Search Results for author: Xin Liu

Found 120 papers, 41 papers with code

Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting

no code implementations ECCV 2020 Junhua Zou, Zhisong Pan, Junyang Qiu, Xin Liu, Ting Rui, Wei Li

Diversity-Ensemble and Region Fitting","We introduce a three stage pipeline: resized-diverse-inputs (RDIM), diversity-ensemble (DEM) and region fitting, that work together to generate transferable adversarial examples.

Cross-lingual Transfer for Text Classification with Dictionary-based Heterogeneous Graph

1 code implementation9 Sep 2021 Nuttapong Chairatanakul, Noppayut Sriwatanasakdi, Nontawat Charoenphakdee, Xin Liu, Tsuyoshi Murata

To address this challenge, we propose dictionary-based heterogeneous graph neural network (DHGNet) that effectively handles the heterogeneity of DHG by two-step aggregations, which are word-level and language-level aggregations.

Cross-Lingual Transfer Text Classification +1

GNNSampler: Bridging the Gap between Sampling Algorithms of GNN and Hardware

no code implementations26 Aug 2021 Xin Liu, Mingyu Yan, Shuhan Song, Zhengyang Lv, WenMing Li, Guangyu Sun, Xiaochun Ye, Dongrui Fan

Finally, we emphatically conduct experiments on large graph datasets to analyze the relevance between the training time, model accuracy, and hardware-level metrics, which helps achieve a good trade-off between time and accuracy in GNN training.

AGNet: Weighing Black Holes with Deep Learning

1 code implementation17 Aug 2021 Joshua Yao-Yu Lin, Sneh Pandya, Devanshi Pratap, Xin Liu, Matias Carrasco Kind, Volodymyr Kindratenko

We find a 1$\sigma$ scatter of 0. 37 dex between the predicted SMBH mass and the fiducial virial mass estimate based on SDSS single-epoch spectra, which is comparable to the systematic uncertainty in the virial mass estimate.

Time Series

MMChat: Multi-Modal Chat Dataset on Social Media

no code implementations16 Aug 2021 Yinhe Zheng, Guanyi Chen, Xin Liu, Ke Lin

We develop a benchmark model to address this issue in dialogue generation tasks by adapting the attention routing mechanism on image features.

Dialogue Generation

Provable Convergence of Nesterov Accelerated Method for Over-Parameterized Neural Networks

no code implementations5 Jul 2021 Xin Liu, Zhisong Pan

Specifically, we prove that the error of NAG converges to zero at a linear convergence rate $1-\Theta(1/\sqrt{\kappa})$, where $\kappa > 1$ is determined by the initialization and the architecture of neural network.

iMiGUE: An Identity-free Video Dataset for Micro-Gesture Understanding and Emotion Analysis

1 code implementation CVPR 2021 Xin Liu, Henglin Shi, Haoyu Chen, Zitong Yu, Xiaobai Li, Guoying Zhaoz?

We introduce a new dataset for the emotional artificial intelligence research: identity-free video dataset for Micro-Gesture Understanding and Emotion analysis (iMiGUE).

Emotion Recognition

Early Mobility Recognition for Intensive Care Unit Patients Using Accelerometers

no code implementations28 Jun 2021 Rex Liu, Sarina A Fazio, Huanle Zhang, Albara Ah Ramli, Xin Liu, Jason Yeates Adams

In this paper, we target a new healthcare application of human activity recognition, early mobility recognition for Intensive Care Unit(ICU) patients.

Activity Recognition Feature Engineering

Multi-hop Graph Convolutional Network with High-order Chebyshev Approximation for Text Reasoning

1 code implementation ACL 2021 Shuoran Jiang, Qingcai Chen, Xin Liu, Baotian Hu, Lisai Zhang

In this study, we define the spectral graph convolutional network with the high-order dynamic Chebyshev approximation (HDGCN), which augments the multi-hop graph reasoning by fusing messages aggregated from direct and long-term dependencies into one convolutional layer.

A Provably-Efficient Model-Free Algorithm for Constrained Markov Decision Processes

no code implementations3 Jun 2021 Honghao Wei, Xin Liu, Lei Ying

This paper presents the first {\em model-free}, {\em simulator-free} reinforcement learning algorithm for Constrained Markov Decision Processes (CMDPs) with sublinear regret and zero constraint violation.

Improving Graph Neural Networks with Simple Architecture Design

1 code implementation17 May 2021 Sunil Kumar Maurya, Xin Liu, Tsuyoshi Murata

Combining these techniques, we present a simple and shallow model, Feature Selection Graph Neural Network (FSGNN), and show empirically that the proposed model outperforms other state of the art GNN models and achieves up to 64% improvements in accuracy on node classification tasks.

Feature Selection Node Classification

FDDH: Fast Discriminative Discrete Hashing for Large-Scale Cross-Modal Retrieval

1 code implementation15 May 2021 Xin Liu, Xingzhi Wang, Yiu-ming Cheung

To tackle these issues, we formulate the learning of similarity-preserving hash codes in terms of orthogonally rotating the semantic data so as to minimize the quantization loss of mapping such data to hamming space, and propose an efficient Fast Discriminative Discrete Hashing (FDDH) approach for large-scale cross-modal retrieval.

Cross-Modal Retrieval Quantization

Accuracy-Privacy Trade-off in Deep Ensembles

1 code implementation12 May 2021 Shahbaz Rezaei, Zubair Shafiq, Xin Liu

Ensemble learning has also been used to defend against membership inference attacks that undermine privacy.

Ensemble Learning Inference Attack +1

Gait Characterization in Duchenne Muscular Dystrophy (DMD) Using a Single-Sensor Accelerometer: Classical Machine Learning and Deep Learning Approaches

no code implementations12 May 2021 Albara Ah Ramli, Huanle Zhang, Jiahui Hou, Rex Liu, Xin Liu, Alina Nicorici, Daniel Aranki, Corey Owens, Poonam Prasad, Craig McDonald, Erik Henricson

Differences in gait patterns of children with Duchenne muscular dystrophy (DMD) and typically developing (TD) peers are visible to the eye, but quantification of those differences outside of the gait laboratory has been elusive.

Distractor-Aware Fast Tracking via Dynamic Convolutions and MOT Philosophy

1 code implementation CVPR 2021 Zikai Zhang, Bineng Zhong, Shengping Zhang, Zhenjun Tang, Xin Liu, Zhaoxiang Zhang

A practical long-term tracker typically contains three key properties, i. e. an efficient model design, an effective global re-detection strategy and a robust distractor awareness mechanism.

Multiple Object Tracking

A Survey on Federated Learning and its Applications for Accelerating Industrial Internet of Things

no code implementations21 Apr 2021 Jiehan Zhou, Shouhua Zhang, Qinghua Lu, Wenbin Dai, Min Chen, Xin Liu, Susanna Pirttikangas, Yang Shi, Weishan Zhang, Enrique Herrera-Viedma

Federated learning (FL) brings collaborative intelligence into industries without centralized training data to accelerate the process of Industry 4. 0 on the edge computing level.

Edge-computing Federated Learning

ASER: Towards Large-scale Commonsense Knowledge Acquisition via Higher-order Selectional Preference over Eventualities

1 code implementation5 Apr 2021 Hongming Zhang, Xin Liu, Haojie Pan, Haowen Ke, Jiefu Ou, Tianqing Fang, Yangqiu Song

After conceptualization with Probase, a selectional preference based concept-instance relational knowledge base, our concept graph contains 15 million conceptualized eventualities and 224 million edges between them.

Discourse Parsing

Learning to Filter: Siamese Relation Network for Robust Tracking

1 code implementation CVPR 2021 Siyuan Cheng, Bineng Zhong, Guorong Li, Xin Liu, Zhenjun Tang, Xianxian Li, Jing Wang

RD performs in a meta-learning way to obtain a learning ability to filter the distractors from the background while RM aims to effectively integrate the proposed RD into the Siamese framework to generate accurate tracking result.


No frame left behind: Full Video Action Recognition

1 code implementation CVPR 2021 Xin Liu, Silvia L. Pintea, Fatemeh Karimi Nejadasl, Olaf Booij, Jan C. van Gemert

A common heuristic is uniformly sampling a small number of video frames and using these to recognize the action.

Action Recognition

An Overview of Human Activity Recognition Using Wearable Sensors: Healthcare and Artificial Intelligence

no code implementations29 Mar 2021 Rex Liu, Albara Ah Ramli, Huanle Zhang, Erik Henricson, Xin Liu

With the rapid development of the internet of things (IoT) and artificial intelligence (AI) technologies, human activity recognition (HAR) has been applied in a variety of domains such as security and surveillance, human-robot interaction, and entertainment.

Activity Recognition Feature Engineering +2

Balanced Softmax Cross-Entropy for Incremental Learning

no code implementations23 Mar 2021 Quentin Jodelet, Xin Liu, Tsuyoshi Murata

Deep neural networks are prone to catastrophic forgetting when incrementally trained on new classes or new tasks as adaptation to the new data leads to a drastic decrease of the performance on the old classes and tasks.

class-incremental learning Incremental Learning +1

Sampling methods for efficient training of graph convolutional networks: A survey

no code implementations10 Mar 2021 Xin Liu, Mingyu Yan, Lei Deng, Guoqi Li, Xiaochun Ye, Dongrui Fan

Graph Convolutional Networks (GCNs) have received significant attention from various research fields due to the excellent performance in learning graph representations.

Higher-order topological superconductors based on weak topological insulators

no code implementations2 Mar 2021 Xun-Jiang Luo, Xiao-Hong Pan, Xin Liu

High-order topological phases host robust boundary states at the boundary of the boundary, which can be interpreted from their boundary topology.

Superconductivity Mesoscale and Nanoscale Physics Materials Science

DST: Data Selection and joint Training for Learning with Noisy Labels

no code implementations1 Mar 2021 Yi Wei, Xue Mei, Xin Liu, Pengxiang Xu

In this paper, we propose a Data Selection and joint Training (DST) method to automatically select training samples with accurate annotations.

Learning with noisy labels

An Efficient Pessimistic-Optimistic Algorithm for Stochastic Linear Bandits with General Constraints

no code implementations10 Feb 2021 Xin Liu, Bin Li, Pengyi Shi, Lei Ying

Thus, the overall computational complexity of our algorithm is similar to that of the linear UCB for unconstrained stochastic linear bandits.

Learning adaptive differential evolution algorithm from optimization experiences by policy gradient

no code implementations6 Feb 2021 Jianyong Sun, Xin Liu, Thomas Bäck, Zongben Xu

A reinforcement learning algorithm, named policy gradient, is applied to learn an agent (i. e. parameter controller) that can provide the control parameters of a proposed differential evolution adaptively during the search procedure.

Stochastic Optimization

Spectrum Sharing for 6G Integrated Satellite-Terrestrial Communication Networks Based on NOMA and Cognitive Radio

no code implementations27 Jan 2021 Xin Liu, Kwok-Yan Lam, Feng Li, Jun Zhao, Li Wang

ISTCN aims to provide high speed and pervasive network services by integrating broadband terrestrial mobile networks with satellite communication networks.

SplitSR: An End-to-End Approach to Super-Resolution on Mobile Devices

no code implementations20 Jan 2021 Xin Liu, Yuang Li, Josh Fromm, Yuntao Wang, Ziheng Jiang, Alex Mariakakis, Shwetak Patel

In this work, we demonstrate state-of-the-art latency and accuracy for on-device super-resolution using a novel hybrid architecture called SplitSR and a novel lightweight residual block called SplitSRBlock.


Generalized Image Reconstruction over T-Algebra

1 code implementation17 Jan 2021 Liang Liao, Xuechun Zhang, Xinqiang Wang, Sen Lin, Xin Liu

We also show in our experiments that the performance of TPCA increases when the order of compounded pixels increases.

Dimensionality Reduction Image Reconstruction

Automated Model Design and Benchmarking of 3D Deep Learning Models for COVID-19 Detection with Chest CT Scans

2 code implementations14 Jan 2021 Xin He, Shihao Wang, Xiaowen Chu, Shaohuai Shi, Jiangping Tang, Xin Liu, Chenggang Yan, Jiyong Zhang, Guiguang Ding

The experimental results show that our automatically searched models (CovidNet3D) outperform the baseline human-designed models on the three datasets with tens of times smaller model size and higher accuracy.

Medical Diagnosis Neural Architecture Search

An Unsupervised Learning Method with Convolutional Auto-Encoder for Vessel Trajectory Similarity Computation

no code implementations10 Jan 2021 Maohan Liang, Ryan Wen Liu, Shichen Li, Zhe Xiao, Xin Liu, Feng Lu

Based on the massive vessel trajectories collected, the CAE can learn the low-dimensional representations of informative trajectory images in an unsupervised manner.

OAAE: Adversarial Autoencoders for Novelty Detection in Multi-modal Normality Case via Orthogonalized Latent Space

no code implementations7 Jan 2021 Sungkwon An, Jeonghoon Kim, Myungjoo Kang, Shahbaz Razaei, Xin Liu

Specifically, we employ orthogonal low-rank embedding in the latent space to disentangle the features in the latent space using mutual class information.

Image Reconstruction

MedWriter: Knowledge-Aware Medical Text Generation

no code implementations COLING 2020 Youcheng Pan, Qingcai Chen, Weihua Peng, Xiaolong Wang, Baotian Hu, Xin Liu, Junying Chen, Wenxiu Zhou

To exploit the domain knowledge to guarantee the correctness of generated text has been a hot topic in recent years, especially for high professional domains such as medical.

Text Generation

AGNet: Weighing Black Holes with Machine Learning

1 code implementation30 Nov 2020 Joshua Yao-Yu Lin, Sneh Pandya, Devanshi Pratap, Xin Liu, Matias Carrasco Kind

Supermassive black holes (SMBHs) are ubiquitously found at the centers of most galaxies.

Time Series

Multi-task MR Imaging with Iterative Teacher Forcing and Re-weighted Deep Learning

no code implementations27 Nov 2020 Kehan Qi, Yu Gong, Xinfeng Liu, Xin Liu, Hairong Zheng, Shanshan Wang

Noises, artifacts, and loss of information caused by the magnetic resonance (MR) reconstruction may compromise the final performance of the downstream applications.

Soft-Median Choice: An Automatic Feature Smoothing Method for Sound Event Detection

no code implementations25 Nov 2020 Fengnian Zhao, Ruwei Li, Xin Liu, Liwen Xu

In Sound Event Detection (SED) systems, the lengths of median filters for post-processing have never been optimized during training due to several problems.

Event Detection Sound Event Detection

Adaptive Federated Dropout: Improving Communication Efficiency and Generalization for Federated Learning

no code implementations8 Nov 2020 Nader Bouacida, Jiahui Hou, Hui Zang, Xin Liu

With more regulations tackling users' privacy-sensitive data protection in recent years, access to such data has become increasingly restricted and controversial.

Federated Learning

AbdomenCT-1K: Is Abdominal Organ Segmentation A Solved Problem?

1 code implementation28 Oct 2020 Jun Ma, Yao Zhang, Song Gu, Cheng Zhu, Cheng Ge, Yichi Zhang, Xingle An, Congcong Wang, Qiyuan Wang, Xin Liu, Shucheng Cao, Qi Zhang, Shangqing Liu, Yunpeng Wang, Yuhui Li, Jian He, Xiaoping Yang

With the unprecedented developments in deep learning, automatic segmentation of main abdominal organs seems to be a solved problem as state-of-the-art (SOTA) methods have achieved comparable results with inter-rater variability on many benchmark datasets.

Continual Learning Pancreas Segmentation

Bandit Policies for Reliable Cellular Network Handovers in Extreme Mobility

no code implementations28 Oct 2020 Yuanjie Li, Esha Datta, Jiaxin Ding, Ness Shroff, Xin Liu

The demand for seamless Internet access under extreme user mobility, such as on high-speed trains and vehicles, has become a norm rather than an exception.

Advancing Non-Contact Vital Sign Measurement using Synthetic Avatars

no code implementations24 Oct 2020 Daniel McDuff, Javier Hernandez, Erroll Wood, Xin Liu, Tadas Baltrusaitis

Non-contact physiological measurement has the potential to provide low-cost, non-invasive health monitoring.

POND: Pessimistic-Optimistic oNline Dispatching

no code implementations20 Oct 2020 Xin Liu, Bin Li, Pengyi Shi, Lei Ying

This paper considers constrained online dispatching with unknown arrival, reward and constraint distributions.

WeightAlign: Normalizing Activations by Weight Alignment

no code implementations14 Oct 2020 Xiangwei Shi, Yunqiang Li, Xin Liu, Jan van Gemert

Such methods are less stable than BN as they critically depend on the statistics of a single input sample.

Domain Adaptation Semantic Segmentation

MetaPhys: Few-Shot Adaptation for Non-Contact Physiological Measurement

no code implementations5 Oct 2020 Xin Liu, Ziheng Jiang, Josh Fromm, Xuhai Xu, Shwetak Patel, Daniel McDuff

There are large individual differences in physiological processes, making designing personalized health sensing algorithms challenging.


ENAS4D: Efficient Multi-stage CNN Architecture Search for Dynamic Inference

no code implementations19 Sep 2020 Zhihang Yuan, Xin Liu, Bingzhe Wu, Guangyu Sun

The inference of a input sample can exit from early stage if the prediction of the stage is confident enough.

Candidate Periodically Variable Quasars from the Dark Energy Survey and the Sloan Digital Sky Survey

no code implementations27 Aug 2020 Yu-Ching Chen, Xin Liu, Wei-Ting Liao, A. Miguel Holgado, Hengxiao Guo, Robert A. Gruendl, Eric Morganson, Yue Shen, Kaiwen Zhang, Tim M. C. Abbott, Michel Aguena, Sahar Allam, Santiago Avila, Emmanuel Bertin, Sunayana Bhargava, David Brooks, David L. Burke, Aurelio Carnero Rosell, Daniela Carollo, Matias Carrasco Kind, Jorge Carretero, Matteo Costanzi, Luiz N. da Costa, Tamara M. Davis, Juan De Vicente, Shantanu Desai, H. Thomas Diehl, Peter Doel, Spencer Everett, Brenna Flaugher, Douglas Friedel, Joshua Frieman, Juan García-Bellido, Enrique Gaztanaga, Karl Glazebrook, Daniel Gruen, Gaston Gutierrez, Samuel R. Hinton, Devon L. Hollowood, David J. James, Alex G. Kim, Kyler Kuehn, Nikolay Kuropatkin, Geraint F. Lewis, Christopher Lidman, Marcos Lima, Marcio A. G. Maia, Marisa March, Jennifer L. Marshall, Felipe Menanteau, Ramon Miquel, Antonella Palmese, Francisco Paz-Chinchón, Andrés A. Plazas, Eusebio Sanchez, Michael Schubnell, Santiago Serrano, Ignacio Sevilla-Noarbe, Mathew Smith, Eric Suchyta, Molly E. C. Swanson, Gregory Tarle, Brad E. Tucker, Tamas Norbert Varga, Alistair R. Walker

We present a systematic search for periodic light curves in 625 spectroscopically confirmed quasars with a median redshift of 1. 8 in a 4. 6 deg$^2$ overlapping region of the Dark Energy Survey Supernova (DES-SN) fields and the Sloan Digital Sky Survey Stripe 82 (SDSS-S82).

High Energy Astrophysical Phenomena Astrophysics of Galaxies

A Variational Approach to Unsupervised Sentiment Analysis

no code implementations21 Aug 2020 Ziqian Zeng, Wenxuan Zhou, Xin Liu, Zizheng Lin, Yangqin Song, Michael David Kuo, Wan Hang Keith Chiu

Our objective function is to predict an opinion word given a target word while our ultimate goal is to learn a sentiment classifier.

Sentiment Analysis

2nd Place Scheme on Action Recognition Track of ECCV 2020 VIPriors Challenges: An Efficient Optical Flow Stream Guided Framework

no code implementations10 Aug 2020 Haoyu Chen, Zitong Yu, Xin Liu, Wei Peng, Yoon Lee, Guoying Zhao

To address the problem of training on small datasets for action recognition tasks, most prior works are either based on a large number of training samples or require pre-trained models transferred from other large datasets to tackle overfitting problems.

Action Recognition Optical Flow Estimation

Graph Convolutional Networks for Graphs Containing Missing Features

2 code implementations9 Jul 2020 Hibiki Taguchi, Xin Liu, Tsuyoshi Murata

Notably, our approach does not increase the computational complexity of GCN and it is consistent with GCN when the features are complete.

Graph Learning Imputation +2

Making Adversarial Examples More Transferable and Indistinguishable

no code implementations8 Jul 2020 Junhua Zou, Zhisong Pan, Junyang Qiu, Yexin Duan, Xin Liu, Yu Pan

Many previous methods generate adversarial examples based on the fast gradient sign attack series.

Deep Low-rank Prior in Dynamic MR Imaging

no code implementations22 Jun 2020 Ziwen Ke, Wenqi Huang, Jing Cheng, Zhuoxu Cui, Sen Jia, Haifeng Wang, Xin Liu, Hairong Zheng, Leslie Ying, Yanjie Zhu, Dong Liang

The deep learning methods have achieved attractive performance in dynamic MR cine imaging.

An Opportunistic Bandit Approach for User Interface Experimentation

no code implementations21 Jun 2020 Nader Bouacida, Amit Pande, Xin Liu

In fact, we model user interface experimentation as an opportunistic bandit problem, in which the cost of exploration varies under a factor extracted from customer features.

Contextual Bandits with Side-Observations

no code implementations6 Jun 2020 Rahul Singh, Fang Liu, Xin Liu, Ness Shroff

We show that this asymptotically optimal regret is upper-bounded as $O\left(|\chi(\mathcal{G})|\log T\right)$, where $|\chi(\mathcal{G})|$ is the domination number of $\mathcal{G}$.

Multi-Armed Bandits

Multi-Task Temporal Shift Attention Networks for On-Device Contactless Vitals Measurement

2 code implementations NeurIPS 2020 Xin Liu, Josh Fromm, Shwetak Patel, Daniel McDuff

Telehealth and remote health monitoring have become increasingly important during the SARS-CoV-2 pandemic and it is widely expected that this will have a lasting impact on healthcare practices.

BWCNN: Blink to Word, a Real-Time Convolutional Neural Network Approach

no code implementations1 Jun 2020 Albara Ah Ramli, Rex Liu, Rahul Krishnamoorthy, Vishal I B, Xiaoxiao Wang, Ilias Tagkopoulos, Xin Liu

The system uses a Convolutional Neural Network (CNN) to find the blinking pattern, which is defined as a series of Open and Closed states.

On the Difficulty of Membership Inference Attacks

1 code implementation CVPR 2021 Shahbaz Rezaei, Xin Liu

Recent studies propose membership inference (MI) attacks on deep models, where the goal is to infer if a sample has been used in the training process.

Image Classification Inference Attack

MMFashion: An Open-Source Toolbox for Visual Fashion Analysis

3 code implementations18 May 2020 Xin Liu, Jiancheng Li, Jiaqi Wang, Ziwei Liu

This toolbox supports a wide spectrum of fashion analysis tasks, including Fashion Attribute Prediction, Fashion Recognition and Retrieval, Fashion Landmark Detection, Fashion Parsing and Segmentation and Fashion Compatibility and Recommendation.

On the Importance of Word and Sentence Representation Learning in Implicit Discourse Relation Classification

1 code implementation27 Apr 2020 Xin Liu, Jiefu Ou, Yangqiu Song, Xin Jiang

Implicit discourse relation classification is one of the most difficult parts in shallow discourse parsing as the relation prediction without explicit connectives requires the language understanding at both the text span level and the sentence level.

Classification Discourse Parsing +3

Decomposing Word Embedding with the Capsule Network

no code implementations7 Apr 2020 Xin Liu, Qingcai Chen, Yan Liu, Joanna Siebert, Baotian Hu, Xiang-Ping Wu, Buzhou Tang

We propose a Capsule network-based method to Decompose the unsupervised word Embedding of an ambiguous word into context specific Sense embedding, called CapsDecE2S.

Word Embeddings Word Sense Disambiguation

Learning Diverse Fashion Collocation by Neural Graph Filtering

no code implementations11 Mar 2020 Xin Liu, Yongbin Sun, Ziwei Liu, Dahua Lin

To facilitate a comprehensive study on diverse fashion collocation, we reorganize Amazon Fashion dataset with carefully designed evaluation protocols.

Recommendation Systems

XGPT: Cross-modal Generative Pre-Training for Image Captioning

no code implementations3 Mar 2020 Qiaolin Xia, Haoyang Huang, Nan Duan, Dong-dong Zhang, Lei Ji, Zhifang Sui, Edward Cui, Taroon Bharti, Xin Liu, Ming Zhou

While many BERT-based cross-modal pre-trained models produce excellent results on downstream understanding tasks like image-text retrieval and VQA, they cannot be applied to generation tasks directly.

Data Augmentation Denoising +4

Neural Subgraph Isomorphism Counting

1 code implementation25 Dec 2019 Xin Liu, Haojie Pan, Mutian He, Yangqiu Song, Xin Jiang, Lifeng Shang

In this paper, we study a new graph learning problem: learning to count subgraph isomorphisms.

Domain Adaptation Graph Learning +4

Security of Deep Learning Methodologies: Challenges and Opportunities

no code implementations8 Dec 2019 Shahbaz Rezaei, Xin Liu

Despite the plethora of studies about security vulnerabilities and defenses of deep learning models, security aspects of deep learning methodologies, such as transfer learning, have been rarely studied.

Transfer Learning

IPO: Interior-point Policy Optimization under Constraints

no code implementations21 Oct 2019 Yongshuai Liu, Jiaxin Ding, Xin Liu

In this paper, we study reinforcement learning (RL) algorithms to solve real-world decision problems with the objective of maximizing the long-term reward as well as satisfying cumulative constraints.

Cross Domain Image Matching in Presence of Outliers

no code implementations8 Sep 2019 Xin Liu, Seyran Khademi, Jan C. van Gemert

Cross domain image matching between image collections from different source and target domains is challenging in times of deep learning due to i) limited variation of image conditions in a training set, ii) lack of paired-image labels during training, iii) the existing of outliers that makes image matching domains not fully overlap.

Domain Adaptation Outlier Detection

Hyper-Path-Based Representation Learning for Hyper-Networks

1 code implementation24 Aug 2019 Jie Huang, Xin Liu, Yangqiu Song

Then a carefully designed algorithm, Hyper-gram, utilizes these random walks to capture both pairwise relationships and tuplewise relationships in the whole hyper-networks.

Link Prediction Representation Learning

A Novel Kalman Filter Based Shilling Attack Detection Algorithm

no code implementations18 Aug 2019 Xin Liu, Yingyuan Xiao, Xu Jiao, Wenguang Zheng, Zihao Ling

Collaborative filtering has been widely used in recommendation systems to recommend items that users might like.

Recommendation Systems

hood2vec: Identifying Similar Urban Areas Using Mobility Networks

no code implementations17 Jul 2019 Xin Liu, Konstantinos Pelechrinis, Alexandros Labrinidis

Hence, in this paper, we introduce an approach, namely hood2vec, to identify the similarity between urban areas through learning a node embedding of the mobility network captured through Foursquare check-ins.

Collecting Indicators of Compromise from Unstructured Text of Cybersecurity Articles using Neural-Based Sequence Labelling

no code implementations4 Jul 2019 Zi Long, Lianzhi Tan, Shengping Zhou, Chaoyang He, Xin Liu

Indicators of Compromise (IOCs) are artifacts observed on a network or in an operating system that can be utilized to indicate a computer intrusion and detect cyber-attacks in an early stage.

Multitask Learning for Network Traffic Classification

1 code implementation12 Jun 2019 Shahbaz Rezaei, Xin Liu

We show that with a large amount of easily obtainable data samples for bandwidth and duration prediction tasks, and only a few data samples for the traffic classification task, one can achieve high accuracy.

Classification General Classification +3

DeepcomplexMRI: Exploiting deep residual network for fast parallel MR imaging with complex convolution

1 code implementation11 Jun 2019 Shan-Shan Wang, Huitao Cheng, Leslie Ying, Taohui Xiao, Ziwen Ke, Xin Liu, Hairong Zheng, Dong Liang

This paper proposes a multi-channel image reconstruction method, named DeepcomplexMRI, to accelerate parallel MR imaging with residual complex convolutional neural network.

Image Reconstruction

Super-Resolved Image Perceptual Quality Improvement via Multi-Feature Discriminators

no code implementations24 Apr 2019 Xuan Zhu, Yue Cheng, Jinye Peng, Rongzhi Wang, Mingnan Le, Xin Liu

However, the GAN-based SR methods only use image discriminator to distinguish SR images and high-resolution (HR) images.

Image Super-Resolution

Relation Discovery with Out-of-Relation Knowledge Base as Supervision

1 code implementation NAACL 2019 Yan Liang, Xin Liu, Jianwen Zhang, Yangqiu Song

In this paper, we study the problem of how to use out-of-relation knowledge bases to supervise the discovery of unseen relations, where out-of-relation means that relations to discover from the text corpus and those in knowledge bases are not overlapped.

A Target-Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer Learning

1 code implementation ICLR 2020 Shahbaz Rezaei, Xin Liu

Due to insufficient training data and the high computational cost to train a deep neural network from scratch, transfer learning has been extensively used in many deep-neural-network-based applications.

Face Recognition Image Classification +2

AdaLinUCB: Opportunistic Learning for Contextual Bandits

no code implementations20 Feb 2019 Xueying Guo, Xiaoxiao Wang, Xin Liu

In this paper, we propose and study opportunistic contextual bandits - a special case of contextual bandits where the exploration cost varies under different environmental conditions, such as network load or return variation in recommendations.

Multi-Armed Bandits

DNNVM : End-to-End Compiler Leveraging Heterogeneous Optimizations on FPGA-based CNN Accelerators

no code implementations20 Feb 2019 Yu Xing, Shuang Liang, Lingzhi Sui, Xijie Jia, Jiantao Qiu, Xin Liu, Yushun Wang, Yu Wang, Yi Shan

On the Xilinx ZU2 @330 MHz and ZU9 @330 MHz, we achieve equivalently state-of-the-art performance on our benchmarks by na\"ive implementations without optimizations, and the throughput is further improved up to 1. 26x by leveraging heterogeneous optimizations in DNNVM.

Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era

no code implementations1 Feb 2019 Gabrielle Allen, Igor Andreoni, Etienne Bachelet, G. Bruce Berriman, Federica B. Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Daniel George, Tom Gibbs, Matthew Graham, William Gropp, Anushri Gupta, Roland Haas, E. A. Huerta, Elise Jennings, Daniel S. Katz, Asad Khan, Volodymyr Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Kenton McHenry, J. M. Miller, M. S. Neubauer, Steve Oberlin, Alexander R. Olivas Jr, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard Schutz, Alex Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Brigitta M. Sipőcz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, JinJun Xiong, Zhizhen Zhao

We discuss key aspects to realize this endeavor, namely (i) the design and exploitation of scalable and computationally efficient AI algorithms for Multi-Messenger Astrophysics; (ii) cyberinfrastructure requirements to numerically simulate astrophysical sources, and to process and interpret Multi-Messenger Astrophysics data; (iii) management of gravitational wave detections and triggers to enable electromagnetic and astro-particle follow-ups; (iv) a vision to harness future developments of machine and deep learning and cyberinfrastructure resources to cope with the scale of discovery in the Big Data Era; (v) and the need to build a community that brings domain experts together with data scientists on equal footing to maximize and accelerate discovery in the nascent field of Multi-Messenger Astrophysics.

Catching Loosely Synchronized Behavior in Face of Camouflage

no code implementations21 Oct 2018 Yikun Ban, Jiao Sun, Xin Liu

Fraud has severely detrimental impacts on the business of social networks and other online applications.

Social and Information Networks Cryptography and Security

Parallelizable Algorithms for Optimization Problems with Orthogonality Constraints

1 code implementation9 Oct 2018 Bin Gao, Xin Liu, Ya-xiang Yuan

Numerical experiments in serial illustrate that the novel updating rule for the Lagrangian multipliers significantly accelerates the convergence of PLAM and makes it comparable with the existent feasible solvers for optimization problems with orthogonality constraints, and the performance of PCAL does not highly rely on the choice of the penalty parameter.

Optimization and Control 15A18, 65F15, 65K05, 90C06

The BQ Corpus: A Large-scale Domain-specific Chinese Corpus For Sentence Semantic Equivalence Identification

no code implementations EMNLP 2018 Jing Chen, Qingcai Chen, Xin Liu, Haijun Yang, Daohe Lu, Buzhou Tang

As the largest manually annotated public Chinese SSEI corpus in the bank domain, the BQ corpus is not only useful for Chinese question semantic matching research, but also a significant resource for cross-lingual and cross-domain SSEI research.

Paraphrase Identification Question Answering

LCQMC:A Large-scale Chinese Question Matching Corpus

no code implementations COLING 2018 Xin Liu, Qingcai Chen, Chong Deng, Huajun Zeng, Jing Chen, Dongfang Li, Buzhou Tang

In this paper, we first use a search engine to collect large-scale question pairs related to high-frequency words from various domains, then filter irrelevant pairs by the Wasserstein distance, and finally recruit three annotators to manually check the left pairs.

Information Retrieval Machine Translation +2

DPatch: An Adversarial Patch Attack on Object Detectors

1 code implementation5 Jun 2018 Xin Liu, Huanrui Yang, Ziwei Liu, Linghao Song, Hai Li, Yiran Chen

Successful realization of DPatch also illustrates the intrinsic vulnerability of the modern detector architectures to such patch-based adversarial attacks.

Object Classification

CerfGAN: A Compact, Effective, Robust, and Fast Model for Unsupervised Multi-Domain Image-to-Image Translation

no code implementations28 May 2018 Xiao Liu, Shengchuan Zhang, Hong Liu, Xin Liu, Cheng Deng, Rongrong Ji

In principle, CerfGAN contains a novel component, i. e., a multi-class discriminator (MCD), which gives the model an extremely powerful ability to match multiple translation mappings.

Face Hallucination Image-to-Image Translation +1

In-Orbit Instrument Performance Study and Calibration for POLAR Polarization Measurements

1 code implementation19 May 2018 Zheng-Heng Li, Merlin Kole, Jian-Chao Sun, Li-Ming Song, Nicolas Produit, Bo-Bing Wu, Tianwei Bao, Tancredi Bernasconi, Franck Cadoux, Yongwei Dong, Minzi Feng, Neal Gauvin, Wojtek Hajdas, Hancheng Li, Lu Li, Xin Liu, Radoslaw Marcinkowski, Martin Pohl, Dominik K. Rybka, Haoli Shi, Jacek Szabelski, Teresa Tymieniecka, Ruijie Wang, Yuanhao Wang, Xing Wen, Xin Wu, Shao-Lin Xiong, Anna Zwolinska, Li Zhang, Lai-Yu Zhang, Shuang-Nan Zhang, Yong-Jie Zhang, Yi Zhao

POLAR is a compact space-borne detector designed to perform reliable measurements of the polarization for transient sources like Gamma-Ray Bursts in the energy range 50-500keV.

Instrumentation and Methods for Astrophysics High Energy Physics - Experiment Instrumentation and Detectors

MTFH: A Matrix Tri-Factorization Hashing Framework for Efficient Cross-Modal Retrieval

1 code implementation4 May 2018 Xin Liu, Zhikai Hu, Haibin Ling, Yiu-ming Cheung

More specifically, MTFH exploits an efficient objective function to flexibly learn the modality-specific hash codes with different length settings, while synchronously learning two semantic correlation matrices to semantically correlate the different hash representations for heterogeneous data comparable.

Cross-Modal Retrieval Semantic Textual Similarity

Recursive Spatial Transformer (ReST) for Alignment-Free Face Recognition

no code implementations ICCV 2017 Wanglong Wu, Meina Kan, Xin Liu, Yi Yang, Shiguang Shan, Xilin Chen

The designed ReST has an intrinsic recursive structure and is capable of progressively aligning faces to a canonical one, even those with large variations.

Face Alignment Face Recognition +1

Adaptive Exploration-Exploitation Tradeoff for Opportunistic Bandits

no code implementations ICML 2018 Huasen Wu, Xueying Guo, Xin Liu

When the load/price is low, so is the cost/regret of pulling a suboptimal arm (e. g., trying a suboptimal network configuration).

Parameter Estimation in Computational Biology by Approximate Bayesian Computation coupled with Sensitivity Analysis

1 code implementation28 Apr 2017 Xin Liu, Mahesan Niranjan

We address the problem of parameter estimation in models of systems biology from noisy observations.

Group-based Sparse Representation for Image Compressive Sensing Reconstruction with Non-Convex Regularization

no code implementations24 Apr 2017 Zhiyuan Zha, Xinggan Zhang, Qiong Wang, Lan Tang, Xin Liu

In this paper, a group-based sparse representation method with non-convex regularization (GSR-NCR) for image CS reconstruction is proposed.

Compressive Sensing Dictionary Learning

CNN based music emotion classification

no code implementations19 Apr 2017 Xin Liu, Qingcai Chen, Xiang-Ping Wu, Yan Liu, Yang Liu

Music emotion recognition (MER) is usually regarded as a multi-label tagging task, and each segment of music can inspire specific emotion tags.

Classification Emotion Classification +3

Group Sparsity Residual Constraint for Image Denoising

no code implementations1 Mar 2017 Zhiyuan Zha, Xinggan Zhang, Qiong Wang, Lan Tang, Xin Liu

Unlike the conventional group-based sparse representation denoising methods, two kinds of prior, namely, the NSS priors of noisy and pre-filtered images, are used in GSRC.

Image Denoising

Analyzing the group sparsity based on the rank minimization methods

no code implementations28 Nov 2016 Zhiyuan Zha, Xin Liu, Xiaohua Huang, Henglin Shi, Yingyue Xu, Qiong Wang, Lan Tang, Xinggan Zhang

Then, we prove that group-based sparse coding is equivalent to the rank minimization problem, and thus the sparse coefficient of each group is measured by estimating the singular values of each group.

Compressive Sensing Image Inpainting

Stroke Sequence-Dependent Deep Convolutional Neural Network for Online Handwritten Chinese Character Recognition

no code implementations13 Oct 2016 Baotian Hu, Xin Liu, Xiang-Ping Wu, Qingcai Chen

In this paper, we propose a novel model, named Stroke Sequence-dependent Deep Convolutional Neural Network (SSDCNN), using the stroke sequence information and eight-directional features for Online Handwritten Chinese Character Recognition (OLHCCR).

Image denoising via group sparsity residual constraint

no code implementations12 Sep 2016 Zhiyuan Zha, Xin Liu, Ziheng Zhou, Xiaohua Huang, Jingang Shi, Zhenhong Shang, Lan Tang, Yechao Bai, Qiong Wang, Xinggan Zhang

Group sparsity has shown great potential in various low-level vision tasks (e. g, image denoising, deblurring and inpainting).

Deblurring Image Denoising

Spontaneous Facial Micro-Expression Recognition using Discriminative Spatiotemporal Local Binary Pattern with an Improved Integral Projection

no code implementations7 Aug 2016 Xiaohua Huang, Su-Jing Wang, Xin Liu, Guoying Zhao, Xiaoyi Feng, Matti Pietikainen

For increasing the discrimination of micro-expressions, we propose a new feature selection based on Laplacian method to extract the discriminative information for facial micro-expression recognition.

Feature Selection Micro-Expression Recognition

Saliency Integration: An Arbitrator Model

no code implementations4 Aug 2016 Yingyue Xu, Xiaopeng Hong, Fatih Porikli, Xin Liu, Jie Chen, Guoying Zhao

Previous offline integration methods usually face two challenges: 1. if most of the candidate saliency models misjudge the saliency on an image, the integration result will lean heavily on those inferior candidate models; 2. an unawareness of the ground truth saliency labels brings difficulty in estimating the expertise of each candidate model.

Double Thompson Sampling for Dueling Bandits

1 code implementation NeurIPS 2016 Huasen Wu, Xin Liu

This simple algorithm applies to general Copeland dueling bandits, including Condorcet dueling bandits as its special case.

Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits

no code implementations NeurIPS 2015 Huasen Wu, R. Srikant, Xin Liu, Chong Jiang

To the best of our knowledge, this is the first work that shows how to achieve logarithmic regret in constrained contextual bandits.

Multi-Armed Bandits

The Power of Online Learning in Stochastic Network Optimization

no code implementations6 Apr 2014 Longbo Huang, Xin Liu, Xiaohong Hao

We prove strong performance guarantees of the proposed algorithms: $\mathtt{OLAC}$ and $\mathtt{OLAC2}$ achieve the near-optimal $[O(\epsilon), O([\log(1/\epsilon)]^2)]$ utility-delay tradeoff and $\mathtt{OLAC2}$ possesses an $O(\epsilon^{-2/3})$ convergence time.

Cannot find the paper you are looking for? You can Submit a new open access paper.