-forgetting techniques, such as data replay and feature/label distillation.

class-incremental learning Class Incremental Learning +1

HYDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networks

1 code implementation4 Feb 2021 YuanYuan Chen, Boyang Li, Han Yu, Pengcheng Wu, Chunyan Miao

the weights of training data, HYDRA assesses the contribution of training data toward test data points throughout the training trajectory.

Rolling Shutter Correction

Brain-inspired Search Engine Assistant based on Knowledge Graph

no code implementations25 Dec 2020 Xuejiao Zhao, Huanhuan Chen, Zhenchang Xing, Chunyan Miao

However, when a query is complex, developers need to repeatedly refine the search keywords and open a large number of web pages to find and summarize answers.

Decision Making

A Hybrid Bandit Framework for Diversified Recommendation

no code implementations24 Dec 2020 Qinxu Ding, Yong liu, Chunyan Miao, Fei Cheng, Haihong Tang

Previous interactive recommendation methods primarily focus on learning users' personalized preferences on the relevance properties of an item set.

Recommendation Systems

Keyword-Guided Neural Conversational Model

1 code implementation15 Dec 2020 Peixiang Zhong, Yong liu, Hao Wang, Chunyan Miao

We study the problem of imposing conversational goals/keywords on open-domain conversational agents, where the agent is required to lead the conversation to a target keyword smoothly and fast.

Knowledge Graphs Retrieval +1

CARE: Commonsense-Aware Emotional Response Generation with Latent Concepts

no code implementations15 Dec 2020 Peixiang Zhong, Di Wang, Pengfei Li, Chen Zhang, Hao Wang, Chunyan Miao

Experimental results on two large-scale datasets support our hypothesis and show that our model can produce more accurate and commonsense-aware emotional responses and achieve better human ratings than state-of-the-art models that only specialize in one aspect.

Response Generation

Federated Learning for Personalized Humor Recognition

no code implementations3 Dec 2020 Xu Guo, Han Yu, Boyang Li, Hao Wang, Pengwei Xing, Siwei Feng, Zaiqing Nie, Chunyan Miao

In this paper, we propose the FedHumor approach for the recognition of humorous content in a personalized manner through Federated Learning (FL).

Federated Learning Language Modelling

Commonsense knowledge adversarial dataset that challenges ELECTRA

no code implementations25 Oct 2020 Gongqi Lin, Yuan Miao, Xiaoyong Yang, Wenwu Ou, Lizhen Cui, Wei Guo, Chunyan Miao

To investigate machine comprehension models' ability in handling the commonsense knowledge, we created a Question and Answer Dataset with common knowledge of Synonyms (QADS).

Reading Comprehension Word Sense Disambiguation

Structure-Aware Generation Network for Recipe Generation from Images

1 code implementation ECCV 2020 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

We investigate an open research task of generating cooking instructions based on only food images and ingredients, which is similar to the image captioning task.

Image Captioning Recipe Generation

Scalable and Communication-efficient Decentralized Federated Edge Learning with Multi-blockchain Framework

no code implementations10 Aug 2020 Jiawen Kang, Zehui Xiong, Chunxiao Jiang, Yi Liu, Song Guo, Yang Zhang, Dusit Niyato, Cyril Leung, Chunyan Miao

This framework can achieve scalable and flexible decentralized FEL by individually manage local model updates or model sharing records for performance isolation.

Cryptography and Security

Decomposing Generation Networks with Structure Prediction for Recipe Generation

no code implementations27 Jul 2020 Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao

Recipe generation from food images and ingredients is a challenging task, which requires the interpretation of the information from another modality.

Image Captioning Recipe Generation

Federated Learning in the Sky: Aerial-Ground Air Quality Sensing Framework with UAV Swarms

no code implementations23 Jul 2020 Yi Liu, Jiangtian Nie, Xuandi Li, Syed Hassan Ahmed, Wei Yang Bryan Lim, Chunyan Miao

To this end, this paper proposes a new federated learning-based aerial-ground air quality sensing framework for fine-grained 3D air quality monitoring and forecasting.

Federated Learning

Joint Auction-Coalition Formation Framework for Communication-Efficient Federated Learning in UAV-Enabled Internet of Vehicles

no code implementations13 Jul 2020 Jer Shyuan Ng, Wei Yang Bryan Lim, Hong-Ning Dai, Zehui Xiong, Jianqiang Huang, Dusit Niyato, Xian-Sheng Hua, Cyril Leung, Chunyan Miao

The simulation results show that the grand coalition, where all UAVs join a single coalition, is not always stable due to the profit-maximizing behavior of the UAVs.

Networking and Internet Architecture Signal Processing

Towards Persona-Based Empathetic Conversational Models

1 code implementation EMNLP 2020 Peixiang Zhong, Chen Zhang, Hao Wang, Yong liu, Chunyan Miao

To this end, we propose a new task towards persona-based empathetic conversations and present the first empirical study on the impact of persona on empathetic responding.

Learning Hierarchical Review Graph Representations for Recommendation

no code implementations24 Apr 2020 Yong liu, Susen Yang, Yinan Zhang, Chunyan Miao, Zaiqing Nie, Juyong Zhang

Therefore, they may not be effective in capturing the global dependency between words, and tend to be easily biased by noise review information.

Graph Attention

Contextualized Graph Attention Network for Recommendation with Item Knowledge Graph

no code implementations24 Apr 2020 Susen Yang, Yong liu, Yonghui Xu, Chunyan Miao, Min Wu, Juyong Zhang

Graph neural networks (GNN) have recently been applied to exploit knowledge graph (KG) for recommendation.

Graph Attention

Towards Federated Learning in UAV-Enabled Internet of Vehicles: A Multi-Dimensional Contract-Matching Approach

no code implementations8 Apr 2020 Wei Yang Bryan Lim, Jianqiang Huang, Zehui Xiong, Jiawen Kang, Dusit Niyato, Xian-Sheng Hua, Cyril Leung, Chunyan Miao

Coupled with the rise of Deep Learning, the wealth of data and enhanced computation capabilities of Internet of Vehicles (IoV) components enable effective Artificial Intelligence (AI) based models to be built.

Signal Processing Networking and Internet Architecture

Learning to Segment the Tail

1 code implementation CVPR 2020 Xinting Hu, Yi Jiang, Kaihua Tang, Jingyuan Chen, Chunyan Miao, Hanwang Zhang

Real-world visual recognition requires handling the extreme sample imbalance in large-scale long-tailed data.

Few-Shot Learning Incremental Learning

Commonsense Knowledge + BERT for Level 2 Reading Comprehension Ability Test

no code implementations8 Sep 2019 Yidan Hu, Gongqi Lin, Yuan Miao, Chunyan Miao

In this research, we propose a system which aims to allow computers to read articles and answer related questions with commonsense knowledge like a human being for CAT level 2.

Reading Comprehension

Reading Comprehension Ability Test-A Turing Test for Reading Comprehension

no code implementations5 Sep 2019 Yuan Miao, Gongqi Lin, Yidan Hu, Chunyan Miao

In order to be able to compare the difference between people reading and machines reading, we proposed a test called (reading) Comprehension Ability Test (CAT). CAT is similar to Turing test, passing of which means we cannot differentiate people from algorithms in term of their comprehension ability.

Reading Comprehension

PD-GAN: Adversarial Learning for Personalized Diversity-Promoting Recommendation

1 code implementation IJCAI 2019 Qiong Wu, Yong liu, Chunyan Miao, Binqiang Zhao, Yin Zhao, Lu Guan

This paper proposes Personalized Diversity-promoting GAN (PD-GAN), a novel recommendation model to generate diverse, yet relevant recommendations.

Recommendation Systems

EEG-Based Emotion Recognition Using Regularized Graph Neural Networks

1 code implementation18 Jul 2019 Peixiang Zhong, Di Wang, Chunyan Miao

Finally, investigations on the neuronal activities reveal important brain regions and inter-channel relations for EEG-based emotion recognition.

EEG Emotion Recognition Electroencephalogram (EEG)

Bandit Learning for Diversified Interactive Recommendation

no code implementations1 Jul 2019 Yong Liu, Yingtai Xiao, Qiong Wu, Chunyan Miao, Juyong Zhang

Interactive recommender systems that enable the interactions between users and the recommender system have attracted increasing research attentions.

Bayesian Inference Recommendation Systems +1

Recent Advances in Diversified Recommendation

no code implementations16 May 2019 Qiong Wu, Yong liu, Chunyan Miao, Yin Zhao, Lu Guan, Haihong Tang

With the rapid development of recommender systems, accuracy is no longer the only golden criterion for evaluating whether the recommendation results are satisfying or not.

Recommendation Systems

Diversity-Promoting Deep Reinforcement Learning for Interactive Recommendation

no code implementations19 Mar 2019 Yong Liu, Yinan Zhang, Qiong Wu, Chunyan Miao, Lizhen Cui, Binqiang Zhao, Yin Zhao, Lu Guan

Interactive recommendation that models the explicit interactions between users and the recommender system has attracted a lot of research attentions in recent years.

Recommendation Systems reinforcement-learning +1

Multi-Scale Quasi-RNN for Next Item Recommendation

no code implementations26 Feb 2019 Chaoyue He, Yong liu, Qingyu Guo, Chunyan Miao

To this end, architectural inductive biases such as Markov-Chains, Recurrent models, Convolutional networks and many others have demonstrated reasonable success on this task.

Recommendation Systems

Ethically Aligned Opportunistic Scheduling for Productive Laziness

no code implementations2 Jan 2019 Han Yu, Chunyan Miao, Yongqing Zheng, Lizhen Cui, Simon Fauvel, Cyril Leung

In order to enable workforce management systems to follow the IEEE Ethically Aligned Design guidelines to prioritize worker wellbeing, we propose a distributed Computational Productive Laziness (CPL) approach in this paper.

Management Scheduling

Building Ethics into Artificial Intelligence

no code implementations7 Dec 2018 Han Yu, Zhiqi Shen, Chunyan Miao, Cyril Leung, Victor R. Lesser, Qiang Yang

As artificial intelligence (AI) systems become increasingly ubiquitous, the topic of AI governance for ethical decision-making by AI has captured public imagination.

Decision Making Ethics

PSDVec: a Toolbox for Incremental and Scalable Word Embedding

no code implementations10 Jun 2016 Shaohua Li, Jun Zhu, Chunyan Miao

PSDVec is a Python/Perl toolbox that learns word embeddings, i. e. the mapping of words in a natural language to continuous vectors which encode the semantic/syntactic regularities between the words.

Word Embeddings Word Similarity

Generative Topic Embedding: a Continuous Representation of Documents (Extended Version with Proofs)

1 code implementation9 Jun 2016 Shaohua Li, Tat-Seng Chua, Jun Zhu, Chunyan Miao

Word embedding maps words into a low-dimensional continuous embedding space by exploiting the local word collocation patterns in a small context window.

Document Classification Variational Inference

A Generative Word Embedding Model and its Low Rank Positive Semidefinite Solution

1 code implementation EMNLP 2015 Shaohua Li, Jun Zhu, Chunyan Miao

Most existing word embedding methods can be categorized into Neural Embedding Models and Matrix Factorization (MF)-based methods.

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