Search Results for author: Hao liu

Found 107 papers, 29 papers with code

MABNet: A Lightweight Stereo Network Based on Multibranch Adjustable Bottleneck Module

no code implementations ECCV 2020 Jiabin Xing, Zhi Qi, Jiying Dong, Jiaxuan Cai, Hao liu

MABNet is based on a novel Multibranch Adjustable Bottleneck (MAB) module, which is less demanding on parameters and computation.

Disparity Estimation

Diversified Multiple Instance Learning for Document-Level Multi-Aspect Sentiment Classification

no code implementations EMNLP 2020 Yunjie Ji, Hao liu, Bolei He, Xinyan Xiao, Hua Wu, Yanhua Yu

To this end, we propose a novel Diversified Multiple Instance Learning Network (D-MILN), which is able to achieve aspect-level sentiment classification with only document-level weak supervision.

General Classification Multiple Instance Learning +1

Arrhythmia Classifier using Binarized Convolutional Neural Network for Resource-Constrained Devices

1 code implementation7 May 2022 Ao Wang, Wenxing Xu, Hanshi Sun, Ninghao Pu, Zijin Liu, Hao liu

In this paper, a binarized convolutional neural network suitable for ECG monitoring is proposed, which is hardware-friendly and more suitable for use in resource-constrained wearable devices.

The Devil is in the Frequency: Geminated Gestalt Autoencoder for Self-Supervised Visual Pre-Training

no code implementations18 Apr 2022 Hao liu, Xinghua Jiang, Xin Li, Antai Guo, Deqiang Jiang, Bo Ren

The self-supervised Masked Image Modeling (MIM) schema, following "mask-and-reconstruct" pipeline of recovering contents from masked image, has recently captured the increasing interest in the multimedia community, owing to the excellent ability of learning visual representation from unlabeled data.

Predicting Solar Energetic Particles Using SDO/HMI Vector Magnetic Data Products and a Bidirectional LSTM Network

no code implementations27 Mar 2022 Yasser Abduallah, Vania K. Jordanova, Hao liu, Qin Li, Jason T. L. Wang, Haimin Wang

Solar energetic particles (SEPs) are an essential source of space radiation, which are hazards for humans in space, spacecraft, and technology in general.

Joint Covering Congestion Rents in Multi-area Power Systems Considering Loop Flow Effects

no code implementations23 Mar 2022 Hao liu, Ye Guo, Haitian Liu, Hongbin Sun

We consider the problem of how multiple areas should jointly cover congestion rents of internal and tie-lines in an interconnected power system.

Elastica Models for Color Image Regularization

no code implementations18 Mar 2022 Hao liu, Xue-Cheng Tai, Ron Kimmel, Roland Glowinski

Recently, the authors proposed a color elastica model, which minimizes both the surface area and elastica of the image manifold.

UNIMO-2: End-to-End Unified Vision-Language Grounded Learning

no code implementations Findings (ACL) 2022 Wei Li, Can Gao, guocheng niu, Xinyan Xiao, Hao liu, Jiachen Liu, Hua Wu, Haifeng Wang

In particular, we propose to conduct grounded learning on both images and texts via a sharing grounded space, which helps bridge unaligned images and texts, and align the visual and textual semantic spaces on different types of corpora.

PUFA-GAN: A Frequency-Aware Generative Adversarial Network for 3D Point Cloud Upsampling

no code implementations2 Mar 2022 Hao liu, Hui Yuan, Junhui Hou, Raouf Hamzaoui, Wei Gao

We propose a generative adversarial network for point cloud upsampling, which can not only make the upsampled points evenly distributed on the underlying surface but also efficiently generate clean high frequency regions.

Network resilience in the aging brain

no code implementations3 Feb 2022 Tao Liu, Shu Guo, Hao liu, Rui Kang, Mingyang Bai, Jiyang Jiang, Wei Wen, Xing Pan, Jun Tai, JianXin Li, Jian Cheng, Jing Jing, Zhenzhou Wu, Haijun Niu, Haogang Zhu, Zixiao Li, Yongjun Wang, Henry Brodaty, Perminder Sachdev, Daqing Li

Degeneration and adaptation are two competing sides of the same coin called resilience in the progressive processes of brain aging or diseases.

CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery

no code implementations1 Feb 2022 Michael Laskin, Hao liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel

We introduce Contrastive Intrinsic Control (CIC), an algorithm for unsupervised skill discovery that maximizes the mutual information between state-transitions and latent skill vectors.

Contrastive Learning reinforcement-learning +1

Continual Learning with Recursive Gradient Optimization

no code implementations ICLR 2022 Hao liu, Huaping Liu

Learning multiple tasks sequentially without forgetting previous knowledge, called Continual Learning(CL), remains a long-standing challenge for neural networks.

Continual Learning

Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces

no code implementations1 Jan 2022 Hao liu, Haizhao Yang, Minshuo Chen, Tuo Zhao, Wenjing Liao

Learning operators between infinitely dimensional spaces is an important learning task arising in wide applications in machine learning, imaging science, mathematical modeling and simulations, etc.

Learning to Walk with Dual Agents for Knowledge Graph Reasoning

1 code implementation23 Dec 2021 Denghui Zhang, Zixuan Yuan, Hao liu, Xiaodong Lin, Hui Xiong

Graph walking based on reinforcement learning (RL) has shown great success in navigating an agent to automatically complete various reasoning tasks over an incomplete knowledge graph (KG) by exploring multi-hop relational paths.


Domain-oriented Language Pre-training with Adaptive Hybrid Masking and Optimal Transport Alignment

no code implementations1 Dec 2021 Denghui Zhang, Zixuan Yuan, Yanchi Liu, Hao liu, Fuzhen Zhuang, Hui Xiong, Haifeng Chen

Also, the word co-occurrences guided semantic learning of pre-training models can be largely augmented by entity-level association knowledge.

Entity Alignment

Generalized DataWeighting via Class-Level Gradient Manipulation

1 code implementation NeurIPS 2021 Can Chen, Shuhao Zheng, Xi Chen, Erqun Dong, Xue (Steve) Liu, Hao liu, Dejing Dou

To be specific, GDW unrolls the loss gradient to class-level gradients by the chain rule and reweights the flow of each gradient separately.

Neural Collaborative Graph Machines for Table Structure Recognition

no code implementations26 Nov 2021 Hao liu, Xin Li, Bing Liu, Deqiang Jiang, Yinsong Liu, Bo Ren

We also show that the proposed NCGM can modulate collaborative pattern of different modalities conditioned on the context of intra-modality cues, which is vital for diversified table cases.

Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark

1 code implementation25 Nov 2021 Qian Yin, Qingyong Hu, Hao liu, Feng Zhang, Yingqian Wang, Zaiping Lin, Wei An, Yulan Guo

Satellite video cameras can provide continuous observation for a large-scale area, which is important for many remote sensing applications.

Frame Matrix Completion +2

NomMer: Nominate Synergistic Context in Vision Transformer for Visual Recognition

1 code implementation25 Nov 2021 Hao liu, Xinghua Jiang, Xin Li, Zhimin Bao, Deqiang Jiang, Bo Ren

For the sake of trade-off between efficiency and performance, a group of works merely perform SA operation within local patches, whereas the global contextual information is abandoned, which would be indispensable for visual recognition tasks.

Object Detection Semantic Segmentation

Enhanced Fast Boolean Matching based on Sensitivity Signatures Pruning

no code implementations11 Nov 2021 Jiaxi Zhang, Liwei Ni, Shenggen Zheng, Hao liu, Xiangfu Zou, Feng Wang, Guojie Luo

In this paper, we introduce Boolean sensitivity into Boolean matching and design several sensitivity-related signatures to enhance fast Boolean matching.

Generalized Data Weighting via Class-level Gradient Manipulation

1 code implementation29 Oct 2021 Can Chen, Shuhao Zheng, Xi Chen, Erqun Dong, Xue Liu, Hao liu, Dejing Dou

To be specific, GDW unrolls the loss gradient to class-level gradients by the chain rule and reweights the flow of each gradient separately.

URLB: Unsupervised Reinforcement Learning Benchmark

1 code implementation28 Oct 2021 Michael Laskin, Denis Yarats, Hao liu, Kimin Lee, Albert Zhan, Kevin Lu, Catherine Cang, Lerrel Pinto, Pieter Abbeel

Deep Reinforcement Learning (RL) has emerged as a powerful paradigm to solve a range of complex yet specific control tasks.

Continuous Control reinforcement-learning +1

Emoji-aware Co-attention Network with EmoGraph2vec Model for Sentiment Anaylsis

no code implementations27 Oct 2021 Xiaowei Yuan, Jingyuan Hu, Xiaodan Zhang, Honglei Lv, Hao liu

In this work, we propose a method to learn emoji representations called EmoGraph2vec and design an emoji-aware co-attention network that learns the mutual emotional semantics between text and emojis on short texts of social media.

Representation Learning Sentiment Analysis +1

Emoji-based Co-attention Network for Microblog Sentiment Analysis

no code implementations27 Oct 2021 Xiaowei Yuan, Jingyuan Hu, Xiaodan Zhang, Honglei Lv, Hao liu

In this paper, we propose an emoji-based co-attention network that learns the mutual emotional semantics between text and emojis on microblogs.

Sentiment Analysis

Spatial-Temporal Transformer for 3D Point Cloud Sequences

no code implementations19 Oct 2021 Yimin Wei, Hao liu, TingTing Xie, Qiuhong Ke, Yulan Guo

We test the effectiveness our PST2 with two different tasks on point cloud sequences, i. e., 4D semantic segmentation and 3D action recognition.

3D Action Recognition Semantic Segmentation

Scaling Fair Learning to Hundreds of Intersectional Groups

no code implementations29 Sep 2021 Eric Zhao, De-An Huang, Hao liu, Zhiding Yu, Anqi Liu, Olga Russakovsky, Anima Anandkumar

In real-world applications, however, there are multiple protected attributes yielding a large number of intersectional protected groups.

Fairness Knowledge Distillation

There are free lunches

no code implementations29 Sep 2021 Zhuoran Xu, Hao liu, Bo Dong

In this paper we propose a novel idea, "There are free lunches" (TAFL) Theorem, which states that some algorithms can achieve the best performance in all possible tasks, in the condition that tasks are given in a specific order.

A Multimodal Sentiment Dataset for Video Recommendation

no code implementations17 Sep 2021 Hongxuan Tang, Hao liu, Xinyan Xiao, Hua Wu

Based on this, we propose a multimodal sentiment analysis dataset, named baiDu Video Sentiment dataset (DuVideoSenti), and introduce a new sentiment system which is designed to describe the sentimental style of a video on recommendation scenery.

Multimodal Sentiment Analysis Video Understanding

Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks

no code implementations7 Sep 2021 Hao liu, Minshuo Chen, Tuo Zhao, Wenjing Liao

Most of existing statistical theories on deep neural networks have sample complexities cursed by the data dimension and therefore cannot well explain the empirical success of deep learning on high-dimensional data.

DuTrust: A Sentiment Analysis Dataset for Trustworthiness Evaluation

no code implementations30 Aug 2021 Lijie Wang, Hao liu, Shuyuan Peng, Hongxuan Tang, Xinyan Xiao, Ying Chen, Hua Wu, Haifeng Wang

Therefore, in order to systematically evaluate the factors for building trustworthy systems, we propose a novel and well-annotated sentiment analysis dataset to evaluate robustness and interpretability.

Sentiment Analysis

Knowledge accumulating: The general pattern of learning

no code implementations9 Aug 2021 Zhuoran Xu, Hao liu

Artificial Intelligence has been developed for decades with the achievement of great progress.

Image Classification reinforcement-learning

An Operator-Splitting Method for the Gaussian Curvature Regularization Model with Applications to Surface Smoothing and Imaging

no code implementations4 Aug 2021 Hao liu, Xue-Cheng Tai, Roland Glowinski

In our method, we decouple the full nonlinearity of Gaussian curvature from differential operators by introducing two matrix- and vector-valued functions.

Image Denoising

MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal

no code implementations12 Jul 2021 Weijia Zhang, Hao liu, Lijun Zha, HengShu Zhu, Ji Liu, Dejing Dou, Hui Xiong

Real estate appraisal refers to the process of developing an unbiased opinion for real property's market value, which plays a vital role in decision-making for various players in the marketplace (e. g., real estate agents, appraisers, lenders, and buyers).

Decision Making Graph Representation Learning +1

Multi-Agent Cooperative Bidding Games for Multi-Objective Optimization in e-Commercial Sponsored Search

no code implementations8 Jun 2021 Ziyu Guan, Hongchang Wu, Qingyu Cao, Hao liu, Wei Zhao, Sheng Li, Cai Xu, Guang Qiu, Jian Xu, Bo Zheng

Although a few studies use multi-agent reinforcement learning to set up a cooperative game, they still suffer the following drawbacks: (1) They fail to avoid collusion solutions where all the advertisers involved in an auction collude to bid an extremely low price on purpose.

Multi-agent Reinforcement Learning

JIZHI: A Fast and Cost-Effective Model-As-A-Service System for Web-Scale Online Inference at Baidu

1 code implementation3 Jun 2021 Hao liu, Qian Gao, Jiang Li, Xiaochao Liao, Hao Xiong, Guangxing Chen, Wenlin Wang, Guobao Yang, Zhiwei Zha, daxiang dong, Dejing Dou, Haoyi Xiong

In this work, we present JIZHI - a Model-as-a-Service system - that per second handles hundreds of millions of online inference requests to huge deep models with more than trillions of sparse parameters, for over twenty real-time recommendation services at Baidu, Inc.

Recommendation Systems

Multi-modal Trajectory Prediction for Autonomous Driving with Semantic Map and Dynamic Graph Attention Network

no code implementations30 Mar 2021 Bo Dong, Hao liu, Yu Bai, Jinbiao Lin, Zhuoran Xu, Xinyu Xu, Qi Kong

Predicting future trajectories of surrounding obstacles is a crucial task for autonomous driving cars to achieve a high degree of road safety.

Autonomous Driving Graph Attention +1

Intelligent Electric Vehicle Charging Recommendation Based on Multi-Agent Reinforcement Learning

1 code implementation15 Feb 2021 Weijia Zhang, Hao liu, Fan Wang, Tong Xu, Haoran Xin, Dejing Dou, Hui Xiong

Electric Vehicle (EV) has become a preferable choice in the modern transportation system due to its environmental and energy sustainability.

Multi-agent Reinforcement Learning reinforcement-learning

Out-of-Town Recommendation with Travel Intention Modeling

1 code implementation29 Jan 2021 Haoran Xin, Xinjiang Lu, Tong Xu, Hao liu, Jingjing Gu, Dejing Dou, Hui Xiong

Second, a user-specific travel intention is formulated as an aggregation combining home-town preference and generic travel intention together, where the generic travel intention is regarded as a mixture of inherent intentions that can be learned by Neural Topic Model (NTM).

CoordiQ : Coordinated Q-learning for Electric Vehicle Charging Recommendation

no code implementations28 Jan 2021 Carter Blum, Hao liu, Hui Xiong

Electric vehicles have been rapidly increasing in usage, but stations to charge them have not always kept up with demand, so efficient routing of vehicles to stations is critical to operating at maximum efficiency.

Decision Making Q-Learning +1

Out-of-distribution Prediction with Invariant Risk Minimization: The Limitation and An Effective Fix

no code implementations16 Jan 2021 Ruocheng Guo, Pengchuan Zhang, Hao liu, Emre Kiciman

Nevertheless, we find that the performance of IRM can be dramatically degraded under \emph{strong $\Lambda$ spuriousness} -- when the spurious correlation between the spurious features and the class label is strong due to the strong causal influence of their common cause, the domain label, on both of them (see Fig.

Spatial Object Recommendation with Hints: When Spatial Granularity Matters

no code implementations8 Jan 2021 Hui Luo, Jingbo Zhou, Zhifeng Bao, Shuangli Li, J. Shane Culpepper, Haochao Ying, Hao liu, Hui Xiong

We design a novel multi-task learning model called MPR (short for Multi-level POI Recommendation), where each task aims to return the top-k POIs at a certain spatial granularity level.

Multi-Task Learning Representation Learning

Unsupervised Active Pre-Training for Reinforcement Learning

no code implementations1 Jan 2021 Hao liu, Pieter Abbeel

On DMControl suite, APT beats all baselines in terms of asymptotic performance and data efficiency and dramatically improves performance on tasks that are extremely difficult for training from scratch.

Atari Games Contrastive Learning +2

Statistics of non-polarized points in the CMB polarization maps

no code implementations31 Dec 2020 Jaan Kasak, James Creswell, Hao liu, Pavel Naselsky

We show that the total number density of non-polarized points of the E- and B-families is closely related to the presence of lensing and the tensor-to-scalar ratio $r$.

Cosmology and Nongalactic Astrophysics

Joint Air Quality and Weather Prediction Based on Multi-Adversarial Spatiotemporal Networks

no code implementations30 Dec 2020 Jindong Han, Hao liu, HengShu Zhu, Hui Xiong, Dejing Dou

Specifically, we first propose a heterogeneous recurrent graph neural network to model the spatiotemporal autocorrelation among air quality and weather monitoring stations.

Graph Learning Multi-Task Learning

Magnetoelectric coupling and decoupling in multiferroic hexagonal YbFeO3 thin films

no code implementations13 Nov 2020 Yu Yun, Xin Li, Arashdeep Singh Thind, Yuewei Yin, Hao liu, Qiang Li, Wenbin Wang, Alpha T. N Diaye, Corbyn Mellinger, Xuanyuan Jiang, Rohan Mishra, Xiaoshan Xu

The coupling between ferroelectric and magnetic orders in multiferroic materials and the nature of magnetoelectric (ME) effects are enduring experimental challenges.

Materials Science Other Condensed Matter

Doubly Robust Off-Policy Learning on Low-Dimensional Manifolds by Deep Neural Networks

no code implementations3 Nov 2020 Minshuo Chen, Hao liu, Wenjing Liao, Tuo Zhao

Our theory shows that deep neural networks are adaptive to the low-dimensional geometric structures of the covariates, and partially explains the success of deep learning for causal inference.

Causal Inference

Interactive Reinforcement Learning for Feature Selection with Decision Tree in the Loop

no code implementations2 Oct 2020 Wei Fan, Kunpeng Liu, Hao liu, Yong Ge, Hui Xiong, Yanjie Fu

In this journal version, we propose a novel interactive and closed-loop architecture to simultaneously model interactive reinforcement learning (IRL) and decision tree feedback (DTF).

Feature Importance reinforcement-learning

AutoFS: Automated Feature Selection via Diversity-aware Interactive Reinforcement Learning

no code implementations27 Aug 2020 Wei Fan, Kunpeng Liu, Hao liu, Pengyang Wang, Yong Ge, Yanjie Fu

Motivated by such a computational dilemma, this study is to develop a novel feature space navigation method.


Identifying and Tracking Solar Magnetic Flux Elements with Deep Learning

3 code implementations27 Aug 2020 Haodi Jiang, Jiasheng Wang, Chang Liu, Ju Jing, Hao liu, Jason T. L. Wang, Haimin Wang

Deep learning has drawn a lot of interest in recent years due to its effectiveness in processing big and complex observational data gathered from diverse instruments.

Semantic Segmentation

A Color Elastica Model for Vector-Valued Image Regularization

no code implementations19 Aug 2020 Hao Liu, Xue-Cheng Tai, Ron Kimmel, Roland Glowinski

Here, we introduce an addition to the Polyakov action for color images that minimizes the color manifold curvature.

Semantic Context Encoding for Accurate 3D Point Cloud Segmentation

no code implementations IEEE 2020 Hao liu, Y ulan Guo, Y anni Ma, Yinjie Lei, and Gongjian Wen

In this paper, we propose a simple yet effective Point Context Encoding (PointCE) module to capture semantic contexts of a point cloud and adaptively highlight intermediate feature maps.

Hybrid Discriminative-Generative Training via Contrastive Learning

1 code implementation17 Jul 2020 Hao Liu, Pieter Abbeel

In this paper we show that through the perspective of hybrid discriminative-generative training of energy-based models we can make a direct connection between contrastive learning and supervised learning.

Contrastive Learning Out-of-Distribution Detection

Polestar: An Intelligent, Efficient and National-Wide Public Transportation Routing Engine

no code implementations11 Jul 2020 Hao Liu, Ying Li, Yanjie Fu, Huaibo Mei, Jingbo Zhou, Xu Ma, Hui Xiong

Then, we introduce a general route search algorithm coupled with an efficient station binding method for efficient route candidate generation.

Global context reasoning for semantic segmentation of 3d point clouds

no code implementations IEEE 2020 Y anni Ma, Y ulan Guo, Hao liu, Yinjie Lei

In this paper, we propose a Point Global Context Reasoning (PointGCR) module to capture global contextual information along the channel dimension.

SKEP: Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis

5 code implementations ACL 2020 Hao Tian, Can Gao, Xinyan Xiao, Hao liu, Bolei He, Hua Wu, Haifeng Wang, Feng Wu

In particular, the prediction of aspect-sentiment pairs is converted into multi-label classification, aiming to capture the dependency between words in a pair.

Multi-Label Classification Sentiment Analysis

Inferring Vector Magnetic Fields from Stokes Profiles of GST/NIRIS Using a Convolutional Neural Network

no code implementations8 May 2020 Hao Liu, Yan Xu, Jiasheng Wang, Ju Jing, Chang Liu, Jason T. L. Wang, Haimin Wang

By learning the latent patterns in the training data prepared by the physics-based ME tool, the proposed CNN method is able to infer vector magnetic fields from the Stokes profiles of GST/NIRIS.

Solar and Stellar Astrophysics

PuzzleNet: Scene Text Detection by Segment Context Graph Learning

no code implementations26 Feb 2020 Hao Liu, Antai Guo, Deqiang Jiang, Yiqing Hu, Bo Ren

Recently, a series of decomposition-based scene text detection methods has achieved impressive progress by decomposing challenging text regions into pieces and linking them in a bottom-up manner.

Graph Learning Scene Text Detection

Predicting Coronal Mass Ejections Using SDO/HMI Vector Magnetic Data Products and Recurrent Neural Networks

2 code implementations22 Feb 2020 Hao Liu, Chang Liu, Jason T. L. Wang, Haimin Wang

We present two recurrent neural networks (RNNs), one based on gated recurrent units and the other based on long short-term memory, for predicting whether an active region (AR) that produces an M- or X-class flare will also produce a coronal mass ejection (CME).

Time Series

Curvature Regularized Surface Reconstruction from Point Cloud

no code implementations22 Jan 2020 Yuchen He, Sung Ha Kang, Hao Liu

We propose a variational functional and fast algorithms to reconstruct implicit surface from point cloud data with a curvature constraint.

Surface Reconstruction

Learning functions varying along a central subspace

no code implementations22 Jan 2020 Hao Liu, Wenjing Liao

The estimation error of this variance quantity is also given in this paper.

Deep Learning for 3D Point Clouds: A Survey

3 code implementations27 Dec 2019 Yulan Guo, Hanyun Wang, Qingyong Hu, Hao liu, Li Liu, Mohammed Bennamoun

To stimulate future research, this paper presents a comprehensive review of recent progress in deep learning methods for point clouds.

3D Object Detection 3D Shape Classification +2

A Comprehensive Study and Comparison of Core Technologies for MPEG 3D Point Cloud Compression

no code implementations20 Dec 2019 Hao Liu, Hui Yuan, Qi Liu, Junhui Hou, Ju Liu

Point cloud based 3D visual representation is becoming popular due to its ability to exhibit the real world in a more comprehensive and immersive way.

Towards Omni-Supervised Face Alignment for Large Scale Unlabeled Videos

no code implementations16 Dec 2019 Congcong Zhu, Hao liu, Zhenhua Yu, Xuehong Sun

In this paper, we propose a spatial-temporal relational reasoning networks (STRRN) approach to investigate the problem of omni-supervised face alignment in videos.

Face Alignment Frame +1

Semi-Supervised Hierarchical Recurrent Graph Neural Network for City-Wide Parking Availability Prediction

1 code implementation24 Nov 2019 Weijia Zhang, Hao liu, Yanchi Liu, Jingbo Zhou, Hui Xiong

However, it is a non-trivial task for predicting citywide parking availability because of three major challenges: 1) the non-Euclidean spatial autocorrelation among parking lots, 2) the dynamic temporal autocorrelation inside of and between parking lots, and 3) the scarcity of information about real-time parking availability obtained from real-time sensors (e. g., camera, ultrasonic sensor, and GPS).

Triply Robust Off-Policy Evaluation

no code implementations13 Nov 2019 Anqi Liu, Hao liu, Anima Anandkumar, Yisong Yue

Ours is a general approach that can be used to augment any existing OPE method that utilizes the direct method.

Frame Multi-Armed Bandits

Guided Adaptive Credit Assignment for Sample Efficient Policy Optimization

no code implementations25 Sep 2019 Hao liu, Richard Socher, Caiming Xiong

In this work, we propose a guided adaptive credit assignment method to do effectively credit assignment for policy gradient methods.

Policy Gradient Methods

Dense Scale Network for Crowd Counting

1 code implementation24 Jun 2019 Feng Dai, Hao liu, Yike Ma, Juan Cao, Qiang Zhao, Yongdong Zhang

The key component of our network is the dense dilated convolution block, in which each dilation layer is densely connected with the others to preserve information from continuously varied scales.

Crowd Counting

Predicting Solar Flares Using a Long Short-Term Memory Network

2 code implementations17 May 2019 Hao Liu, Chang Liu, Jason T. L. Wang, Haimin Wang

The essence of our approach is to model data samples in an AR as time series and use LSTMs to capture temporal information of the data samples.

14 Time Series

Learning to Search Efficient DenseNet with Layer-wise Pruning

no code implementations ICLR 2019 Xuanyang Zhang, Hao liu, Zhanxing Zhu, Zenglin Xu

Deep neural networks have achieved outstanding performance in many real-world applications with the expense of huge computational resources.

Competitive Experience Replay

no code implementations ICLR 2019 Hao Liu, Alexander Trott, Richard Socher, Caiming Xiong

We propose a novel method called competitive experience replay, which efficiently supplements a sparse reward by placing learning in the context of an exploration competition between a pair of agents.


Sequence-based Person Attribute Recognition with Joint CTC-Attention Model

no code implementations20 Nov 2018 Hao Liu, Jingjing Wu, Jianguo Jiang, Meibin Qi, Bo Ren

Attribute recognition has become crucial because of its wide applications in many computer vision tasks, such as person re-identification.

Object Recognition Person Re-Identification

Variational Inference with Tail-adaptive f-Divergence

1 code implementation NeurIPS 2018 Dilin Wang, Hao liu, Qiang Liu

Variational inference with {\alpha}-divergences has been widely used in modern probabilistic machine learning.

Variational Inference

Shrinkage-based Bias-Variance Trade-off for Deep Reinforcement Learning

no code implementations27 Sep 2018 Yihao Feng, Hao liu, Jian Peng, Qiang Liu

Deep reinforcement learning has achieved remarkable successes in solving various challenging artificial intelligence tasks.

Continuous Control reinforcement-learning

Pattern-revising Enhanced Simple Question Answering over Knowledge Bases

no code implementations COLING 2018 Yanchao Hao, Hao liu, Shizhu He, Kang Liu, Jun Zhao

Question Answering over Knowledge Bases (KB-QA), which automatically answer natural language questions based on the facts contained by a knowledge base, is one of the most important natural language processing (NLP) tasks.

Entity Linking Fact Selection +1

Large-scale Bisample Learning on ID Versus Spot Face Recognition

no code implementations8 Jun 2018 Xiangyu Zhu, Hao liu, Zhen Lei, Hailin Shi, Fan Yang, Dong Yi, Guo-Jun Qi, Stan Z. Li

In this paper, we propose a deep learning based large-scale bisample learning (LBL) method for IvS face recognition.

Face Recognition General Classification

On Connecting Stochastic Gradient MCMC and Differential Privacy

no code implementations25 Dec 2017 Bai Li, Changyou Chen, Hao liu, Lawrence Carin

Significant success has been realized recently on applying machine learning to real-world applications.

N-gram Model for Chinese Grammatical Error Diagnosis

no code implementations WS 2017 Jianbo Zhao, Hao liu, Zuyi Bao, Xiaopeng Bai, Si Li, Zhiqing Lin

Detection and correction of Chinese grammatical errors have been two of major challenges for Chinese automatic grammatical error diagnosis. This paper presents an N-gram model for automatic detection and correction of Chinese grammatical errors in NLPTEA 2017 task.

Language Modelling

Action-depedent Control Variates for Policy Optimization via Stein's Identity

2 code implementations30 Oct 2017 Hao Liu, Yihao Feng, Yi Mao, Dengyong Zhou, Jian Peng, Qiang Liu

Policy gradient methods have achieved remarkable successes in solving challenging reinforcement learning problems.

Policy Gradient Methods reinforcement-learning

Deep Learning for Case-Based Reasoning through Prototypes: A Neural Network that Explains Its Predictions

3 code implementations13 Oct 2017 Oscar Li, Hao liu, Chaofan Chen, Cynthia Rudin

This architecture contains an autoencoder and a special prototype layer, where each unit of that layer stores a weight vector that resembles an encoded training input.

General Classification

Triangle Generative Adversarial Networks

1 code implementation NeurIPS 2017 Zhe Gan, Liqun Chen, Wei-Yao Wang, Yunchen Pu, Yizhe Zhang, Hao liu, Chunyuan Li, Lawrence Carin

The generators are designed to learn the two-way conditional distributions between the two domains, while the discriminators implicitly define a ternary discriminative function, which is trained to distinguish real data pairs and two kinds of fake data pairs.

Image-to-Image Translation Semi-Supervised Image Classification +1

ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching

5 code implementations NeurIPS 2017 Chunyuan Li, Hao liu, Changyou Chen, Yunchen Pu, Liqun Chen, Ricardo Henao, Lawrence Carin

We investigate the non-identifiability issues associated with bidirectional adversarial training for joint distribution matching.

Stochastic Sequential Neural Networks with Structured Inference

no code implementations24 May 2017 Hao Liu, Haoli Bai, Lirong He, Zenglin Xu

Inheriting these advantages of stochastic neural sequential models, we propose a structured and stochastic sequential neural network, which models both the long-term dependencies via recurrent neural networks and the uncertainty in the segmentation and labels via discrete random variables.

Medical Diagnosis Time Series

Multi-View Image Generation from a Single-View

no code implementations17 Apr 2017 Bo Zhao, Xiao Wu, Zhi-Qi Cheng, Hao liu, Zequn Jie, Jiashi Feng

This paper addresses a challenging problem -- how to generate multi-view cloth images from only a single view input.

Image Generation Variational Inference

Learning Policies for Markov Decision Processes from Data

no code implementations21 Jan 2017 Manjesh K. Hanawal, Hao liu, Henghui Zhu, Ioannis Ch. Paschalidis

We assume that the policy belongs to a class of parameterized policies which are defined using features associated with the state-action pairs.

Robot Navigation

Recurrent Image Captioner: Describing Images with Spatial-Invariant Transformation and Attention Filtering

no code implementations15 Dec 2016 Hao Liu, Yang Yang, Fumin Shen, Lixin Duan, Heng Tao Shen

Along with the prosperity of recurrent neural network in modelling sequential data and the power of attention mechanism in automatically identify salient information, image captioning, a. k. a., image description, has been remarkably advanced in recent years.

Image Captioning Variational Inference

Panoptic Studio: A Massively Multiview System for Social Interaction Capture

1 code implementation9 Dec 2016 Hanbyul Joo, Tomas Simon, Xulong Li, Hao liu, Lei Tan, Lin Gui, Sean Banerjee, Timothy Godisart, Bart Nabbe, Iain Matthews, Takeo Kanade, Shohei Nobuhara, Yaser Sheikh

The core challenges in capturing social interactions are: (1) occlusion is functional and frequent; (2) subtle motion needs to be measured over a space large enough to host a social group; (3) human appearance and configuration variation is immense; and (4) attaching markers to the body may prime the nature of interactions.

End-to-End Comparative Attention Networks for Person Re-identification

no code implementations14 Jun 2016 Hao Liu, Jiashi Feng, Meibin Qi, Jianguo Jiang, Shuicheng Yan

The CAN model is able to learn which parts of images are relevant for discerning persons and automatically integrates information from different parts to determine whether a pair of images belongs to the same person.

Person Re-Identification

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