Search Results for author: Hao Wu

Found 118 papers, 27 papers with code

A Meta-framework for Spatiotemporal Quantity Extraction from Text

no code implementations ACL 2022 Qiang Ning, Ben Zhou, Hao Wu, Haoruo Peng, Chuchu Fan, Matt Gardner

News events are often associated with quantities (e. g., the number of COVID-19 patients or the number of arrests in a protest), and it is often important to extract their type, time, and location from unstructured text in order to analyze these quantity events.

Vision Learners Meet Web Image-Text Pairs

no code implementations17 Jan 2023 Bingchen Zhao, Quan Cui, Hao Wu, Osamu Yoshie, Cheng Yang

First, we conduct a benchmark study of representative SSL pre-training methods on large-scale web data in a fair condition.

Self-Supervised Learning Transfer Learning

Online Handbook of Argumentation for AI: Volume 3

no code implementations15 Dec 2022 Lars Bengel, Elfia Bezou-Vrakatseli, Lydia Blümel, Federico Castagna, Giulia D'Agostino, Daphne Odekerken, Minal Suresh Patil, Jordan Robinson, Hao Wu, Andreas Xydis

This volume contains revised versions of the papers selected for the third volume of the Online Handbook of Argumentation for AI (OHAAI).

An ADMM-Incorporated Latent Factorization of Tensors Method for QoS Prediction

no code implementations3 Dec 2022 Jiajia Mi, Hao Wu

We maintain the non-negativity of the model by constructing an augmented Lagrangian function with the ADMM optimization framework.

Track Targets by Dense Spatio-Temporal Position Encoding

no code implementations17 Oct 2022 Jinkun Cao, Hao Wu, Kris Kitani

Experiments on video multi-object tracking (MOT) and multi-object tracking and segmentation (MOTS) datasets demonstrate the effectiveness of the proposed DST position encoding.

Association Multi-Object Tracking +1

Enhancing Spatiotemporal Prediction Model using Modular Design and Beyond

no code implementations4 Oct 2022 Haoyu Pan, Hao Wu, Tan Yang

In this paper, a modular design is proposed, which decomposes spatiotemporal sequence model into two modules: a spatial encoder-decoder and a predictor.

A detail-enhanced sampling strategy in Hadamard single-pixel imaging

no code implementations9 Sep 2022 Yan Cai, Shijian Li, Wei zhang, Hao Wu, Xu-Ri Yao, Qing Zhao

Hadamard single-pixel imaging (HSI) is an appealing imaging technique due to its features of low hardware complexity and industrial cost.

Image Reconstruction

\b{eta}-Divergence-Based Latent Factorization of Tensors model for QoS prediction

no code implementations14 Aug 2022 Zemiao Peng, Hao Wu

A nonnegative latent factorization of tensors (NLFT) model can well model the temporal pattern hidden in nonnegative quality-of-service (QoS) data for predicting the unobserved ones with high accuracy.

Distinctive Image Captioning via CLIP Guided Group Optimization

no code implementations8 Aug 2022 Youyuan Zhang, Jiuniu Wang, Hao Wu, Wenjia Xu

Image captioning models are usually trained according to human annotated ground-truth captions, which could generate accurate but generic captions.

Image Captioning

Dual Power Spectrum Manifold and Toeplitz HPD Manifold: Enhancement and Analysis for Matrix CFAR Detection

no code implementations24 Jun 2022 Hao Wu, Yongqiang Cheng, Xixi Chen, Zheng Yang, Xiang Li, Hongqiang Wang

These advantages benefit from the geometry of the Toeplitz Hermitian positive definite (HPD) manifold $\mathcal{M}_{\mathcal{T}H_{++}}$, but the sophisticated geometry also results in some challenges for geometric detectors, such as the implementation of the enhanced detector to improve the SCR (signal-to-clutter ratio) and the analysis of the detection performance.

All One Needs to Know about Priors for Deep Image Restoration and Enhancement: A Survey

1 code implementation4 Jun 2022 Yunfan Lu, Yiqi Lin, Hao Wu, Yunhao Luo, Xu Zheng, Lin Wang

Image restoration and enhancement is a process of improving the image quality by removing degradations, such as noise, blur, and resolution degradation.

Image Restoration

Resilience in Industrial Internet of Things Systems: A Communication Perspective

no code implementations1 Jun 2022 Hao Wu, Yifan Miao, Peng Zhang, Yang Tian, Hui Tian

Industrial Internet of Things is an ultra-large-scale system that is much more sophisticated and fragile than conventional industrial platforms.


Edge YOLO: Real-Time Intelligent Object Detection System Based on Edge-Cloud Cooperation in Autonomous Vehicles

no code implementations30 May 2022 Siyuan Liang, Hao Wu

Driven by the ever-increasing requirements of autonomous vehicles, such as traffic monitoring and driving assistant, deep learning-based object detection (DL-OD) has been increasingly attractive in intelligent transportation systems.

Autonomous Driving object-detection +1

A New Outlier Removal Strategy Based on Reliability of Correspondence Graph for Fast Point Cloud Registration

1 code implementation16 May 2022 Li Yan, Pengcheng Wei, Hong Xie, Jicheng Dai, Hao Wu, Ming Huang

We use a simple and intuitive method to describe the 6-DOF (degree of freedom) curtailment process in point cloud registration and propose an outlier removal strategy based on the reliability of the correspondence graph.

Point Cloud Registration

CODE-MVP: Learning to Represent Source Code from Multiple Views with Contrastive Pre-Training

no code implementations Findings (NAACL) 2022 Xin Wang, Yasheng Wang, Yao Wan, Jiawei Wang, Pingyi Zhou, Li Li, Hao Wu, Jin Liu

Specifically, we first extract multiple code views using compiler tools, and learn the complementary information among them under a contrastive learning framework.

Contrastive Learning Defect Detection +2

Towards Practical and Efficient Long Video Summary

1 code implementation ICASSP 2022 Xiaopeng Ke, Boyu Chang, Hao Wu, Fengyuan Xu, Sheng Zhong

Recently, video summarization (VS) techniques are widely used to alleviate huge processing pressure brought by numerous long videos.

Video Summarization

Digging into Primary Financial Market: Challenges and Opportunities of Adopting Blockchain

no code implementations20 Apr 2022 Ji Liu, Zheng Xu, Yanmei Zhang, Wei Dai, Hao Wu, Shiping Chen

Since the emergence of blockchain technology, its application in the financial market has always been an area of focus and exploration by all parties.

GMSS: Graph-Based Multi-Task Self-Supervised Learning for EEG Emotion Recognition

1 code implementation12 Apr 2022 Yang Li, Ji Chen, Fu Li, Boxun Fu, Hao Wu, Youshuo Ji, Yijin Zhou, Yi Niu, Guangming Shi, Wenming Zheng

GMSS has the ability to learn more general representations by integrating multiple self-supervised tasks, including spatial and frequency jigsaw puzzle tasks, and contrastive learning tasks.

Contrastive Learning EEG +2

Monte Carlo PINNs: deep learning approach for forward and inverse problems involving high dimensional fractional partial differential equations

no code implementations16 Mar 2022 Ling Guo, Hao Wu, Xiaochen Yu, Tao Zhou

We introduce a sampling based machine learning approach, Monte Carlo physics informed neural networks (MC-PINNs), for solving forward and inverse fractional partial differential equations (FPDEs).

Beyond the Limitation of Pulse Width in Optical Time-domain Reflectometry

no code implementations14 Mar 2022 Hao Wu, Ming Tang

Here, we propose and experimentally demonstrate an OTDR deconvolution neural network based on deep convolutional neural networks.

Compilable Neural Code Generation with Compiler Feedback

no code implementations Findings (ACL) 2022 Xin Wang, Yasheng Wang, Yao Wan, Fei Mi, Yitong Li, Pingyi Zhou, Jin Liu, Hao Wu, Xin Jiang, Qun Liu

Automatically generating compilable programs with (or without) natural language descriptions has always been a touchstone problem for computational linguistics and automated software engineering.

Code Completion Code Generation +3

Contrastive Vision-Language Pre-training with Limited Resources

1 code implementation17 Dec 2021 Quan Cui, Boyan Zhou, Yu Guo, Weidong Yin, Hao Wu, Osamu Yoshie, Yubo Chen

However, these works require a tremendous amount of data and computational resources (e. g., billion-level web data and hundreds of GPUs), which prevent researchers with limited resources from reproduction and further exploration.

Contrastive Learning

FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling

1 code implementation NeurIPS 2021 BoWen Zhang, Yidong Wang, Wenxin Hou, Hao Wu, Jindong Wang, Manabu Okumura, Takahiro Shinozaki

However, like other modern SSL algorithms, FixMatch uses a pre-defined constant threshold for all classes to select unlabeled data that contribute to the training, thus failing to consider different learning status and learning difficulties of different classes.

Semi-Supervised Image Classification

Positional-Spectral-Temporal Attention in 3D Convolutional Neural Networks for EEG Emotion Recognition

no code implementations13 Oct 2021 Jiyao Liu, Yanxi Zhao, Hao Wu, Dongmei Jiang

The proposed module, denoted by PST-Attention, consists of Positional, Spectral and Temporal Attention modules to explore more discriminative EEG features.

EEG EEG Emotion Recognition

Aspect-driven User Preference and News Representation Learning for News Recommendation

no code implementations12 Oct 2021 Rongyao Wang, Wenpeng Lu, Shoujin Wang, Xueping Peng, Hao Wu, Qian Zhang

News recommender systems are essential for helping users to efficiently and effectively find out those interesting news from a large amount of news.

News Recommendation Recommendation Systems +1

Enabling variable high spatial resolution retrieval from a long pulse BOTDA sensor

no code implementations9 Sep 2021 Zhao Ge, Li Shen, Can Zhao, Hao Wu, Zhiyong Zhao, Ming Tang

We propose a convolutional neural network (CNN) to process the data of conventional Brillouin optical time domain analysis (BOTDA) sensors, which achieves unprecedented performance improvement that allows to directly retrieve higher spatial resolution (SR) from the sensing system that use long pump pulses.


Normalizing field flows: Solving forward and inverse stochastic differential equations using physics-informed flow models

no code implementations30 Aug 2021 Ling Guo, Hao Wu, Tao Zhou

We introduce in this work the normalizing field flows (NFF) for learning random fields from scattered measurements.

Gaussian Processes

Cooperative Learning for Noisy Supervision

no code implementations11 Aug 2021 Hao Wu, Jiangchao Yao, Ya zhang, Yanfeng Wang

Learning with noisy labels has gained the enormous interest in the robust deep learning area.

Learning with noisy labels

SynCoBERT: Syntax-Guided Multi-Modal Contrastive Pre-Training for Code Representation

no code implementations10 Aug 2021 Xin Wang, Yasheng Wang, Fei Mi, Pingyi Zhou, Yao Wan, Xiao Liu, Li Li, Hao Wu, Jin Liu, Xin Jiang

Code representation learning, which aims to encode the semantics of source code into distributed vectors, plays an important role in recent deep-learning-based models for code intelligence.

Clone Detection Code Search +5

Conjugate Energy-Based Models

no code implementations ICLR Workshop EBM 2021 Hao Wu, Babak Esmaeili, Michael Wick, Jean-Baptiste Tristan, Jan-Willem van de Meent

In this paper, we propose conjugate energy-based models (CEBMs), a new class of energy-based models that define a joint density over data and latent variables.

Nested Variational Inference

no code implementations NeurIPS 2021 Heiko Zimmermann, Hao Wu, Babak Esmaeili, Jan-Willem van de Meent

We develop nested variational inference (NVI), a family of methods that learn proposals for nested importance samplers by minimizing an forward or reverse KL divergence at each level of nesting.

Variational Inference

Boosting Offline Reinforcement Learning with Residual Generative Modeling

no code implementations19 Jun 2021 Hua Wei, Deheng Ye, Zhao Liu, Hao Wu, Bo Yuan, Qiang Fu, Wei Yang, Zhenhui Li

While most research focuses on the state-action function part through reducing the bootstrapping error in value function approximation induced by the distribution shift of training data, the effects of error propagation in generative modeling have been neglected.

Offline RL Q-Learning +2

Mathematical Modeling of Chemotaxis Guided Amoeboid Cell Swimming

no code implementations7 Apr 2021 Qixuan Wang, Hao Wu

Cells and microorganisms adopt various strategies to migrate in response to different environmental stimuli.

Collaborative Label Correction via Entropy Thresholding

no code implementations31 Mar 2021 Hao Wu, Jiangchao Yao, Jiajie Wang, Yinru Chen, Ya zhang, Yanfeng Wang

Deep neural networks (DNNs) have the capacity to fit extremely noisy labels nonetheless they tend to learn data with clean labels first and then memorize those with noisy labels.

Minimization of ion micromotion with artificial neural network

no code implementations3 Mar 2021 Yang Liu, Qi-feng Lao, Peng-fei Lu, Xin-xin Rao, Hao Wu, Teng Liu, Kun-xu Wang, Zhao Wang, Ming-shen Li, Feng Zhu, Luo Le

Minimizing the micromotion of the single trapped ion in a linear Paul trap is a tedious and time-consuming work, but is of great importance in cooling the ion into the motional ground state as well as maintaining long coherence time, which is crucial for quantum information processing and quantum computation.

Atomic Physics Quantum Physics

Learning Proposals for Probabilistic Programs with Inference Combinators

1 code implementation1 Mar 2021 Sam Stites, Heiko Zimmermann, Hao Wu, Eli Sennesh, Jan-Willem van de Meent

Proposals in these samplers can be parameterized using neural networks, which in turn can be trained by optimizing variational objectives.

A Convergent Semi-Proximal Alternating Direction Method of Multipliers for Recovering Internet Traffics from Link Measurements

no code implementations5 Feb 2021 Zhenyu Ming, Liping Zhang, Hao Wu, Yanwei Xu, Mayank Bakshi, Bo Bai, Gong Zhang

Our model can be divided into a series of subproblems, which only relate to the traffics in a certain individual time interval.

Optimization and Control

LEAP: TrustZone Based Developer-Friendly TEE for Intelligent Mobile Apps

no code implementations4 Feb 2021 Lizhi Sun, Shuocheng Wang, Hao Wu, Yuhang Gong, Fengyuan Xu, Yunxin Liu, Hao Han, Sheng Zhong

ARM TrustZone is widely deployed on commercial-off-the-shelf mobile devices for secure execution.

Cryptography and Security

Coalition Game Based Full-duplex Popular Content Distribution in mmWave Vehicular Networks

no code implementations29 Jan 2021 Yibing Wang, Hao Wu, Yong Niu, Zhu Han, Bo Ai, Zhangdui Zhong

We evaluate the proposed scheme by extensive simulations in mmWave vehicular networks.

Fairness Information Theory Networking and Internet Architecture Information Theory

Adaptive Tree Wasserstein Minimization for Hierarchical Generative Modeling

no code implementations1 Jan 2021 ZiHao Wang, Xu Zhao, Tam Le, Hao Wu, Yong Zhang, Makoto Yamada

In this work, we consider OT over tree metrics, which is more general than the sliced Wasserstein and includes the sliced Wasserstein as a special case, and we propose a fast minimization algorithm in $O(n)$ for the optimal Wasserstein-1 transport plan between two distributions in the tree structure.

Unsupervised Domain Adaptation

Learning the Best Pooling Strategy for Visual Semantic Embedding

1 code implementation CVPR 2021 Jiacheng Chen, Hexiang Hu, Hao Wu, Yuning Jiang, Changhu Wang

Visual Semantic Embedding (VSE) is a dominant approach for vision-language retrieval, which aims at learning a deep embedding space such that visual data are embedded close to their semantic text labels or descriptions.

Cross-Modal Information Retrieval Image-text Retrieval +4

Memory Group Sampling Based Online Action Recognition Using Kinetic Skeleton Features

no code implementations1 Nov 2020 Guoliang Liu, Qinghui Zhang, Yichao Cao, Junwei Li, Hao Wu, Guohui Tian

First, we combine the spatial and temporal skeleton features to depict the actions, which include not only the geometrical features, but also multi-scale motion features, such that both the spatial and temporal information of the action are covered.

Action Recognition

Semi-Supervised Bilingual Lexicon Induction with Two-way Interaction

1 code implementation EMNLP 2020 Xu Zhao, ZiHao Wang, Hao Wu, Yong Zhang

In this paper, we propose a new semi-supervised BLI framework to encourage the interaction between the supervised signal and unsupervised alignment.

Bilingual Lexicon Induction

A Relaxed Matching Procedure for Unsupervised BLI

no code implementations ACL 2020 Xu Zhao, ZiHao Wang, Hao Wu, Yong Zhang

Recently unsupervised Bilingual Lexicon Induction (BLI) without any parallel corpus has attracted much research interest.

Bilingual Lexicon Induction Translation

Improving the spatial resolution of a BOTDA sensor using deconvolution algorithm

no code implementations15 Sep 2020 Li Shen, Zhiyong Zhao, Can Zhao, Hao Wu, Chao Lu, Ming Tang

The frequency dependency of Brillouin gain temporal envelope is investigated by simulation, and its impact on the recovered results of deconvolution algorithm is thoroughly analyzed.


DanHAR: Dual Attention Network For Multimodal Human Activity Recognition Using Wearable Sensors

no code implementations25 Jun 2020 Wenbin Gao, Lei Zhang, Qi Teng, Jun He, Hao Wu

Recently, two attention methods are proposed via combining with Gated Recurrent Units (GRU) and Long Short-Term Memory (LSTM) network, which can capture the dependencies of sensing signals in both spatial and temporal domains simultaneously.

Hard Attention Human Activity Recognition

Learning Based Distributed Tracking

no code implementations23 Jun 2020 Hao Wu, Junhao Gan, Rui Zhang

Inspired by the great success of machine learning in the past decade, people have been thinking about the possibility of improving the theoretical results by exploring data distribution.

Data Structures and Algorithms

Real-time Human Activity Recognition Using Conditionally Parametrized Convolutions on Mobile and Wearable Devices

no code implementations5 Jun 2020 Xin Cheng, Lei Zhang, Yin Tang, Yue Liu, Hao Wu, Jun He

For deep learning, improvements in performance have to heavily rely on increasing model size or capacity to scale to larger and larger datasets, which inevitably leads to the increase of operations.

Human Activity Recognition

Response to LiveBot: Generating Live Video Comments Based on Visual and Textual Contexts

2 code implementations4 Jun 2020 Hao Wu, Gareth J. F. Jones, Francois Pitie

Recently the Chinese video sharing platform Bilibili, has popularised a novel captioning system where user comments are displayed as streams of moving subtitles overlaid on the video playback screen and broadcast to all viewers in real-time.

Modeling nanoconfinement effects using active learning

no code implementations6 May 2020 Javier E. Santos, Mohammed Mehana, Hao Wu, Masa Prodanovic, Michael J. Pyrcz, Qinjun Kang, Nicholas Lubbers, Hari Viswanathan

At this scale, the fluid properties are affected by nanoconfinement effects due to the increased fluid-solid interactions.

Active Learning

TORQUE: A Reading Comprehension Dataset of Temporal Ordering Questions

no code implementations EMNLP 2020 Qiang Ning, Hao Wu, Rujun Han, Nanyun Peng, Matt Gardner, Dan Roth

A critical part of reading is being able to understand the temporal relationships between events described in a passage of text, even when those relationships are not explicitly stated.

Machine Reading Comprehension Question Answering

Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation

1 code implementation20 Apr 2020 Hao Wu, Patrick Judd, Xiaojie Zhang, Mikhail Isaev, Paulius Micikevicius

Quantization techniques can reduce the size of Deep Neural Networks and improve inference latency and throughput by taking advantage of high throughput integer instructions.


Masked Face Recognition Dataset and Application

3 code implementations20 Mar 2020 Zhongyuan Wang, Guangcheng Wang, Baojin Huang, Zhangyang Xiong, Qi Hong, Hao Wu, Peng Yi, Kui Jiang, Nanxi Wang, Yingjiao Pei, Heling Chen, Yu Miao, Zhibing Huang, Jinbi Liang

These datasets are freely available to industry and academia, based on which various applications on masked faces can be developed.

Face Detection Face Recognition

Fully Convolutional Networks for Automatically Generating Image Masks to Train Mask R-CNN

no code implementations3 Mar 2020 Hao Wu, Jan Paul Siebert, Xiangrong Xu

This paper proposes a novel automatically generating image masks method for the state-of-the-art Mask R-CNN deep learning method.

object-detection Object Detection

DeepDualMapper: A Gated Fusion Network for Automatic Map Extraction using Aerial Images and Trajectories

no code implementations17 Feb 2020 Hao Wu, Hanyuan Zhang, Xin-Yu Zhang, Weiwei Sun, Baihua Zheng, Yuning Jiang

We propose a deep convolutional neural network called DeepDualMapper which fuses the aerial image and trajectory data in a more seamless manner to extract the digital map.

Stochastic Normalizing Flows

1 code implementation NeurIPS 2020 Hao Wu, Jonas Köhler, Frank Noé

The sampling of probability distributions specified up to a normalization constant is an important problem in both machine learning and statistical mechanics.

Structural-Aware Sentence Similarity with Recursive Optimal Transport

no code implementations28 Jan 2020 Zihao Wang, Yong Zhang, Hao Wu

Moreover, we further develop Recursive Optimal Similarity (ROTS) for sentences with the valuable semantic insights from the connections between cosine similarity of weighted average of word vectors and optimal transport.

Sentence Similarity STS

Deep learning Markov and Koopman models with physical constraints

1 code implementation16 Dec 2019 Andreas Mardt, Luca Pasquali, Frank Noé, Hao Wu

Here we develop theory and methods for deep learning Markov and Koopman models that can bear such physical constraints.

Computational Physics

Structured Multi-Hashing for Model Compression

no code implementations CVPR 2020 Elad Eban, Yair Movshovitz-Attias, Hao Wu, Mark Sandler, Andrew Poon, Yerlan Idelbayev, Miguel A. Carreira-Perpinan

Despite the success of deep neural networks (DNNs), state-of-the-art models are too large to deploy on low-resource devices or common server configurations in which multiple models are held in memory.

Model Compression

Amortized Population Gibbs Samplers with Neural Sufficient Statistics

1 code implementation ICML 2020 Hao Wu, Heiko Zimmermann, Eli Sennesh, Tuan Anh Le, Jan-Willem van de Meent

We develop amortized population Gibbs (APG) samplers, a class of scalable methods that frames structured variational inference as adaptive importance sampling.

Variational Inference

Continuous Convolutional Neural Network forNonuniform Time Series

no code implementations25 Sep 2019 Hui Shi, Yang Zhang, Hao Wu, Shiyu Chang, Kaizhi Qian, Mark Hasegawa-Johnson, Jishen Zhao

Convolutional neural network (CNN) for time series data implicitly assumes that the data are uniformly sampled, whereas many event-based and multi-modal data are nonuniform or have heterogeneous sampling rates.

Time Series

Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds

1 code implementation IJCNLP 2019 John P. Lalor, Hao Wu, Hong Yu

We demonstrate a use-case for latent difficulty item parameters, namely training set filtering, and show that using difficulty to sample training data outperforms baseline methods.

Natural Language Inference Sentiment Analysis

An encoding framework with brain inner state for natural image identification

no code implementations22 Aug 2019 Hao Wu, Ziyu Zhu, Jiayi Wang, Nanning Zheng, Badong Chen

The framework comprises two parts: forward encoding model that deals with visual stimuli and inner state model that captures influence from intrinsic connections in the brain.

Brain Decoding

Detecting 11K Classes: Large Scale Object Detection without Fine-Grained Bounding Boxes

no code implementations ICCV 2019 Hao Yang, Hao Wu, Hao Chen

However, these methods require fully annotated object bounding boxes for training, which are incredibly hard to scale up due to the high annotation cost.

object-detection Object Detection +1

Joint Reasoning for Temporal and Causal Relations

no code implementations ACL 2018 Qiang Ning, Zhili Feng, Hao Wu, Dan Roth

Understanding temporal and causal relations between events is a fundamental natural language understanding task.

Natural Language Understanding

A Variational Approach for Learning from Positive and Unlabeled Data

1 code implementation NeurIPS 2020 Hui Chen, Fangqing Liu, Yin Wang, Liyue Zhao, Hao Wu

Learning binary classifiers only from positive and unlabeled (PU) data is an important and challenging task in many real-world applications, including web text classification, disease gene identification and fraud detection, where negative samples are difficult to verify experimentally.

Fraud Detection text-classification +1

ZQM at SemEval-2019 Task9: A Single Layer CNN Based on Pre-trained Model for Suggestion Mining

no code implementations SEMEVAL 2019 Qimin Zhou, Zhengxin Zhang, Hao Wu, Linmao Wang

In our system, the input of convolutional neural network is the embedding vectors which are drawn from the pre-trained BERT model.

Suggestion mining

Adaptive Learning Material Recommendation in Online Language Education

no code implementations26 May 2019 Shuhan Wang, Hao Wu, Ji Hun Kim, Erik Andersen

Recommending personalized learning materials for online language learning is challenging because we typically lack data about the student's ability and the relative difficulty of learning materials.

Uneven illumination surface defects inspection based on convolutional neural network

no code implementations16 May 2019 Hao Wu, Xiangrong Xu, Wenbin Gao

Surface defect inspection based on machine vision is often affected by uneven illumination.

Free Component Analysis: Theory, Algorithms & Applications

no code implementations5 May 2019 Hao Wu, Raj Rao Nadakuditi

We describe a method for unmixing mixtures of freely independent random variables in a manner analogous to the independent component analysis (ICA) based method for unmixing independent random variables from their additive mixtures.

Wasserstein-Fisher-Rao Document Distance

no code implementations23 Apr 2019 Zihao Wang, Datong Zhou, Yong Zhang, Hao Wu, Chenglong Bao

As a fundamental problem of natural language processing, it is important to measure the distance between different documents.

Semantic Similarity Semantic Textual Similarity

Boltzmann Generators -- Sampling Equilibrium States of Many-Body Systems with Deep Learning

2 code implementations4 Dec 2018 Frank Noé, Simon Olsson, Jonas Köhler, Hao Wu

Computing equilibrium states in condensed-matter many-body systems, such as solvated proteins, is a long-standing challenge.

Variational Selection of Features for Molecular Kinetics

no code implementations28 Nov 2018 Martin K. Scherer, Brooke E. Husic, Moritz Hoffmann, Fabian Paul, Hao Wu, Frank Noé

The modeling of atomistic biomolecular simulations using kinetic models such as Markov state models (MSMs) has had many notable algorithmic advances in recent years.

Model Selection

Composing Modeling and Inference Operations with Probabilistic Program Combinators

no code implementations14 Nov 2018 Eli Sennesh, Adam Ścibior, Hao Wu, Jan-Willem van de Meent

We assume that models are dynamic, but that model composition is static, in the sense that combinator application takes place prior to evaluating the model on data.

Zewen at SemEval-2018 Task 1: An Ensemble Model for Affect Prediction in Tweets

no code implementations SEMEVAL 2018 Zewen Chi, He-Yan Huang, Jiangui Chen, Hao Wu, Ran Wei

This paper presents a method for Affect in Tweets, which is the task to automatically determine the intensity of emotions and intensity of sentiment of tweets.

Sentence Classification Sentiment Analysis

Deep Generative Markov State Models

2 code implementations NeurIPS 2018 Hao Wu, Andreas Mardt, Luca Pasquali, Frank Noe

We propose a deep generative Markov State Model (DeepGenMSM) learning framework for inference of metastable dynamical systems and prediction of trajectories.

Time Series

A Multi-Axis Annotation Scheme for Event Temporal Relations

no code implementations ACL 2018 Qiang Ning, Hao Wu, Dan Roth

Existing temporal relation (TempRel) annotation schemes often have low inter-annotator agreements (IAA) even between experts, suggesting that the current annotation task needs a better definition.

Improving Temporal Relation Extraction with a Globally Acquired Statistical Resource

no code implementations NAACL 2018 Qiang Ning, Hao Wu, Haoruo Peng, Dan Roth

We argue that this task would gain from the availability of a resource that provides prior knowledge in the form of the temporal order that events usually follow.

Temporal Relation Extraction

Loss Rank Mining: A General Hard Example Mining Method for Real-time Detectors

no code implementations10 Apr 2018 Hao Yu, Zhaoning Zhang, Zheng Qin, Hao Wu, Dongsheng Li, Jun Zhao, Xicheng Lu

LRM is a general method for real-time detectors, as it utilizes the final feature map which exists in all real-time detectors to mine hard examples.

A Novel Brain Decoding Method: a Correlation Network Framework for Revealing Brain Connections

no code implementations1 Dec 2017 Siyu Yu, Nanning Zheng, Yongqiang Ma, Hao Wu, Badong Chen

Analyzing the correlations of collected data from human brain activities and representing activity patterns are two problems in brain decoding based on functional magnetic resonance imaging (fMRI) signals.

Brain Decoding

VAMPnets: Deep learning of molecular kinetics

1 code implementation16 Oct 2017 Andreas Mardt, Luca Pasquali, Hao Wu, Frank Noé

There is an increasing demand for computing the relevant structures, equilibria and long-timescale kinetics of biomolecular processes, such as protein-drug binding, from high-throughput molecular dynamics simulations.

Dimensionality Reduction

Network Vector: Distributed Representations of Networks with Global Context

no code implementations7 Sep 2017 Hao Wu, Kristina Lerman

We propose a neural embedding algorithm called Network Vector, which learns distributed representations of nodes and the entire networks simultaneously.

General Classification Node Classification

Variational approach for learning Markov processes from time series data

no code implementations14 Jul 2017 Hao Wu, Frank Noé

This leads to the definition of a family of score functions called VAMP-r which can be calculated from data, and can be employed to optimize a Markovian model.

Management Model Selection +1

Soft Label Memorization-Generalization for Natural Language Inference

no code implementations27 Feb 2017 John P. Lalor, Hao Wu, Hong Yu

Often when multiple labels are obtained for a training example it is assumed that there is an element of noise that must be accounted for.

Memorization Natural Language Inference

Variational Koopman models: slow collective variables and molecular kinetics from short off-equilibrium simulations

no code implementations20 Oct 2016 Hao Wu, Feliks Nüske, Fabian Paul, Stefan Klus, Peter Koltai, Frank Noé

Recently, a powerful generalization of MSMs has been introduced, the variational approach (VA) of molecular kinetics and its special case the time-lagged independent component analysis (TICA), which allow us to approximate slow collective variables and molecular kinetics by linear combinations of smooth basis functions or order parameters.

Dimensionality Reduction

Spectral learning of dynamic systems from nonequilibrium data

no code implementations NeurIPS 2016 Hao Wu, Frank Noé

Observable operator models (OOMs) and related models are one of the most important and powerful tools for modeling and analyzing stochastic systems.

Hierarchical Neural Language Models for Joint Representation of Streaming Documents and their Content

no code implementations28 Jun 2016 Nemanja Djuric, Hao Wu, Vladan Radosavljevic, Mihajlo Grbovic, Narayan Bhamidipati

In particular, we exploit the context of documents in streams and use one of the language models to model the document sequences, and the other to model word sequences within them.

Building an Evaluation Scale using Item Response Theory

no code implementations EMNLP 2016 John P. Lalor, Hao Wu, Hong Yu

Evaluation of NLP methods requires testing against a previously vetted gold-standard test set and reporting standard metrics (accuracy/precision/recall/F1).

Natural Language Inference

Sparse Estimation of Multivariate Poisson Log-Normal Models from Count Data

no code implementations22 Feb 2016 Hao Wu, Xinwei Deng, Naren Ramakrishnan

Modeling data with multivariate count responses is a challenging problem due to the discrete nature of the responses.

Association regression

The Computational Principles of Learning Ability

no code implementations23 Sep 2015 Hao Wu

It has been quite a long time since AI researchers in the field of computer science stop talking about simulating human intelligence or trying to explain how brain works.

Common Sense Reasoning

What is Learning? A primary discussion about information and Representation

no code implementations19 May 2015 Hao Wu

While for AI and machine learning researchers, it is a consensus that we are not anywhere near the core technique which could bring the Terminator, Number 5 or R2D2 into real life, and there is not even a formal definition about what is intelligence, or one of its basic properties: Learning.

BIG-bench Machine Learning

Clustering Assisted Fundamental Matrix Estimation

no code implementations14 Apr 2015 Hao Wu, Yi Wan

In computer vision, the estimation of the fundamental matrix is a basic problem that has been extensively studied.

3D Reconstruction

Maximum Margin Clustering for State Decomposition of Metastable Systems

no code implementations31 Dec 2014 Hao Wu

When studying a metastable dynamical system, a prime concern is how to decompose the phase space into a set of metastable states.

ILLINOISCLOUDNLP: Text Analytics Services in the Cloud

no code implementations LREC 2014 Hao Wu, Zhiye Fei, Aaron Dai, Mark Sammons, Dan Roth, Stephen Mayhew

Natural Language Processing (NLP) continues to grow in popularity in a range of research and commercial applications.

Knowledge Base Population

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