Search Results for author: Lei Chen

Found 79 papers, 23 papers with code

Outdoor Position Recovery from HeterogeneousTelco Cellular Data

no code implementations24 Aug 2021 Yige Zhang, Weixiong Rao, Kun Zhang, Lei Chen

The HMM approaches typically assume stable mobility patterns of the underlying mobile devices.

Multi-Task Learning

Resisting Out-of-Distribution Data Problem in Perturbation of XAI

no code implementations27 Jul 2021 Luyu Qiu, Yi Yang, Caleb Chen Cao, Jing Liu, Yueyuan Zheng, Hilary Hei Ting Ngai, Janet Hsiao, Lei Chen

Besides, our solution also resolves a fundamental problem with the faithfulness indicator, a commonly used evaluation metric of XAI algorithms that appears to be sensitive to the OoD issue.

Explainable artificial intelligence

A Queueing-Theoretic Framework for Vehicle Dispatching in Dynamic Car-Hailing [technical report]

no code implementations19 Jul 2021 Peng Cheng, Jiabao Jin, Lei Chen, Xuemin Lin, Libin Zheng

In this paper, we consider an important dynamic car-hailing problem, namely \textit{maximum revenue vehicle dispatching} (MRVD), in which rider requests dynamically arrive and drivers need to serve as many riders as possible such that the entire revenue of the platform is maximized.

Scene-adaptive Knowledge Distillation for Sequential Recommendation via Differentiable Architecture Search

no code implementations15 Jul 2021 Lei Chen, Fajie Yuan, Jiaxi Yang, Min Yang, Chengming Li

To realize such a goal, we propose AdaRec, a knowledge distillation (KD) framework which compresses knowledge of a teacher model into a student model adaptively according to its recommendation scene by using differentiable Neural Architecture Search (NAS).

Knowledge Distillation Neural Architecture Search +1

Hyper-LifelongGAN: Scalable Lifelong Learning for Image Conditioned Generation

no code implementations CVPR 2021 Mengyao Zhai, Lei Chen, Greg Mori

Deep neural networks are susceptible to catastrophic forgetting: when encountering a new task, they can only remember the new task and fail to preserve its ability to accomplish previously learned tasks.

Continual Learning

User-specific Adaptive Fine-tuning for Cross-domain Recommendations

no code implementations15 Jun 2021 Lei Chen, Fajie Yuan, Jiaxi Yang, Xiangnan He, Chengming Li, Min Yang

Fine-tuning works as an effective transfer learning technique for this objective, which adapts the parameters of a pre-trained model from the source domain to the target domain.

Recommendation Systems Transfer Learning

Learning-Aided Heuristics Design for Storage System

no code implementations14 Jun 2021 Yingtian Tang, Han Lu, Xijun Li, Lei Chen, Mingxuan Yuan, Jia Zeng

Computer systems such as storage systems normally require transparent white-box algorithms that are interpretable for human experts.

Label-Guided Learning for Item Categorization in e-Commerce

no code implementations NAACL 2021 Lei Chen, Hirokazu Miyake

Item categorization is an important application of text classification in e-commerce due to its impact on the online shopping experience of users.

Classification Hierarchical structure +1

Set2setRank: Collaborative Set to Set Ranking for Implicit Feedback based Recommendation

1 code implementation16 May 2021 Lei Chen, Le Wu, Kun Zhang, Richang Hong, Meng Wang

Despite the performance gain of these implicit feedback based models, the recommendation results are still far from satisfactory due to the sparsity of the observed item set for each user.

Adaptive Appearance Rendering

1 code implementation24 Apr 2021 Mengyao Zhai, Ruizhi Deng, Jiacheng Chen, Lei Chen, Zhiwei Deng, Greg Mori

Hence, we develop an approach based on intermediate representations of poses and appearance: our pose-guided appearance rendering network firstly encodes the targets' poses using an encoder-decoder neural network.

Video Generation

Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation

no code implementations ECCV 2020 Mengyao Zhai, Lei Chen, JiaWei He, Megha Nawhal, Frederick Tung, Greg Mori

In contrast, we propose a parameter efficient framework, Piggyback GAN, which learns the current task by building a set of convolutional and deconvolutional filters that are factorized into filters of the models trained on previous tasks.

Efficient Relation-aware Scoring Function Search for Knowledge Graph Embedding

1 code implementation22 Apr 2021 Shimin Di, Quanming Yao, Yongqi Zhang, Lei Chen

The scoring function, which measures the plausibility of triplets in knowledge graphs (KGs), is the key to ensure the excellent performance of KG embedding, and its design is also an important problem in the literature.

AutoML Knowledge Graph Embedding +1

Searching to Sparsify Tensor Decomposition for N-ary Relational Data

no code implementations21 Apr 2021 Shimin Di, Quanming Yao, Lei Chen

Recently, tensor decomposition methods have been introduced into N-ary relational data and become state-of-the-art on embedding learning.

Neural Architecture Search Tensor Decomposition

Learning Fair Representations for Recommendation: A Graph-based Perspective

1 code implementation18 Feb 2021 Le Wu, Lei Chen, Pengyang Shao, Richang Hong, Xiting Wang, Meng Wang

For each user, this transformation is achieved under the adversarial learning of a user-centric graph, in order to obfuscate each sensitive feature between both the filtered user embedding and the sub graph structures of this user.

Fairness Recommendation Systems

Field-free spin-orbit torque-induced switching of perpendicular magnetization in a ferrimagnetic layer with vertical composition gradient

no code implementations21 Jan 2021 Zhenyi Zheng, Yue Zhang, Victor Lopez-Dominguez, Luis Sánchez-Tejerina, Jiacheng Shi, Xueqiang Feng, Lei Chen, Zilu Wang, Zhizhong Zhang, Kun Zhang, Bin Hong, Yong Xu, Youguang Zhang, Mario Carpentieri, Albert Fert, Giovanni Finocchio, Weisheng Zhao, Pedram Khalili Amiri

Existing methods to do so involve the application of an in-plane bias magnetic field, or incorporation of in-plane structural asymmetry in the device, both of which can be difficult to implement in practical applications.

Mesoscale and Nanoscale Physics

Far-Field Super-Resolution Imaging By Nonlinear Excited Evanescent Waves

no code implementations14 Jan 2021 ZhiHao Zhou, Wei Liu, Jiajing He, Lei Chen, Xin Luo, Dongyi Shen, Jianjun Cao, Yaping Dan, Xianfeng Chen, Wenjie Wan

Abbe's resolution limit, one of the best-known physical limitations, poses a great challenge for any wave systems in imaging, wave transport, and dynamics.

Super-Resolution Optics

FTSO: Effective NAS via First Topology Second Operator

no code implementations1 Jan 2021 Likang Wang, Lei Chen

Existing one-shot neural architecture search (NAS) methods generally contain a giant supernet, which leads to heavy computational costs.

Neural Architecture Search

Quantitative Evaluations on Saliency Methods: An Experimental Study

no code implementations31 Dec 2020 Xiao-Hui Li, Yuhan Shi, Haoyang Li, Wei Bai, Yuanwei Song, Caleb Chen Cao, Lei Chen

It has been long debated that eXplainable AI (XAI) is an important topic, but it lacks rigorous definition and fair metrics.

Modeling Evolution of Message Interaction for Rumor Resolution

no code implementations COLING 2020 Lei Chen, Zhongyu Wei, Jing Li, Baohua Zhou, Qi Zhang, Xuanjing Huang

Previous work for rumor resolution concentrates on exploiting time-series characteristics or modeling topology structure separately.

Time Series

PG-GSQL: Pointer-Generator Network with Guide Decoding for Cross-Domain Context-Dependent Text-to-SQL Generation

1 code implementation COLING 2020 Huajie Wang, Mei Li, Lei Chen

We pay close attention to the cross-domain context-dependent text-to-SQL generation task, which requires a model to depend on the interaction history and current utterance to generate SQL query.


Scalable Federated Learning over Passive Optical Networks

no code implementations29 Oct 2020 Jun Li, Lei Chen, Jiajia Chen

Two-step aggregation is introduced to facilitate scalable federated learning (SFL) over passive optical networks (PONs).

Networking and Internet Architecture

On Graph Neural Networks versus Graph-Augmented MLPs

1 code implementation ICLR 2021 Lei Chen, Zhengdao Chen, Joan Bruna

From the perspective of expressive power, this work compares multi-layer Graph Neural Networks (GNNs) with a simplified alternative that we call Graph-Augmented Multi-Layer Perceptrons (GA-MLPs), which first augments node features with certain multi-hop operators on the graph and then applies an MLP in a node-wise fashion.

Community Detection

Efficient, Simple and Automated Negative Sampling for Knowledge Graph Embedding

1 code implementation24 Oct 2020 Yongqi Zhang, Quanming Yao, Lei Chen

In this paper, motivated by the observation that negative triplets with large gradients are important but rare, we propose to directly keep track of them with the cache.

Knowledge Graph Embedding

UniNet: Scalable Network Representation Learning with Metropolis-Hastings Sampling

1 code implementation10 Oct 2020 Xingyu Yao, Yingxia Shao, Bin Cui, Lei Chen

Finally, with the new edge sampler and random walk model abstraction, we carefully implement a scalable NRL framework called UniNet.

Representation Learning

Improving Sequential Latent Variable Models with Autoregressive Flows

no code implementations7 Oct 2020 Joseph Marino, Lei Chen, JiaWei He, Stephan Mandt

We propose an approach for improving sequence modeling based on autoregressive normalizing flows.

Latent Variable Models

Semi-Anchored Detector for One-Stage Object Detection

no code implementations10 Sep 2020 Lei Chen, Qi Qian, Hao Li

The anchor-free strategy benefits the classification task but can lead to sup-optimum for the regression task due to the lack of prior bounding boxes.

Classification General Classification +1

SPL-MLL: Selecting Predictable Landmarks for Multi-Label Learning

no code implementations ECCV 2020 Junbing Li, Changqing Zhang, Pengfei Zhu, Baoyuan Wu, Lei Chen, QinGhua Hu

Although significant progress achieved, multi-label classification is still challenging due to the complexity of correlations among different labels.

General Classification Multi-Label Classification +1

Learning to Transfer Graph Embeddings for Inductive Graph based Recommendation

no code implementations24 May 2020 Le Wu, Yonghui Yang, Lei Chen, Defu Lian, Richang Hong, Meng Wang

The transfer network is designed to approximate the learned item embeddings from graph neural networks by taking each item's visual content as input, in order to tackle the new segment problem in the test phase.

Transfer Learning

Multi-View Self-Attention for Interpretable Drug-Target Interaction Prediction

1 code implementation1 May 2020 Brighter Agyemang, Wei-Ping Wu, Michael Yelpengne Kpiebaareh, Zhihua Lei, Ebenezer Nanor, Lei Chen

In this study, we propose a self-attention-based multi-view representation learning approach for modeling drug-target interactions.

Drug Discovery Representation Learning

STAS: Adaptive Selecting Spatio-Temporal Deep Features for Improving Bias Correction on Precipitation

no code implementations13 Apr 2020 Yiqun Liu, Shouzhen Chen, Lei Chen, Hai Chu, Xiaoyang Xu, Junping Zhang, Leiming Ma

We thus propose an end-to-end deep-learning BCoP model named Spatio-Temporal feature Auto-Selective (STAS) model to select optimal ST regularity from EC via the ST Feature-selective Mechanisms (SFM/TFM).

Can Graph Neural Networks Count Substructures?

1 code implementation NeurIPS 2020 Zhengdao Chen, Lei Chen, Soledad Villar, Joan Bruna

We also prove positive results for k-WL and k-IGNs as well as negative results for k-WL with a finite number of iterations.

Revisiting Graph based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach

2 code implementations28 Jan 2020 Lei Chen, Le Wu, Richang Hong, Kun Zhang, Meng Wang

Second, we propose a residual network structure that is specifically designed for CF with user-item interaction modeling, which alleviates the over smoothing problem in graph convolution aggregation operation with sparse user-item interaction data.

Recommendation Systems Representation Learning

Adapting Grad-CAM for Embedding Networks

1 code implementation17 Jan 2020 Lei Chen, Jianhui Chen, Hossein Hajimirsadeghi, Greg Mori

Then, we develop an efficient weight-transfer method to explain decisions for any image without back-propagation.

Image Captioning Image Classification

Interstellar: Searching Recurrent Architecture for Knowledge Graph Embedding

2 code implementations NeurIPS 2020 Yongqi Zhang, Quanming Yao, Lei Chen

In this work, based on the relational paths, which are composed of a sequence of triplets, we define the Interstellar as a recurrent neural architecture search problem for the short-term and long-term information along the paths.

Knowledge Graph Embedding Neural Architecture Search

SpiralNet++: A Fast and Highly Efficient Mesh Convolution Operator

1 code implementation13 Nov 2019 Shunwang Gong, Lei Chen, Michael Bronstein, Stefanos Zafeiriou

Intrinsic graph convolution operators with differentiable kernel functions play a crucial role in analyzing 3D shape meshes.

3D Shape Reconstruction

Bandwidth Slicing to Boost Federated Learning in Edge Computing

no code implementations24 Oct 2019 Jun Li, Xiaoman Shen, Lei Chen, Jiajia Chen

Bandwidth slicing is introduced to support federated learning in edge computing to assure low communication delay for training traffic.

Edge-computing Federated Learning

DR Loss: Improving Object Detection by Distributional Ranking

1 code implementation CVPR 2020 Qi Qian, Lei Chen, Hao Li, Rong Jin

This architecture is efficient but can suffer from the imbalance issue with respect to two aspects: the inter-class imbalance between the number of candidates from foreground and background classes and the intra-class imbalance in the hardness of background candidates, where only a few candidates are hard to be identified.

Object Detection

Precipitation Nowcasting with Star-Bridge Networks

no code implementations18 Jul 2019 Yuan Cao, Qiuying Li, Hongming Shan, Zhizhong Huang, Lei Chen, Leiming Ma, Junping Zhang

Precipitation nowcasting, which aims to precisely predict the short-term rainfall intensity of a local region, is gaining increasing attention in the artificial intelligence community.

Video Prediction

Personalized Multimedia Item and Key Frame Recommendation

no code implementations1 Jun 2019 Le Wu, Lei Chen, Yonghui Yang, Richang Hong, Yong Ge, Xing Xie, Meng Wang

We argue that the key challenge of this problem lies in discovering users' visual profiles for key frame recommendation, as most recommendation models would fail without any users' fine-grained image behavior.

AutoSF: Searching Scoring Functions for Knowledge Graph Embedding

3 code implementations26 Apr 2019 Yongqi Zhang, Quanming Yao, Wenyuan Dai, Lei Chen

The algorithm is further sped up by a filter and a predictor, which can avoid repeatedly training SFs with same expressive ability and help removing bad candidates during the search before model training.

AutoML Knowledge Graph Embedding +2

Universal chosen-ciphertext attack for a family of image encryption schemes

2 code implementations28 Mar 2019 Junxin Chen, Lei Chen, Yicong Zhou

During the past decades, there is a great popularity employing nonlinear dynamics and permutation-substitution architecture for image encryption.


Quality-aware Unpaired Image-to-Image Translation

no code implementations15 Mar 2019 Lei Chen, Le Wu, Zhenzhen Hu, Meng Wang

To tackle the above two challenges, in this paper, we propose a unified quality-aware GAN-based framework for unpaired image-to-image translation, where a quality-aware loss is explicitly incorporated by comparing each source image and the reconstructed image at the domain level.

Image Quality Assessment Image-to-Image Translation

NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding

3 code implementations16 Dec 2018 Yongqi Zhang, Quanming Yao, Yingxia Shao, Lei Chen

Negative sampling, which samples negative triplets from non-observed ones in the training data, is an important step in KG embedding.

Knowledge Graph Embedding Link Prediction

Local Distribution in Neighborhood for Classification

no code implementations7 Dec 2018 Chengsheng Mao, Bin Hu, Lei Chen, Philip Moore, Xiaowei Zhang

Additionally, based on the local distribution, we generate a generalized local classification form that can be effectively applied to various datasets through tuning the parameters.

Classification General Classification

Part-Activated Deep Reinforcement Learning for Action Prediction

no code implementations ECCV 2018 Lei Chen, Jiwen Lu, Zhanjie Song, Jie zhou

In this paper, we propose a part-activated deep reinforcement learning (PA-DRL) for action prediction.

A Hierarchical Attention Model for Social Contextual Image Recommendation

1 code implementation3 Jun 2018 Le Wu, Lei Chen, Richang Hong, Yanjie Fu, Xing Xie, Meng Wang

After that, we design a hierarchical attention network that naturally mirrors the hierarchical relationship (elements in each aspects level, and the aspect level) of users' latent interests with the identified key aspects.

Proteomics Analysis of FLT3-ITD Mutation in Acute Myeloid Leukemia Using Deep Learning Neural Network

no code implementations29 Dec 2017 Christine A. Liang, Lei Chen, Amer Wahed, Andy N. D. Nguyen

The results of this study allow a novel approach to determine critical protein pathways in the FLT3-ITD mutation, and provide proof-of-concept for an accurate approach to model big data in cancer proteomics and genomics.

Learning to Forecast Videos of Human Activity with Multi-granularity Models and Adaptive Rendering

no code implementations5 Dec 2017 Mengyao Zhai, Jiacheng Chen, Ruizhi Deng, Lei Chen, Ligeng Zhu, Greg Mori

An architecture combining a hierarchical temporal model for predicting human poses and encoder-decoder convolutional neural networks for rendering target appearances is proposed.

Multi-view Registration Based on Weighted Low Rank and Sparse Matrix Decomposition of Motions

no code implementations25 Sep 2017 Congcong Jin, Jihua Zhu, Yaochen Li, Shanmin Pang, Lei Chen, Jun Wang

Then, it proposes the weighted LRS decomposition, where each block element is assigned with one estimated weight to denote its reliability.

Predicting Audience's Laughter During Presentations Using Convolutional Neural Network

no code implementations WS 2017 Lei Chen, Chong MIn Lee

Public speakings play important roles in schools and work places and properly using humor contributes to effective presentations.

General Classification Text Classification

Subjective Knowledge Acquisition and Enrichment Powered By Crowdsourcing

no code implementations16 May 2017 Rui Meng, Hao Xin, Lei Chen, Yangqiu Song

In our work, we propose a system, called crowdsourced subjective knowledge acquisition (CoSKA), for subjective knowledge acquisition powered by crowdsourcing and existing KBs.

Predicting Audience's Laughter Using Convolutional Neural Network

no code implementations8 Feb 2017 Lei Chen, Chong MIn Lee

For the purpose of automatically evaluating speakers' humor usage, we build a presentation corpus containing humorous utterances based on TED talks.

General Classification Text Classification

Can We Make Computers Laugh at Talks?

no code implementations WS 2016 Chong Min Lee, Su-Youn Yoon, Lei Chen

Considering the importance of public speech skills, a system which makes a prediction on where audiences laugh in a talk can be helpful to a person who prepares for a talk.

Zero-Shot Learning with Multi-Battery Factor Analysis

no code implementations30 Jun 2016 Zhong Ji, Yuzhong Xie, Yanwei Pang, Lei Chen, Zhongfei Zhang

Zero-shot learning (ZSL) extends the conventional image classification technique to a more challenging situation where the test image categories are not seen in the training samples.

Image Classification Zero-Shot Learning

Deep Structured Models For Group Activity Recognition

no code implementations12 Jun 2015 Zhiwei Deng, Mengyao Zhai, Lei Chen, Yuhao Liu, Srikanth Muralidharan, Mehrsan Javan Roshtkhari, Greg Mori

This paper presents a deep neural-network-based hierarchical graphical model for individual and group activity recognition in surveillance scenes.

Group Activity Recognition

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