Search Results for author: Hao liu

Found 166 papers, 52 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 +2

One for All: Towards Training One Graph Model for All Classification Tasks

no code implementations29 Sep 2023 Hao liu, Jiarui Feng, Lecheng Kong, Ningyue Liang, DaCheng Tao, Yixin Chen, Muhan Zhang

For in-context learning on graphs, OFA introduces a novel graph prompting paradigm that appends prompting substructures to the input graph, which enables it to address varied tasks without fine-tuning.

Decision Fusion Network with Perception Fine-tuning for Defect Classification

no code implementations22 Sep 2023 Xiaoheng Jiang, Shilong Tian, Zhiwen Zhu, Yang Lu, Hao liu, Li Chen, Shupan Li, Mingliang Xu

In addition, we propose a perception fine-tuning module (PFM) that fine-tunes the foreground and background during the segmentation stage.

CINFormer: Transformer network with multi-stage CNN feature injection for surface defect segmentation

no code implementations22 Sep 2023 Xiaoheng Jiang, Kaiyi Guo, Yang Lu, Feng Yan, Hao liu, Jiale Cao, Mingliang Xu, DaCheng Tao

To address these issues, we propose a transformer network with multi-stage CNN (Convolutional Neural Network) feature injection for surface defect segmentation, which is a UNet-like structure named CINFormer.

Defect Detection

Graph Contrastive Learning Meets Graph Meta Learning: A Unified Method for Few-shot Node Tasks

1 code implementation19 Sep 2023 Hao liu, Jiarui Feng, Lecheng Kong, DaCheng Tao, Yixin Chen, Muhan Zhang

In our study, we first identify two crucial advantages of contrastive learning compared to meta learning, including (1) the comprehensive utilization of graph nodes and (2) the power of graph augmentations.

CoLA Contrastive Learning +3

Guide Your Agent with Adaptive Multimodal Rewards

1 code implementation19 Sep 2023 Changyeon Kim, Younggyo Seo, Hao liu, Lisa Lee, Jinwoo Shin, Honglak Lee, Kimin Lee

Developing an agent capable of adapting to unseen environments remains a difficult challenge in imitation learning.

Imitation Learning

Attention Where It Matters: Rethinking Visual Document Understanding with Selective Region Concentration

no code implementations ICCV 2023 Haoyu Cao, Changcun Bao, Chaohu Liu, Huang Chen, Kun Yin, Hao liu, Yinsong Liu, Deqiang Jiang, Xing Sun

We propose a novel end-to-end document understanding model called SeRum (SElective Region Understanding Model) for extracting meaningful information from document images, including document analysis, retrieval, and office automation.

document understanding Retrieval +1

Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Network

no code implementations31 Aug 2023 Weijia Zhang, Le Zhang, Jindong Han, Hao liu, Jingbo Zhou, Yu Mei, Hui Xiong

Accurate traffic forecasting at intersections governed by intelligent traffic signals is critical for the advancement of an effective intelligent traffic signal control system.

Time Series Time Series Forecasting

Connections between Operator-splitting Methods and Deep Neural Networks with Applications in Image Segmentation

no code implementations18 Jul 2023 Hao liu, Xue-Cheng Tai, Raymond Chan

In this paper, we give an algorithmic explanation for deep neural networks, especially in their connection with operator splitting and multigrid methods.

Image Segmentation Semantic Segmentation

Fine-grained Action Analysis: A Multi-modality and Multi-task Dataset of Figure Skating

no code implementations6 Jul 2023 Sheng-Lan Liu, Yu-Ning Ding, Si-Fan Zhang, Wen-Yue Chen, Ning Zhou, Hao liu, Gui-Hong Lao

MMFS, which possesses action recognition and action quality assessment, captures RGB, skeleton, and is collected the score of actions from 11671 clips with 256 categories including spatial and temporal labels.

Action Analysis Action Quality Assessment +1

A Preference-aware Meta-optimization Framework for Personalized Vehicle Energy Consumption Estimation

1 code implementation26 Jun 2023 Siqi Lai, Weijia Zhang, Hao liu

To this end, this paper proposes a preference-aware meta-optimization framework Meta-Pec for personalized vehicle energy consumption estimation.

Memorization Total Energy

UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction

1 code implementation20 Jun 2023 Yansong Ning, Hao liu, Hao Wang, Zhenyu Zeng, Hui Xiong

We hope the proposed UUKG fosters research on urban knowledge graphs and broad smart city applications.

Knowledge Graphs

Towards Arbitrarily Expressive GNNs in $O(n^2)$ Space by Rethinking Folklore Weisfeiler-Lehman

1 code implementation5 Jun 2023 Jiarui Feng, Lecheng Kong, Hao liu, DaCheng Tao, Fuhai Li, Muhan Zhang, Yixin Chen

We theoretically prove that even if we fix the space complexity to $O(n^2)$ in $(k, t)$-FWL, we can construct an expressiveness hierarchy up to solving the graph isomorphism problem.

Blockwise Parallel Transformer for Large Context Models

2 code implementations30 May 2023 Hao liu, Pieter Abbeel

Transformers have emerged as the cornerstone of state-of-the-art natural language processing models, showcasing exceptional performance across a wide range of AI applications.

Language Modelling

Emergent Agentic Transformer from Chain of Hindsight Experience

no code implementations26 May 2023 Hao liu, Pieter Abbeel

Our method consists of relabelling target return of each trajectory to the maximum total reward among in sequence of trajectories and training an autoregressive model to predict actions conditioning on past states, actions, rewards, target returns, and task completion tokens, the resulting model, Agentic Transformer (AT), can learn to improve upon itself both at training and test time.

D4RL Imitation Learning +2

The False Promise of Imitating Proprietary LLMs

1 code implementation25 May 2023 Arnav Gudibande, Eric Wallace, Charlie Snell, Xinyang Geng, Hao liu, Pieter Abbeel, Sergey Levine, Dawn Song

This approach looks to cheaply imitate the proprietary model's capabilities using a weaker open-source model.

Language Modelling

DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models

no code implementations25 May 2023 Ying Fan, Olivia Watkins, Yuqing Du, Hao liu, MoonKyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, Kimin Lee

These techniques first learn a reward function that captures what humans care about in the task and then improve the models based on the learned reward function.

reinforcement-learning Reinforcement Learning (RL)

Enhancing Short-Term Wind Speed Forecasting using Graph Attention and Frequency-Enhanced Mechanisms

no code implementations19 May 2023 Hao liu, Huimin Ma, Tianyu Hu

In this paper, a Graph-attentive Frequency-enhanced Spatial-Temporal Wind Speed Forecasting model based on graph attention and frequency-enhanced mechanisms, i. e., GFST-WSF, is proposed to improve the accuracy of short-term wind speed forecasting.

Graph Attention

Environment-Aware Codebook for Reconfigurable Intelligent Surface-Aided MISO Communications

no code implementations24 Apr 2023 Xing Jia, Jiancheng An, Hao liu, Hongshu Liao, Lu Gan, Chau Yuen

Reconfigurable intelligent surface (RIS) is a revolutionary technology that can customize the wireless channel and improve the energy efficiency of next-generation cellular networks.

A geometry-aware deep network for depth estimation in monocular endoscopy

1 code implementation20 Apr 2023 Yongming Yang, Shuwei Shao, Tao Yang, Peng Wang, Zhuo Yang, Chengdong Wu, Hao liu

To address this issue, we introduce a gradient loss to penalize edge fluctuations ambiguous around stepped edge structures and a normal loss to explicitly express the sensitivity to frequently small structures, and propose a geometric consistency loss to spreads the spatial information across the sample grids to constrain the global geometric anatomy structures.

3D Reconstruction Anatomy +1

Locate Then Generate: Bridging Vision and Language with Bounding Box for Scene-Text VQA

no code implementations4 Apr 2023 Yongxin Zhu, Zhen Liu, Yukang Liang, Xin Li, Hao liu, Changcun Bao, Linli Xu

Different to conventional STVQA models which take the linguistic semantics and visual semantics in scene text as two separate features, in this paper, we propose a paradigm of "Locate Then Generate" (LTG), which explicitly unifies this two semantics with the spatial bounding box as a bridge connecting them.

Answer Generation Language Modelling +3

A Survey on Vertical Federated Learning: From a Layered Perspective

no code implementations4 Apr 2023 Liu Yang, Di Chai, Junxue Zhang, Yilun Jin, Leye Wang, Hao liu, Han Tian, Qian Xu, Kai Chen

From the hardware layer to the vertical federated system layer, researchers contribute to various aspects of VFL.

Federated Learning Privacy Preserving

Arrhythmia Classifier Based on Ultra-Lightweight Binary Neural Network

1 code implementation4 Apr 2023 Ninghao Pu, Zhongxing Wu, Ao Wang, Hanshi Sun, Zijin Liu, Hao liu

With the development of deep learning, numerous ECG classification algorithms based on deep learning have emerged.

Binarization Classification +1

On Degeneracy Issues in Multi-parametric Programming and Critical Region Exploration based Distributed Optimization in Smart Grid Operations

no code implementations2 Apr 2023 Haitian Liu, Ye Guo, Hao liu

Improving renewable energy resource utilization efficiency is crucial to reducing carbon emissions, and multi-parametric programming has provided a systematic perspective in conducting analysis and optimization toward this goal in smart grid operations.

Distributed Optimization Scheduling

Beta-VAE has 2 Behaviors: PCA or ICA?

no code implementations25 Mar 2023 Zhouzheng Li, Hao liu

Beta-VAE is a very classical model for disentangled representation learning, the use of an expanding bottleneck that allow information into the decoder gradually is key to representation disentanglement as well as high-quality reconstruction.


GQE-Net: A Graph-based Quality Enhancement Network for Point Cloud Color Attribute

no code implementations24 Mar 2023 Jinrui Xing, Hui Yuan, Raouf Hamzaoui, Hao liu, Junhui Hou

Specifically, we use a parallel-serial graph attention module with a multi-head graph attention mechanism to focus on important points or features and help them fuse together.

Graph Attention

Deep Nonparametric Estimation of Intrinsic Data Structures by Chart Autoencoders: Generalization Error and Robustness

no code implementations17 Mar 2023 Hao liu, Alex Havrilla, Rongjie Lai, Wenjing Liao

Our paper establishes statistical guarantees on the generalization error of chart autoencoders, and we demonstrate their denoising capabilities by considering $n$ noisy training samples, along with their noise-free counterparts, on a $d$-dimensional manifold.


Grab What You Need: Rethinking Complex Table Structure Recognition with Flexible Components Deliberation

no code implementations16 Mar 2023 Hao liu, Xin Li, Mingming Gong, Bing Liu, Yunfei Wu, Deqiang Jiang, Yinsong Liu, Xing Sun

Recently, Table Structure Recognition (TSR) task, aiming at identifying table structure into machine readable formats, has received increasing interest in the community.

Window transformer for dialogue document: a joint framework for causal emotion entailment

no code implementations International Journal of Machine Learning and Cybernetics 2023 Dazhi Jiang, Hao liu, Geng Tu & Runguo Wei

The Causal Emotion Entailment (CEE) task aims to extract all potential pairs of emotions and corresponding causes from the unannotated emotion document in the conversational context.

Causal Emotion Entailment

Aligning Text-to-Image Models using Human Feedback

1 code implementation23 Feb 2023 Kimin Lee, Hao liu, MoonKyung Ryu, Olivia Watkins, Yuqing Du, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Shixiang Shane Gu

Our results demonstrate the potential for learning from human feedback to significantly improve text-to-image models.

Image Generation

Chain of Hindsight Aligns Language Models with Feedback

3 code implementations6 Feb 2023 Hao liu, Carmelo Sferrazza, Pieter Abbeel

Applying our method to large language models, we observed that Chain of Hindsight significantly surpasses previous methods in aligning language models with human preferences.

Language Quantized AutoEncoders: Towards Unsupervised Text-Image Alignment

1 code implementation2 Feb 2023 Hao liu, Wilson Yan, Pieter Abbeel

Recent progress in scaling up large language models has shown impressive capabilities in performing few-shot learning across a wide range of text-based tasks.

Few-Shot Image Classification Few-Shot Learning +2

CSAT‑FTCN: A Fuzzy‑Oriented Model with Contextual Self‑attention Network for Multimodal Emotion Recognition

no code implementations Cognitive Computation 2023 Dazhi Jiang, Hao liu, Runguo Wei, Geng Tu

Moreover, the CSAT-FTCN can obtain the dependency relationships of target utterances on internal own key information and external contextual information to understand emotions in a more profound sense.

Multimodal Emotion Recognition Question Answering

Hierarchical Prompt Learning for Multi-Task Learning

no code implementations CVPR 2023 Yajing Liu, Yuning Lu, Hao liu, Yaozu An, Zhuoran Xu, Zhuokun Yao, Baofeng Zhang, Zhiwei Xiong, Chenguang Gui

Considering this, we present Hierarchical Prompt (HiPro) learning, a simple and effective method for jointly adapting a pre-trained VLM to multiple downstream tasks.

Multi-Task Learning

Masked Autoencoding for Scalable and Generalizable Decision Making

1 code implementation23 Nov 2022 Fangchen Liu, Hao liu, Aditya Grover, Pieter Abbeel

We are interested in learning scalable agents for reinforcement learning that can learn from large-scale, diverse sequential data similar to current large vision and language models.

Decision Making Offline RL +2

Instruction-Following Agents with Multimodal Transformer

1 code implementation24 Oct 2022 Hao liu, Lisa Lee, Kimin Lee, Pieter Abbeel

Our \ours method consists of a multimodal transformer that encodes visual observations and language instructions, and a transformer-based policy that predicts actions based on encoded representations.

Instruction Following Visual Grounding

Towards Better Few-Shot and Finetuning Performance with Forgetful Causal Language Models

no code implementations24 Oct 2022 Hao liu, Xinyang Geng, Lisa Lee, Igor Mordatch, Sergey Levine, Sharan Narang, Pieter Abbeel

Large language models (LLM) trained using the next-token-prediction objective, such as GPT3 and PaLM, have revolutionized natural language processing in recent years by showing impressive zero-shot and few-shot capabilities across a wide range of tasks.

Language Modelling Natural Language Inference +1

Palm up: Playing in the Latent Manifold for Unsupervised Pretraining

no code implementations19 Oct 2022 Hao liu, Tom Zahavy, Volodymyr Mnih, Satinder Singh

In this work, we aim to bring the best of both worlds and propose an algorithm that exhibits an exploratory behavior whilst it utilizes large diverse datasets.

reinforcement-learning Reinforcement Learning (RL) +2

Practical Adversarial Attacks on Spatiotemporal Traffic Forecasting Models

2 code implementations5 Oct 2022 Fan Liu, Hao liu, Wenzhao Jiang

Remarkably, we also show that adversarial training with our proposed attacks can significantly improve the robustness of spatiotemporal traffic forecasting models.

TaCo: Textual Attribute Recognition via Contrastive Learning

no code implementations22 Aug 2022 Chang Nie, Yiqing Hu, Yanqiu Qu, Hao liu, Deqiang Jiang, Bo Ren

To realize this goal, we design the learning paradigm from three perspectives: 1) generating attribute views, 2) extracting subtle but crucial details, and 3) exploiting valued view pairs for learning, to fully unlock the pre-training potential.

Contrastive Learning

RepBNN: towards a precise Binary Neural Network with Enhanced Feature Map via Repeating

1 code implementation19 Jul 2022 Xulong Shi, Zhi Qi, Jiaxuan Cai, Keqi Fu, Yaru Zhao, Zan Li, Xuanyu Liu, Hao liu

Binary neural network (BNN) is an extreme quantization version of convolutional neural networks (CNNs) with all features and weights mapped to just 1-bit.

Binarization Quantization

Cycle Self-Training for Semi-Supervised Object Detection with Distribution Consistency Reweighting

no code implementations12 Jul 2022 Hao liu, Bin Chen, Bo wang, Chunpeng Wu, Feng Dai, Peng Wu

To address the coupling problem, we propose a Cycle Self-Training (CST) framework for SSOD, which consists of two teachers T1 and T2, two students S1 and S2.

object-detection Object Detection +1

Masked World Models for Visual Control

no code implementations28 Jun 2022 Younggyo Seo, Danijar Hafner, Hao liu, Fangchen Liu, Stephen James, Kimin Lee, Pieter Abbeel

Yet the current approaches typically train a single model end-to-end for learning both visual representations and dynamics, making it difficult to accurately model the interaction between robots and small objects.

Model-based Reinforcement Learning Reinforcement Learning (RL) +1

Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint

no code implementations9 Jun 2022 Hao liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao

Overparameterized neural networks enjoy great representation power on complex data, and more importantly yield sufficiently smooth output, which is crucial to their generalization and robustness.

Image Classification

Unbiased Implicit Feedback via Bi-level Optimization

no code implementations31 May 2022 Can Chen, Chen Ma, Xi Chen, Sirui Song, Hao liu, Xue Liu

Recent works reveal a huge gap between the implicit feedback and user-item relevance due to the fact that implicit feedback is also closely related to the item exposure.

Recommendation Systems

Multimodal Masked Autoencoders Learn Transferable Representations

1 code implementation27 May 2022 Xinyang Geng, Hao liu, Lisa Lee, Dale Schuurmans, Sergey Levine, Pieter Abbeel

We provide an empirical study of M3AE trained on a large-scale image-text dataset, and find that M3AE is able to learn generalizable representations that transfer well to downstream tasks.

Contrastive Learning

A Fine-grained Interpretability Evaluation Benchmark for Neural NLP

no code implementations23 May 2022 Lijie Wang, Yaozong Shen, Shuyuan Peng, Shuai Zhang, Xinyan Xiao, Hao liu, Hongxuan Tang, Ying Chen, Hua Wu, Haifeng Wang

Based on this benchmark, we conduct experiments on three typical models with three saliency methods, and unveil their strengths and weakness in terms of interpretability.

Reading Comprehension Sentiment Analysis

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

1 code implementation 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

1 code implementation1 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 +2

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

Contextual Debiasing for Visual Recognition With Causal Mechanisms

no code implementations CVPR 2022 Ruyang Liu, Hao liu, Ge Li, Haodi Hou, TingHao Yu, Tao Yang

As a common problem in the visual world, contextual bias means the recognition may depend on the co-occurrence context rather than the objects themselves, which is even more severe in multi-label tasks due to multiple targets and the absence of location.

Causal Inference Multi-Label Classification

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.

reinforcement-learning Reinforcement Learning (RL)

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 implementations CVPR 2022 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.

Table Recognition

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.

Matrix Completion Moving Object Detection +2

NomMer: Nominate Synergistic Context in Vision Transformer for Visual Recognition

1 code implementation CVPR 2022 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 Object Detection +1

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 +2

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

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.

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

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.

Binary Classification

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 (RL)

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.

Model Optimization 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 +1

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).

point of interests

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 +3

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 feature selection +2

Identifying and Tracking Solar Magnetic Flux Elements with Deep Learning

4 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.

Image Segmentation 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.

Image Segmentation Point Cloud Segmentation +1

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.

Semantic Segmentation

SKEP: Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis

6 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 +1

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

3 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 Analysis

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.

Open-Ended Question Answering regression

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

Reinforcement Learning Tracking Control for Robotic Manipulator With Kernel-Based Dynamic Model

no code implementations TRANSACTION 2020 Yazhou Hu, Wenxue Wang, Hao liu, and Lianqing Liu, Member, IEEE

In this algorithm, a reward function is defined according to the features of tracking control in order to speed up the learning process, and then an RL tracking controller with a kernel-based transition dynamic model is proposed.

Continuous Control reinforcement-learning +1

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 +3

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 Relational Reasoning

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.

Multi-Armed Bandits Off-policy evaluation +1

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.

Instruction Following 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.

Solar Flare Prediction Time Series Analysis

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.

reinforcement-learning Reinforcement Learning (RL)

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 +1

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 +2

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.

BIG-bench Machine Learning

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 +1

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

5 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 +1

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