Search Results for author: Hao Zhang

Found 207 papers, 56 papers with code

BIRNAT: Bidirectional Recurrent Neural Networks with Adversarial Training for Video Snapshot Compressive Imaging

1 code implementation ECCV 2020 Ziheng Cheng, Ruiying Lu, Zhengjue Wang, Hao Zhang, Bo Chen, Ziyi Meng, Xin Yuan

This measurement and the modulation masks are fed into our Recurrent Neural Network (RNN) to reconstruct the desired high-speed frames.

WordNet Troponymy and Extraction of “Manner-Result” Relations

no code implementations GWC 2018 Aliaksandr Huminski, Hao Zhang

The procedure of extraction includes three steps and the results are based on the analysis of the whole set of verbs in WordNet.

Friendly Topic Assistant for Transformer Based Abstractive Summarization

no code implementations EMNLP 2020 Zhengjue Wang, Zhibin Duan, Hao Zhang, Chaojie Wang, Long Tian, Bo Chen, Mingyuan Zhou

Abstractive document summarization is a comprehensive task including document understanding and summary generation, in which area Transformer-based models have achieved the state-of-the-art performance.

Abstractive Text Summarization Document Summarization +1

Neighborhood Region Smoothing Regularization for Finding Flat Minima In Deep Neural Networks

no code implementations16 Jan 2022 Yang Zhao, Hao Zhang

NRS leverages the finding that models would benefit from converging to flat minima, and tries to regularize the neighborhood region in weight space to yield approximate outputs.

Manifoldron: Direct Space Partition via Manifold Discovery

1 code implementation14 Jan 2022 Dayang Wang, Feng-Lei Fan, Bo-Jian Hou, Hao Zhang, Rongjie Lai, Hengyong Yu, Fei Wang

A neural network with the widely-used ReLU activation has been shown to partition the sample space into many convex polytopes for prediction.

SAC-GAN: Structure-Aware Image-to-Image Composition for Self-Driving

no code implementations13 Dec 2021 Hang Zhou, Ali Mahdavi-Amiri, Rui Ma, Hao Zhang

Specifically, our network takes the semantic layout features from the input scene image, features encoded from the edges and silhouette in the input object patch, as well as a latent code as inputs, and generates a 2D spatial affine transform defining the translation and scaling of the object patch.

Image Augmentation

Hybrid Neural Networks for On-device Directional Hearing

no code implementations11 Dec 2021 Anran Wang, Maruchi Kim, Hao Zhang, Shyamnath Gollakota

On-device directional hearing requires audio source separation from a given direction while achieving stringent human-imperceptible latency requirements.

Audio Source Separation Causal Inference

UNIST: Unpaired Neural Implicit Shape Translation Network

no code implementations10 Dec 2021 Qimin Chen, Johannes Merz, Aditya Sanghi, Hooman Shayani, Ali Mahdavi-Amiri, Hao Zhang

We introduce UNIST, the first deep neural implicit model for general-purpose, unpaired shape-to-shape translation, in both 2D and 3D domains.

Style Transfer Translation

Self-Reflective Terrain-Aware Robot Adaptation for Consistent Off-Road Ground Navigation

no code implementations12 Nov 2021 Sriram Siva, Maggie Wigness, John G. Rogers, Long Quang, Hao Zhang

Ground robots require the crucial capability of traversing unstructured and unprepared terrains and avoiding obstacles to complete tasks in real-world robotics applications such as disaster response.

Disaster Response

Discovering and Explaining the Representation Bottleneck of DNNs

no code implementations11 Nov 2021 Huiqi Deng, Qihan Ren, Xu Chen, Hao Zhang, Jie Ren, Quanshi Zhang

This paper explores the bottleneck of feature representations of deep neural networks (DNNs), from the perspective of the complexity of interactions between input variables encoded in DNNs.

CLIP2TV: An Empirical Study on Transformer-based Methods for Video-Text Retrieval

no code implementations10 Nov 2021 Zijian Gao, Jingyu Liu, Sheng Chen, Dedan Chang, Hao Zhang, Jinwei Yuan

Modern video-text retrieval frameworks basically consist of three parts: video encoder, text encoder and the similarity head.

 Ranked #1 on Video Retrieval on MSR-VTT (using extra training data)

Representation Learning Video-Text Retrieval

Towards Debiasing Temporal Sentence Grounding in Video

no code implementations8 Nov 2021 Hao Zhang, Aixin Sun, Wei Jing, Joey Tianyi Zhou

In this paper, we propose two debiasing strategies, data debiasing and model debiasing, to "force" a TSGV model to capture cross-modal interactions.

Asynchronous Collaborative Localization by Integrating Spatiotemporal Graph Learning with Model-Based Estimation

no code implementations5 Nov 2021 Peng Gao, Brian Reily, Rui Guo, HongSheng Lu, Qingzhao Zhu, Hao Zhang

In this paper, we introduce a novel approach that integrates uncertainty-aware spatiotemporal graph learning and model-based state estimation for a team of robots to collaboratively localize objects.

Graph Learning Object Localization

Clinical Evidence Engine: Proof-of-Concept For A Clinical-Domain-Agnostic Decision Support Infrastructure

no code implementations31 Oct 2021 BoJian Hou, Hao Zhang, Gur Ladizhinsky, Stephen Yang, Volodymyr Kuleshov, Fei Wang, Qian Yang

As a result, clinicians cannot easily or rapidly scrutinize the CDSS recommendation when facing a difficult diagnosis or treatment decision in practice.

A Prototype-Oriented Framework for Unsupervised Domain Adaptation

1 code implementation NeurIPS 2021 Korawat Tanwisuth, Xinjie Fan, Huangjie Zheng, Shujian Zhang, Hao Zhang, Bo Chen, Mingyuan Zhou

Existing methods for unsupervised domain adaptation often rely on minimizing some statistical distance between the source and target samples in the latent space.

Unsupervised Domain Adaptation

Position-Invariant Truecasing with a Word-and-Character Hierarchical Recurrent Neural Network

no code implementations26 Aug 2021 Hao Zhang, You-Chi Cheng, Shankar Kumar, Mingqing Chen, Rajiv Mathews

Truecasing is the task of restoring the correct case (uppercase or lowercase) of noisy text generated either by an automatic system for speech recognition or machine translation or by humans.

Machine Translation Named Entity Recognition +2

Detecting Small Objects in Thermal Images Using Single-Shot Detector

no code implementations25 Aug 2021 Hao Zhang, Xianggong Hong, Li Zhu

In this paper, we proposed DDSSD (Dilation and Deconvolution Single Shot Multibox Detector), an enhanced SSD with a novel feature fusion module which can improve the performance over SSD for small object detection.

Small Object Detection

Small Object Detection Based on Modified FSSD and Model Compression

no code implementations24 Aug 2021 Qingcai Wang, Hao Zhang, Xianggong Hong, Qinqin Zhou

Small objects have relatively low resolution, the unobvious visual features which are difficult to be extracted, so the existing object detection methods cannot effectively detect small objects, and the detection speed and stability are poor.

Model Compression Small Object Detection

Automatic Modulation Classification Using Involution Enabled Residual Networks

no code implementations23 Aug 2021 Hao Zhang, Lu Yuan, Guangyu Wu, Fuhui Zhou, Qihui Wu

Automatic modulation classification (AMC) is of crucial importance for realizing wireless intelligence communications.

Interpreting Attributions and Interactions of Adversarial Attacks

no code implementations ICCV 2021 Xin Wang, Shuyun Lin, Hao Zhang, Yufei Zhu, Quanshi Zhang

This paper aims to explain adversarial attacks in terms of how adversarial perturbations contribute to the attacking task.

Token Shift Transformer for Video Classification

1 code implementation5 Aug 2021 Hao Zhang, Yanbin Hao, Chong-Wah Ngo

It is worth noticing that our TokShift transformer is a pure convolutional-free video transformer pilot with computational efficiency for video understanding.

Video Classification Video Understanding

COSY: COunterfactual SYntax for Cross-Lingual Understanding

1 code implementation ACL 2021 Sicheng Yu, Hao Zhang, Yulei Niu, Qianru Sun, Jing Jiang

Pre-trained multilingual language models, e. g., multilingual-BERT, are widely used in cross-lingual tasks, yielding the state-of-the-art performance.

Natural Language Inference POS +1

EnsLM: Ensemble Language Model for Data Diversity by Semantic Clustering

1 code implementation ACL 2021 Zhibin Duan, Hao Zhang, Chaojie Wang, Zhengjue Wang, Bo Chen, Mingyuan Zhou

As a result, the backbone learns the shared knowledge among all clusters while modulated weights extract the cluster-specific features.

Language Modelling

Proceedings of ICML 2021 Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI

no code implementations16 Jul 2021 Quanshi Zhang, Tian Han, Lixin Fan, Zhanxing Zhu, Hang Su, Ying Nian Wu, Jie Ren, Hao Zhang

This workshop pays a special interest in theoretic foundations, limitations, and new application trends in the scope of XAI.

Turbulence-immune computational ghost imaging based on a multi-scale generative adversarial network

no code implementations14 Jul 2021 Hao Zhang, Deyang Duan

There is a consensus that turbulence-free images cannot be obtained by conventional computational ghost imaging (CGI) because the CGI is only a classic simulation, which does not satisfy the conditions of turbulence-free imaging.

MINERVAS: Massive INterior EnviRonments VirtuAl Synthesis

no code implementations13 Jul 2021 Haocheng Ren, Hao Zhang, Jia Zheng, Jiaxiang Zheng, Rui Tang, Rui Wang, Hujun Bao

With the rapid development of data-driven techniques, data has played an essential role in various computer vision tasks.

Image Generation

PhotoChat: A Human-Human Dialogue Dataset with Photo Sharing Behavior for Joint Image-Text Modeling

no code implementations ACL 2021 Xiaoxue Zang, Lijuan Liu, Maria Wang, Yang song, Hao Zhang, Jindong Chen

Based on this dataset, we propose two tasks to facilitate research on image-text modeling: a photo-sharing intent prediction task that predicts whether one intends to share a photo in the next conversation turn, and a photo retrieval task that retrieves the most relevant photo according to the dialogue context.

Image Retrieval

Learning Mesh Representations via Binary Space Partitioning Tree Networks

1 code implementation27 Jun 2021 Zhiqin Chen, Andrea Tagliasacchi, Hao Zhang

The network is trained to reconstruct a shape using a set of convexes obtained from a BSP-tree built over a set of planes, where the planes and convexes are both defined by learned network weights.

Neural Marching Cubes

1 code implementation21 Jun 2021 Zhiqin Chen, Hao Zhang

To tackle these challenges, we re-cast MC from a deep learning perspective, by designing tessellation templates more apt at preserving geometric features, and learning the vertex positions and mesh topologies from training meshes, to account for contextual information from nearby cubes.

Interventional Video Grounding with Dual Contrastive Learning

1 code implementation CVPR 2021 Guoshun Nan, Rui Qiao, Yao Xiao, Jun Liu, Sicong Leng, Hao Zhang, Wei Lu

2) Meanwhile, we introduce a dual contrastive learning approach (DCL) to better align the text and video by maximizing the mutual information (MI) between query and video clips, and the MI between start/end frames of a target moment and the others within a video to learn more informative visual representations.

Causal Inference Contrastive Learning +1

D2IM-Net: Learning Detail Disentangled Implicit Fields From Single Images

no code implementations CVPR 2021 Manyi Li, Hao Zhang

We present the first single-view 3D reconstruction network aimed at recovering geometric details from an input image which encompass both topological shape structures and surface features.

3D Reconstruction Single-View 3D Reconstruction

SDNet: mutil-branch for single image deraining using swin

no code implementations31 May 2021 Fuxiang Tan, YuTing Kong, Yingying Fan, Feng Liu, Daxin Zhou, Hao Zhang, Long Chen, Liang Gao, Yurong Qian

The former implements the basic rain pattern feature extraction, while the latter fuses different features to further extract and process the image features.

Autonomous Driving Single Image Deraining

A Novel Automatic Modulation Classification Scheme Based on Multi-Scale Networks

no code implementations31 May 2021 Hao Zhang, Fuhui Zhou, Qihui Wu, Wei Wu, Rose Qingyang Hu

Moreover, a novel loss function that combines the center loss and the cross entropy loss is exploited to learn both discriminative and separable features in order to further improve the classification performance.

Face Recognition

Parallel Attention Network with Sequence Matching for Video Grounding

no code implementations Findings (ACL) 2021 Hao Zhang, Aixin Sun, Wei Jing, Liangli Zhen, Joey Tianyi Zhou, Rick Siow Mong Goh

In this work, we propose a Parallel Attention Network with Sequence matching (SeqPAN) to address the challenges in this task: multi-modal representation learning, and target moment boundary prediction.

Representation Learning

Video Corpus Moment Retrieval with Contrastive Learning

1 code implementation13 May 2021 Hao Zhang, Aixin Sun, Wei Jing, Guoshun Nan, Liangli Zhen, Joey Tianyi Zhou, Rick Siow Mong Goh

We adopt the first approach and introduce two contrastive learning objectives to refine video encoder and text encoder to learn video and text representations separately but with better alignment for VCMR.

Contrastive Learning Moment Retrieval +1

Understanding Deep MIMO Detection

no code implementations11 May 2021 Qiang Hu, Feifei Gao, Hao Zhang, Geoffrey Y. Li, Zongben Xu

We demonstrate that data-driven DL detector asymptotically approaches to the maximum a posterior (MAP) detector in various scenarios but requires enough training samples to converge in time-varying channels.

Contrastive Attraction and Contrastive Repulsion for Representation Learning

no code implementations8 May 2021 Huangjie Zheng, Xu Chen, Jiangchao Yao, Hongxia Yang, Chunyuan Li, Ya zhang, Hao Zhang, Ivor Tsang, Jingren Zhou, Mingyuan Zhou

Extensive large-scale experiments on standard vision tasks show that CACR not only consistently outperforms existing CL methods on benchmark datasets in representation learning, but also provides interpretable contrastive weights, demonstrating the efficacy of the proposed doubly contrastive strategy.

Contrastive Learning Representation Learning

CAPRI-Net: Learning Compact CAD Shapes with Adaptive Primitive Assembly

no code implementations12 Apr 2021 Fenggen Yu, Zhiqin Chen, Manyi Li, Aditya Sanghi, Hooman Shayani, Ali Mahdavi-Amiri, Hao Zhang

We introduce CAPRI-Net, a neural network for learning compact and interpretable implicit representations of 3D computer-aided design (CAD) models, in the form of adaptive primitive assemblies.

Estimating the Generalization in Deep Neural Networks via Sparsity

no code implementations2 Apr 2021 Yang Zhao, Hao Zhang

By training DNNs with a wide range of generalization gap on popular datasets, we show that our key quantities and linear model could be efficient tools for estimating the generalization gap of DNNs.

Image Classification

Learning Multiscale Correlations for Human Motion Prediction

no code implementations19 Mar 2021 Honghong Zhou, Caili Guo, Hao Zhang, Yanjun Wang

We evaluate our approach on two standard benchmark datasets for human motion prediction: Human3. 6M and CMU motion capture dataset.

Human motion prediction motion prediction

Quantitative Performance Assessment of CNN Units via Topological Entropy Calculation

no code implementations17 Mar 2021 Yang Zhao, Hao Zhang

We show that by investigating the feature entropy of units on only training data, it could give discrimination between networks with different generalization ability from the view of the effectiveness of feature representations.

General Classification Image Classification

Memory-Efficient Network for Large-scale Video Compressive Sensing

2 code implementations CVPR 2021 Ziheng Cheng, Bo Chen, Guanliang Liu, Hao Zhang, Ruiying Lu, Zhengjue Wang, Xin Yuan

With the knowledge of masks, optimization algorithms or deep learning methods are employed to reconstruct the desired high-speed video frames from this snapshot measurement.

Compressive Sensing Demosaicking +1

Multi-Channel and Multi-Microphone Acoustic Echo Cancellation Using A Deep Learning Based Approach

no code implementations3 Mar 2021 Hao Zhang, DeLiang Wang

Building on the deep learning based acoustic echo cancellation (AEC) in the single-loudspeaker (single-channel) and single-microphone setup, this paper investigates multi-channel AEC (MCAEC) and multi-microphone AEC (MMAEC).

Acoustic echo cancellation

MetaSCI: Scalable and Adaptive Reconstruction for Video Compressive Sensing

2 code implementations CVPR 2021 Zhengjue Wang, Hao Zhang, Ziheng Cheng, Bo Chen, Xin Yuan

To capture high-speed videos using a two-dimensional detector, video snapshot compressive imaging (SCI) is a promising system, where the video frames are coded by different masks and then compressed to a snapshot measurement.

Compressive Sensing Video Compressive Sensing

TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models

1 code implementation16 Feb 2021 Zhuohan Li, Siyuan Zhuang, Shiyuan Guo, Danyang Zhuo, Hao Zhang, Dawn Song, Ion Stoica

With this key idea, we design TeraPipe, a high-performance token-level pipeline parallel algorithm for synchronous model-parallel training of Transformer-based language models.

Fast Dynamics in a Model Metallic Glass-forming Material

no code implementations28 Jan 2021 Hao Zhang, Xinyi Wang, Hai-Bin Yu, Jack F. Douglas

We investigate the fast $\beta$- and Johari-Goldstein (JG) $\beta$-relaxation processes, along with the elastic scattering response of glass-forming (GF) liquids and the Boson peak, in a simulated Al-Sm GF material exhibiting a fragile-strong (FS) transition.

Materials Science

Dynamic Heterogeneity, Cooperative Motion, and Johari-Goldstein $β$-Relaxation in a Metallic Glass-Forming Material Exhibiting a Fragile to Strong Transition

no code implementations27 Jan 2021 Hao Zhang, Xinyi Wang, Hai-Bin Yu, Jack F. Douglas

We investigate the Johari-Goldstein (JG) $\beta$-relaxation process in a model metallic glass-forming (GF) material (Al90Sm10), previously studied extensively by both frequency-dependent mechanical measurements and simulation studies devoted to equilibrium properties, by molecular dynamics simulations based on validated and optimized interatomic potentials with the primary aim of better understanding the nature of this universal relaxation process from a dynamic heterogeneity (DH) perspective.

Materials Science

Data Association Between Perception and V2V Communication Sensors

no code implementations20 Jan 2021 Mustafa Ridvan Cantas, Arpita Chand, Hao Zhang, Gopi Chandra Surnilla, Levent Guvenc

The connectivity between vehicles, infrastructure, and other traffic participants brings a new dimension to automotive safety applications.

Decision Making Robotics Systems and Control Systems and Control

Reinforcement Learning for Flexibility Design Problems

no code implementations2 Jan 2021 Yehua Wei, Lei Zhang, Ruiyi Zhang, Shijing Si, Hao Zhang, Lawrence Carin

Flexibility design problems are a class of problems that appear in strategic decision-making across industries, where the objective is to design a ($e. g.$, manufacturing) network that affords flexibility and adaptivity.

Decision Making

Towards Understanding and Improving Dropout in Game Theory

no code implementations ICLR 2021 Hao Zhang, Sen Li, Yinchao Ma, Mingjie Li, Yichen Xie, Quanshi Zhang

Experimental results on various DNNs and datasets have shown that the interaction loss can effectively improve the utility of dropout and boost the performance of DNNs.

An Embarrassingly Simple Model for Dialogue Relation Extraction

no code implementations27 Dec 2020 Fuzhao Xue, Aixin Sun, Hao Zhang, Eng Siong Chng

Dialogue relation extraction (RE) is to predict the relation type of two entities mentioned in a dialogue.

Dialog Relation Extraction

Simultaneous View and Feature Selection for Collaborative Multi-Robot Perception

no code implementations17 Dec 2020 Brian Reily, Hao Zhang

In this paper, we propose a novel approach to collaborative multi-robot perception that simultaneously integrates view selection, feature selection, and object recognition into a unified regularized optimization formulation, which uses sparsity-inducing norms to identify the robots with the most representative views and the modalities with the most discriminative features.

Feature Selection Object Recognition

Roof-GAN: Learning to Generate Roof Geometry and Relations for Residential Houses

1 code implementation CVPR 2021 Yiming Qian, Hao Zhang, Yasutaka Furukawa

This paper presents Roof-GAN, a novel generative adversarial network that generates structured geometry of residential roof structures as a set of roof primitives and their relationships.

Unsupervised Image Segmentation using Mutual Mean-Teaching

no code implementations16 Dec 2020 Zhichao Wu, Lei Guo, Hao Zhang, Dan Xu

Unsupervised image segmentation aims at assigning the pixels with similar feature into a same cluster without annotation, which is an important task in computer vision.

Semantic Segmentation Unsupervised Image Segmentation

GDPNet: Refining Latent Multi-View Graph for Relation Extraction

1 code implementation12 Dec 2020 Fuzhao Xue, Aixin Sun, Hao Zhang, Eng Siong Chng

Recent advances on RE task are from BERT-based sequence modeling and graph-based modeling of relationships among the tokens in the sequence.

Ranked #2 on Dialog Relation Extraction on DialogRE (F1c (v1) metric)

Dialog Relation Extraction Dynamic Time Warping

One Point is All You Need: Directional Attention Point for Feature Learning

no code implementations11 Dec 2020 Liqiang Lin, Pengdi Huang, Chi-Wing Fu, Kai Xu, Hao Zhang, Hui Huang

We present a novel attention-based mechanism for learning enhanced point features for tasks such as point cloud classification and segmentation.

Point Cloud Classification

D$^2$IM-Net: Learning Detail Disentangled Implicit Fields from Single Images

no code implementations11 Dec 2020 Manyi Li, Hao Zhang

We present the first single-view 3D reconstruction network aimed at recovering geometric details from an input image which encompass both topological shape structures and surface features.

3D Reconstruction Single-View 3D Reconstruction

LayoutGMN: Neural Graph Matching for Structural Layout Similarity

1 code implementation CVPR 2021 Akshay Gadi Patil, Manyi Li, Matthew Fisher, Manolis Savva, Hao Zhang

In particular, retrieval results by our network better match human judgement of structural layout similarity compared to both IoUs and other baselines including a state-of-the-art method based on graph neural networks and image convolution.

Graph Matching Metric Learning

Bidirectional Convolutional Poisson Gamma Dynamical Systems

1 code implementation NeurIPS 2020 Wenchao Chen, Chaojie Wang, Bo Chen, Yicheng Liu, Hao Zhang, Mingyuan Zhou

Incorporating the natural document-sentence-word structure into hierarchical Bayesian modeling, we propose convolutional Poisson gamma dynamical systems (PGDS) that introduce not only word-level probabilistic convolutions, but also sentence-level stochastic temporal transitions.

Bayesian Inference Variational Inference

Deep Relational Topic Modeling via Graph Poisson Gamma Belief Network

no code implementations NeurIPS 2020 Chaojie Wang, Hao Zhang, Bo Chen, Dongsheng Wang, Zhengjue Wang, Mingyuan Zhou

To analyze a collection of interconnected documents, relational topic models (RTMs) have been developed to describe both the link structure and document content, exploring their underlying relationships via a single-layer latent representation with limited expressive capability.

Topic Models

Semi-supervised URL Segmentation with Recurrent Neural Networks Pre-trained on Knowledge Graph Entities

1 code implementation COLING 2020 Hao Zhang, Jae Ro, Richard Sproat

Breaking domain names such as openresearch into component words open and research is important for applications like Text-to-Speech synthesis and web search.

Chinese Word Segmentation Speech Synthesis +1

Multi-view Sensor Fusion by Integrating Model-based Estimation and Graph Learning for Collaborative Object Localization

no code implementations16 Nov 2020 Peng Gao, Rui Guo, HongSheng Lu, Hao Zhang

Collaborative object localization aims to collaboratively estimate locations of objects observed from multiple views or perspectives, which is a critical ability for multi-agent systems such as connected vehicles.

Autonomous Driving Graph Learning +1

Semi-supervised URL Segmentation with Recurrent Neural NetworksPre-trained on Knowledge Graph Entities

1 code implementation5 Nov 2020 Hao Zhang, Jae Ro, Richard Sproat

Breaking domain names such as openresearch into component words open and research is important for applications like Text-to-Speech synthesis and web search.

Chinese Word Segmentation Speech Synthesis +1

Dynamic radiomics: a new methodology to extract quantitative time-related features from tomographic images

no code implementations1 Nov 2020 Fengying Che, Ruichuan Shi, Jian Wu, Haoran Li, Shuqin Li, Weixing Chen, Hao Zhang, Zhi Li, Xiaoyu Cui

The feature extraction methods of radiomics are mainly based on static tomographic images at a certain moment, while the occurrence and development of disease is a dynamic process that cannot be fully reflected by only static characteristics.

Technical Note: Game-Theoretic Interactions of Different Orders

no code implementations28 Oct 2020 Hao Zhang, Xu Cheng, Yiting Chen, Quanshi Zhang

In this study, we define interaction components of different orders between two input variables based on game theory.

A Novel Self-Packaged DBBPF With Multiple TZs for 5G Applications

no code implementations14 Oct 2020 Hao Zhang

This DBBPF is excited by a pair of U-shape feed lines, which are designed on G6 to fully excite the resonators and to introduce source/load TZs at the same time.

TM-NET: Deep Generative Networks for Textured Meshes

no code implementations13 Oct 2020 Lin Gao, Tong Wu, Yu-Jie Yuan, Ming-Xian Lin, Yu-Kun Lai, Hao Zhang

We introduce a conditional autoregressive model for texture generation, which can be conditioned on both part geometry and textures already generated for other parts to achieve texture compatibility.


Interpreting Multivariate Shapley Interactions in DNNs

no code implementations10 Oct 2020 Hao Zhang, Yichen Xie, Longjie Zheng, Die Zhang, Quanshi Zhang

In this paper, we define and quantify the significance of interactions among multiple input variables of the DNN.

Context Modeling with Evidence Filter for Multiple Choice Question Answering

no code implementations6 Oct 2020 Sicheng Yu, Hao Zhang, Wei Jing, Jing Jiang

In addition to the effective reduction of human efforts of our approach compared, through extensive experiments on OpenbookQA, we show that the proposed approach outperforms the models that use the same backbone and more training data; and our parameter analysis also demonstrates the interpretability of our approach.

Machine Reading Comprehension Question Answering

BalaGAN: Image Translation Between Imbalanced Domains via Cross-Modal Transfer

1 code implementation5 Oct 2020 Or Patashnik, Dov Danon, Hao Zhang, Daniel Cohen-Or

State-of-the-art image-to-image translation methods tend to struggle in an imbalanced domain setting, where one image domain lacks richness and diversity.

Image-to-Image Translation Style Transfer +1

BayesAdapter: Being Bayesian, Inexpensively and Reliably, via Bayesian Fine-tuning

1 code implementation5 Oct 2020 Zhijie Deng, Hao Zhang, Xiao Yang, Yinpeng Dong, Jun Zhu

Despite their theoretical appealingness, Bayesian neural networks (BNNs) are left behind in real-world adoption, due to persistent concerns on their scalability, accessibility, and reliability.

Variational Inference

BayesAdapter: Being Bayesian, Inexpensively and Robustly, via Bayesian Fine-tuning

no code implementations28 Sep 2020 Zhijie Deng, Xiao Yang, Hao Zhang, Yinpeng Dong, Jun Zhu

Despite their theoretical appealingness, Bayesian neural networks (BNNs) are falling far behind in terms of adoption in real-world applications compared with normal NNs, mainly due to their limited scalability in training, and low fidelity in their uncertainty estimates.

Variational Inference

Dictionary Learning with Low-rank Coding Coefficients for Tensor Completion

no code implementations26 Sep 2020 Tai-Xiang Jiang, Xi-Le Zhao, Hao Zhang, Michael K. Ng

In this paper, we propose a novel tensor learning and coding model for third-order data completion.

Dictionary Learning

Interpreting and Boosting Dropout from a Game-Theoretic View

no code implementations24 Sep 2020 Hao Zhang, Sen Li, Yinchao Ma, Mingjie Li, Yichen Xie, Quanshi Zhang

This paper aims to understand and improve the utility of the dropout operation from the perspective of game-theoretic interactions.

Compressive spectral image classification using 3D coded convolutional neural network

no code implementations23 Sep 2020 Hao Zhang, Xu Ma, Xianhong Zhao, Gonzalo R. Arce

The accuracy of classification is effectively improved by exploiting the synergy between the deep learning network and coded apertures.

General Classification Hyperspectral Image Classification

Deep N-ary Error Correcting Output Codes

1 code implementation22 Sep 2020 Hao Zhang, Joey Tianyi Zhou, Tianying Wang, Ivor W. Tsang, Rick Siow Mong Goh

To facilitate the training of N-ary ECOC with deep learning base learners, we further propose three different variants of parameter sharing architectures for deep N-ary ECOC.

Ensemble Learning General Classification +2

TAP-Net: Transport-and-Pack using Reinforcement Learning

no code implementations3 Sep 2020 Ruizhen Hu, Juzhan Xu, Bin Chen, Minglun Gong, Hao Zhang, Hui Huang

Using a learning-based approach, a trained network can learn and encode solution patterns to guide the solution of new problem instances instead of executing an expensive online search.

Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning

2 code implementations27 Aug 2020 Aurick Qiao, Sang Keun Choe, Suhas Jayaram Subramanya, Willie Neiswanger, Qirong Ho, Hao Zhang, Gregory R. Ganger, Eric P. Xing

Some recent schedulers choose job resources for users, but do so without awareness of how DL training can be re-optimized to better utilize the provided resources.


COALESCE: Component Assembly by Learning to Synthesize Connections

no code implementations5 Aug 2020 Kangxue Yin, Zhiqin Chen, Siddhartha Chaudhuri, Matthew Fisher, Vladimir G. Kim, Hao Zhang

We introduce COALESCE, the first data-driven framework for component-based shape assembly which employs deep learning to synthesize part connections.

MRGAN: Multi-Rooted 3D Shape Generation with Unsupervised Part Disentanglement

no code implementations25 Jul 2020 Rinon Gal, Amit Bermano, Hao Zhang, Daniel Cohen-Or

Our network encourages disentangled generation of semantic parts via two key ingredients: a root-mixing training strategy which helps decorrelate the different branches to facilitate disentanglement, and a set of loss terms designed with part disentanglement and shape semantics in mind.

3D Shape Generation

TilinGNN: Learning to Tile with Self-Supervised Graph Neural Network

1 code implementation5 Jul 2020 Hao Xu, Ka Hei Hui, Chi-Wing Fu, Hao Zhang

To start, we reformulate tiling as a graph problem by modeling candidate tile locations in the target shape as graph nodes and connectivity between tile locations as edges.

Multi-source Meta Transfer for Low Resource Multiple-Choice Question Answering

no code implementations ACL 2020 Ming Yan, Hao Zhang, Di Jin, Joey Tianyi Zhou

Multiple-choice question answering (MCQA) is one of the most challenging tasks in machine reading comprehension since it requires more advanced reading comprehension skills such as logical reasoning, summarization, and arithmetic operations.

Machine Reading Comprehension Meta-Learning +2

Building Interpretable Interaction Trees for Deep NLP Models

no code implementations29 Jun 2020 Die Zhang, Huilin Zhou, Hao Zhang, Xiaoyi Bao, Da Huo, Ruizhao Chen, Xu Cheng, Mengyue Wu, Quanshi Zhang

This paper proposes a method to disentangle and quantify interactions among words that are encoded inside a DNN for natural language processing.

Predictive and Generative Neural Networks for Object Functionality

1 code implementation28 Jun 2020 Ruizhen Hu, Zihao Yan, Jingwen Zhang, Oliver van Kaick, Ariel Shamir, Hao Zhang, Hui Huang

Given a 3D object in isolation, our functional similarity network (fSIM-NET), a variation of the triplet network, is trained to predict the functionality of the object by inferring functionality-revealing interaction contexts.

RPM-Net: Recurrent Prediction of Motion and Parts from Point Cloud

1 code implementation26 Jun 2020 Zihao Yan, Ruizhen Hu, Xingguang Yan, Luanmin Chen, Oliver van Kaick, Hao Zhang, Hui Huang

We show results of simultaneous motion and part predictions from synthetic and real scans of 3D objects exhibiting a variety of part mobilities, possibly involving multiple movable parts.

Semantic Segmentation

Students Need More Attention: BERT-based AttentionModel for Small Data with Application to AutomaticPatient Message Triage

1 code implementation22 Jun 2020 Shijing Si, Rui Wang, Jedrek Wosik, Hao Zhang, David Dov, Guoyin Wang, Ricardo Henao, Lawrence Carin

Small and imbalanced datasets commonly seen in healthcare represent a challenge when training classifiers based on deep learning models.

Rotation-Equivariant Neural Networks for Privacy Protection

no code implementations21 Jun 2020 Hao Zhang, Yiting Chen, Haotian Ma, Xu Cheng, Qihan Ren, Liyao Xiang, Jie Shi, Quanshi Zhang

Compared to the traditional neural network, the RENN uses d-ary vectors/tensors as features, in which each element is a d-ary number.

Deep Autoencoding Topic Model with Scalable Hybrid Bayesian Inference

no code implementations15 Jun 2020 Hao Zhang, Bo Chen, Yulai Cong, Dandan Guo, Hongwei Liu, Mingyuan Zhou

Given a posterior sample of the global parameters, in order to efficiently infer the local latent representations of a document under DATM across all stochastic layers, we propose a Weibull upward-downward variational encoder that deterministically propagates information upward via a deep neural network, followed by a Weibull distribution based stochastic downward generative model.

Bayesian Inference

FAME: 3D Shape Generation via Functionality-Aware Model Evolution

1 code implementation9 May 2020 Yanran Guan, Han Liu, Kun Liu, Kangxue Yin, Ruizhen Hu, Oliver van Kaick, Yan Zhang, Ersin Yumer, Nathan Carr, Radomir Mech, Hao Zhang

Our tool supports constrained modeling, allowing users to restrict or steer the model evolution with functionality labels.


Span-based Localizing Network for Natural Language Video Localization

1 code implementation ACL 2020 Hao Zhang, Aixin Sun, Wei Jing, Joey Tianyi Zhou

Given an untrimmed video and a text query, natural language video localization (NLVL) is to locate a matching span from the video that semantically corresponds to the query.

An Unsupervised Semantic Sentence Ranking Scheme for Text Documents

no code implementations28 Apr 2020 Hao Zhang, Jie Wang

It applies two variants of article-structure-biased PageRank to score phrases and words on the first graph and sentences on the second graph.

Data-Driven Construction of Data Center Graph of Things for Anomaly Detection

no code implementations27 Apr 2020 Hao Zhang, Zhan Li, Zhixing Ren

There are lots of sensors in computer rooms for the DC monitoring system, and they are inherently related.

Anomaly Detection Time Series

Graph2Plan: Learning Floorplan Generation from Layout Graphs

no code implementations27 Apr 2020 Ruizhen Hu, Zeyu Huang, Yuhan Tang, Oliver van Kaick, Hao Zhang, Hui Huang

The core component of our learning framework is a deep neural network, Graph2Plan, which converts a layout graph, along with a building boundary, into a floorplan that fulfills both the layout and boundary constraints.

Ocean Reverberation Suppression via Matrix Completion with Sensor Failure

no code implementations26 Apr 2020 Li-ya Xu, Bin Liao, Hao Zhang, Peng Xiao, Jian-jun Huang

Therefore, it is a challenge for target detection in the ocean reverberation with sensor failure.

Matrix Completion

Simultaneous Learning from Human Pose and Object Cues for Real-Time Activity Recognition

no code implementations26 Mar 2020 Brian Reily, Qingzhao Zhu, Christopher Reardon, Hao Zhang

Real-time human activity recognition plays an essential role in real-world human-centered robotics applications, such as assisted living and human-robot collaboration.

Activity Recognition

Dual-discriminator GAN: A GAN way of profile face recognition

no code implementations20 Mar 2020 Xin-Yu Zhang, Yang Zhao, Hao Zhang

A wealth of angle problems occur when facial recognition is performed: At present, the feature extraction network presents eigenvectors with large differences between the frontal face and profile face recognition of the same person in many cases.

Face Recognition

Deep Quaternion Features for Privacy Protection

no code implementations18 Mar 2020 Hao Zhang, Yi-Ting Chen, Liyao Xiang, Haotian Ma, Jie Shi, Quanshi Zhang

We propose a method to revise the neural network to construct the quaternion-valued neural network (QNN), in order to prevent intermediate-layer features from leaking input information.

Developing a Recommendation Benchmark for MLPerf Training and Inference

no code implementations16 Mar 2020 Carole-Jean Wu, Robin Burke, Ed H. Chi, Joseph Konstan, Julian McAuley, Yves Raimond, Hao Zhang

Deep learning-based recommendation models are used pervasively and broadly, for example, to recommend movies, products, or other information most relevant to users, in order to enhance the user experience.

Image Classification Object Detection +2

Propagating Asymptotic-Estimated Gradients for Low Bitwidth Quantized Neural Networks

no code implementations4 Mar 2020 Jun Chen, Yong liu, Hao Zhang, Shengnan Hou, Jian Yang

Meanwhile, we propose a M-bit Inputs and N-bit Weights Network (MINW-Net) trained by AQE, a quantized neural network with 1-3 bits weights and activations.

GANHopper: Multi-Hop GAN for Unsupervised Image-to-Image Translation

1 code implementation ECCV 2020 Wallace Lira, Johannes Merz, Daniel Ritchie, Daniel Cohen-Or, Hao Zhang

Instead of executing translation directly, we steer the translation by requiring the network to produce in-between images that resemble weighted hybrids between images from the input domains.

Translation Unsupervised Image-To-Image Translation

Graph Ordering: Towards the Optimal by Learning

no code implementations18 Jan 2020 Kangfei Zhao, Yu Rong, Jeffrey Xu Yu, Junzhou Huang, Hao Zhang

However, regardless of the fruitful progress, for some kind of graph applications, such as graph compression and edge partition, it is very hard to reduce them to some graph representation learning tasks.

Combinatorial Optimization Community Detection +3

Efficient Robotic Task Generalization Using Deep Model Fusion Reinforcement Learning

no code implementations11 Dec 2019 Tianying Wang, Hao Zhang, Wei Qi Toh, Hongyuan Zhu, Cheston Tan, Yan Wu, Yong liu, Wei Jing

The proposed method is able to efficiently generalize the previously learned task by model fusion to solve the environment adaptation problem.

RoboCoDraw: Robotic Avatar Drawing with GAN-based Style Transfer and Time-efficient Path Optimization

no code implementations11 Dec 2019 Tianying Wang, Wei Qi Toh, Hao Zhang, Xiuchao Sui, Shaohua Li, Yong liu, Wei Jing

The proposed RoboCoDraw system takes a real human face image as input, converts it to a stylized avatar, then draws it with a robotic arm.

Robotics Graphics

DR-KFS: A Differentiable Visual Similarity Metric for 3D Shape Reconstruction

no code implementations ECCV 2020 Jiongchao Jin, Akshay Gadi Patil, Zhang Xiong, Hao Zhang

We introduce a differential visual similarity metric to train deep neural networks for 3D reconstruction, aimed at improving reconstruction quality.

3D Reconstruction 3D Shape Reconstruction

Towards a Unified Evaluation of Explanation Methods without Ground Truth

no code implementations20 Nov 2019 Hao Zhang, Jiayi Chen, Haotian Xue, Quanshi Zhang

This paper proposes a set of criteria to evaluate the objectiveness of explanation methods of neural networks, which is crucial for the development of explainable AI, but it also presents significant challenges.

BSP-Net: Generating Compact Meshes via Binary Space Partitioning

3 code implementations CVPR 2020 Zhiqin Chen, Andrea Tagliasacchi, Hao Zhang

The network is trained to reconstruct a shape using a set of convexes obtained from a BSP-tree built on a set of planes.

3D Reconstruction 3D Shape Representation

Faster and Safer Training by Embedding High-Level Knowledge into Deep Reinforcement Learning

no code implementations22 Oct 2019 Haodi Zhang, Zihang Gao, Yi Zhou, Hao Zhang, Kaishun Wu, Fangzhen Lin

Deep reinforcement learning has been successfully used in many dynamic decision making domains, especially those with very large state spaces.

Decision Making

Generating an Overview Report over Many Documents

no code implementations17 Aug 2019 Jingwen Wang, Hao Zhang, Cheng Zhang, Wenjing Yang, Liqun Shao, Jie Wang

To overcome this obstacle, we present NDORGS (Numerous Documents' Overview Report Generation Scheme) that integrates text filtering, keyword scoring, single-document summarization (SDS), topic modeling, MDS, and title generation to generate a coherent, well-structured ORPT.

Decision Making Document Summarization +1

SDM-NET: Deep Generative Network for Structured Deformable Mesh

no code implementations13 Aug 2019 Lin Gao, Jie Yang, Tong Wu, Yu-Jie Yuan, Hongbo Fu, Yu-Kun Lai, Hao Zhang

At the structural level, we train a Structured Parts VAE (SP-VAE), which jointly learns the part structure of a shape collection and the part geometries, ensuring a coherence between global shape structure and surface details.

An End-to-End Neural Network for Image Cropping by Learning Composition from Aesthetic Photos

2 code implementations2 Jul 2019 Peng Lu, Hao Zhang, Xujun Peng, Xiaofu Jin

In this paper, we primarily focus on improving the accuracy of automatic image cropping, and on further exploring its potential in public datasets with high efficiency.

Image Cropping

Improving Performance of End-to-End ASR on Numeric Sequences

no code implementations1 Jul 2019 Cal Peyser, Hao Zhang, Tara N. Sainath, Zelin Wu

This out-of-vocabulary (OOV) issue is addressed in conventional ASR systems by training part of the model on spoken domain utterances (e. g.

Speech Recognition

Neural Models of Text Normalization for Speech Applications

no code implementations CL 2019 Hao Zhang, Richard Sproat, Axel H. Ng, Felix Stahlberg, Xiaochang Peng, Kyle Gorman, Brian Roark

One problem that has been somewhat resistant to effective machine learning solutions is text normalization for speech applications such as text-to-speech synthesis (TTS).

Speech Synthesis Text-To-Speech Synthesis

Next steps of quantum transport in Majorana nanowire devices

no code implementations20 May 2019 Hao Zhang, Dong E. Liu, Michael Wimmer, Leo P. Kouwenhoven

Majorana zero modes are localized quasiparticles that obey non-Abelian exchange statistics.

Mesoscale and Nanoscale Physics

Variational Hetero-Encoder Randomized GANs for Joint Image-Text Modeling

1 code implementation ICLR 2020 Hao Zhang, Bo Chen, Long Tian, Zhengjue Wang, Mingyuan Zhou

For bidirectional joint image-text modeling, we develop variational hetero-encoder (VHE) randomized generative adversarial network (GAN), a versatile deep generative model that integrates a probabilistic text decoder, probabilistic image encoder, and GAN into a coherent end-to-end multi-modality learning framework.

Constrained low-tubal-rank tensor recovery for hyperspectral images mixed noise removal by bilateral random projections

no code implementations15 May 2019 Hao Zhang, Xi-Le Zhao, Tai-Xiang Jiang, Michael Kwok-Po Ng

In this paper, we propose a novel low-tubal-rank tensor recovery model, which directly constrains the tubal rank prior for effectively removing the mixed Gaussian and sparse noise in hyperspectral images.

Hyperspectral Image Denoising Image Denoising

VHEGAN: Variational Hetero-Encoder Randomized GAN for Zero-Shot Learning

no code implementations ICLR 2019 Hao Zhang, Bo Chen, Long Tian, Zhengjue Wang, Mingyuan Zhou

To extract and relate visual and linguistic concepts from images and textual descriptions for text-based zero-shot learning (ZSL), we develop variational hetero-encoder (VHE) that decodes text via a deep probabilisitic topic model, the variational posterior of whose local latent variables is encoded from an image via a Weibull distribution based inference network.

Image Generation Text Generation +2

A Hybrid Precipitation Prediction Method based on Multicellular Gene Expression Programming

no code implementations1 Apr 2019 Hongya Li, Yuzhong Peng, Chuyan Deng, Yonghua Pan, Daoqing Gong, Hao Zhang

Prompt and accurate precipitation forecast is very important for development management of regional water resource, flood disaster prevention and people's daily activity and production plan; however, non-linear and nonstationary characteristics of precipitation data and noise seriously affect forecast accuracy.


A Seft-adaptive Multicellular GEP Algorithm Based On Fuzzy Control For Function Optimization

no code implementations1 Apr 2019 Chuyan Deng, Yuzhong Peng, Hongya Li, Daoqing Gong, Hao Zhang, Zhiping Liu

According to the concentration and dispersion of individual fitness values in population, the crossover rate, mutation rate and real number set mutation rate of genetic operation are dynamically adjusted.

DenseAttentionSeg: Segment Hands from Interacted Objects Using Depth Input

no code implementations29 Mar 2019 Zihao Bo, Hao Zhang, Junhai Yong, Feng Xu

We propose a real-time DNN-based technique to segment hand and object of interacting motions from depth inputs.

Hand Segmentation

BAE-NET: Branched Autoencoder for Shape Co-Segmentation

1 code implementation ICCV 2019 Zhiqin Chen, Kangxue Yin, Matthew Fisher, Siddhartha Chaudhuri, Hao Zhang

The unsupervised BAE-NET is trained with a collection of un-segmented shapes, using a shape reconstruction loss, without any ground-truth labels.

One-Shot Learning Representation Learning

LOGAN: Unpaired Shape Transform in Latent Overcomplete Space

no code implementations25 Mar 2019 Kangxue Yin, Zhiqin Chen, Hui Huang, Daniel Cohen-Or, Hao Zhang

Our network consists of an autoencoder to encode shapes from the two input domains into a common latent space, where the latent codes concatenate multi-scale shape features, resulting in an overcomplete representation.


AdaCoSeg: Adaptive Shape Co-Segmentation with Group Consistency Loss

no code implementations CVPR 2020 Chenyang Zhu, Kai Xu, Siddhartha Chaudhuri, Li Yi, Leonidas Guibas, Hao Zhang

While the part prior network can be trained with noisy and inconsistently segmented shapes, the final output of AdaCoSeg is a consistent part labeling for the input set, with each shape segmented into up to (a user-specified) K parts.

Instance Segmentation Semantic Segmentation

Can learning from natural image denoising be used for seismic data interpolation?

1 code implementation27 Feb 2019 Hao Zhang, Xiuyan Yang, Jianwei Ma

We propose a convolutional neural network (CNN) denoising based method for seismic data interpolation.

De-aliasing Image Denoising

Alternating Synthetic and Real Gradients for Neural Language Modeling

1 code implementation27 Feb 2019 Fangxin Shang, Hao Zhang

Empirically, we demonstrate the effectiveness of alternating training with synthetic and real gradients after periodic warm restarts on language modeling tasks.

Language Modelling

Interpretable Complex-Valued Neural Networks for Privacy Protection

1 code implementation ICLR 2020 Liyao Xiang, Haotian Ma, Hao Zhang, Yifan Zhang, Jie Ren, Quanshi Zhang

Previous studies have found that an adversary attacker can often infer unintended input information from intermediate-layer features.

Learning Implicit Fields for Generative Shape Modeling

3 code implementations CVPR 2019 Zhiqin Chen, Hao Zhang

We advocate the use of implicit fields for learning generative models of shapes and introduce an implicit field decoder, called IM-NET, for shape generation, aimed at improving the visual quality of the generated shapes.

3D Reconstruction 3D Shape Representation +2

Symbolic Graph Reasoning Meets Convolutions

1 code implementation NeurIPS 2018 Xiaodan Liang, Zhiting Hu, Hao Zhang, Liang Lin, Eric P. Xing

To cooperate with local convolutions, each SGR is constituted by three modules: a) a primal local-to-semantic voting module where the features of all symbolic nodes are generated by voting from local representations; b) a graph reasoning module propagates information over knowledge graph to achieve global semantic coherency; c) a dual semantic-to-local mapping module learns new associations of the evolved symbolic nodes with local representations, and accordingly enhances local features.

Image Classification Semantic Segmentation

CompoNet: Learning to Generate the Unseen by Part Synthesis and Composition

1 code implementation ICCV 2019 Nadav Schor, Oren Katzir, Hao Zhang, Daniel Cohen-Or

Data-driven generative modeling has made remarkable progress by leveraging the power of deep neural networks.

Nearly-tight bounds on linear regions of piecewise linear neural networks

no code implementations31 Oct 2018 Qiang Hu, Hao Zhang

The developments of deep neural networks (DNN) in recent years have ushered a brand new era of artificial intelligence.

Deep Poisson gamma dynamical systems

no code implementations NeurIPS 2018 Dandan Guo, Bo Chen, Hao Zhang, Mingyuan Zhou

We develop deep Poisson-gamma dynamical systems (DPGDS) to model sequentially observed multivariate count data, improving previously proposed models by not only mining deep hierarchical latent structure from the data, but also capturing both first-order and long-range temporal dependencies.

Data Augmentation Time Series

Towards Verifying Semantic Roles Co-occurrence

no code implementations9 Oct 2018 Aliaksandr Huminski, Hao Zhang, Gangeshwar Krishnamurthy

Semantic role theory considers roles as a small universal set of unanalyzed entities.

Event Representation through Semantic Roles: Evaluation of Coverage

no code implementations9 Oct 2018 Aliaksandr Huminski, Hao Zhang

Semantic role theory is a widely used approach for event representation.

Toward Understanding the Impact of Staleness in Distributed Machine Learning

no code implementations ICLR 2019 Wei Dai, Yi Zhou, Nanqing Dong, Hao Zhang, Eric P. Xing

Many distributed machine learning (ML) systems adopt the non-synchronous execution in order to alleviate the network communication bottleneck, resulting in stale parameters that do not reflect the latest updates.

Hartley Spectral Pooling for Deep Learning

no code implementations7 Oct 2018 Hao Zhang, Jianwei Ma

In most convolution neural networks (CNNs), downsampling hidden layers is adopted for increasing computation efficiency and the receptive field size.

Dimensionality Reduction

AutoLoss: Learning Discrete Schedules for Alternate Optimization

1 code implementation4 Oct 2018 Haowen Xu, Hao Zhang, Zhiting Hu, Xiaodan Liang, Ruslan Salakhutdinov, Eric Xing

Many machine learning problems involve iteratively and alternately optimizing different task objectives with respect to different sets of parameters.

Image Generation Machine Translation +2

AutoLoss: Learning Discrete Schedule for Alternate Optimization

no code implementations ICLR 2019 Haowen Xu, Hao Zhang, Zhiting Hu, Xiaodan Liang, Ruslan Salakhutdinov, Eric Xing

Many machine learning problems involve iteratively and alternately optimizing different task objectives with respect to different sets of parameters.

Image Generation Machine Translation +1

High-accuracy mass, spin, and recoil predictions of generic black-hole merger remnants

1 code implementation24 Sep 2018 Vijay Varma, Davide Gerosa, François Hébert, Leo C. Stein, Hao Zhang

We present accurate fits for the remnant properties of generically precessing binary black holes, trained on large banks of numerical-relativity simulations.

General Relativity and Quantum Cosmology High Energy Astrophysical Phenomena

SCORES: Shape Composition with Recursive Substructure Priors

no code implementations14 Sep 2018 Chenyang Zhu, Kai Xu, Siddhartha Chaudhuri, Renjiao Yi, Hao Zhang

The network may significantly alter the geometry and structure of the input parts and synthesize a novel shape structure based on the inputs, while adding or removing parts to minimize a structure plausibility loss.

Semantic WordRank: Generating Finer Single-Document Summarizations

no code implementations12 Sep 2018 Hao Zhang, Jie Wang

We present Semantic WordRank (SWR), an unsupervised method for generating an extractive summary of a single document.

Dual-label Deep LSTM Dereverberation For Speaker Verification

no code implementations8 Sep 2018 Hao Zhang, Stephen Zahorian, Xiao Chen, Peter Guzewich, Xiaoyu Liu

In this paper, we present a reverberation removal approach for speaker verification, utilizing dual-label deep neural networks (DNNs).

Speaker Verification

UKP-Athene: Multi-Sentence Textual Entailment for Claim Verification

1 code implementation WS 2018 Andreas Hanselowski, Hao Zhang, Zile Li, Daniil Sorokin, Benjamin Schiller, Claudia Schulz, Iryna Gurevych

The Fact Extraction and VERification (FEVER) shared task was launched to support the development of systems able to verify claims by extracting supporting or refuting facts from raw text.

Entity Linking General Classification +1

Generative Semantic Manipulation with Mask-Contrasting GAN

no code implementations ECCV 2018 Xiaodan Liang, Hao Zhang, Liang Lin, Eric Xing

Despite the promising results on paired/unpaired image-to-image translation achieved by Generative Adversarial Networks (GANs), prior works often only transfer the low-level information (e. g. color or texture changes), but fail to manipulate high-level semantic meanings (e. g., geometric structure or content) of different object regions.

Image-to-Image Translation

SketchyScene: Richly-Annotated Scene Sketches

2 code implementations ECCV 2018 Changqing Zou, Qian Yu, Ruofei Du, Haoran Mo, Yi-Zhe Song, Tao Xiang, Chengying Gao, Baoquan Chen, Hao Zhang

We contribute the first large-scale dataset of scene sketches, SketchyScene, with the goal of advancing research on sketch understanding at both the object and scene level.

Colorization Image Retrieval +1

Fast and Accurate Reordering with ITG Transition RNN

no code implementations COLING 2018 Hao Zhang, Axel Ng, Richard Sproat

Compared to a strong baseline of attention-based RNN, our ITG RNN re-ordering model can reach the same reordering accuracy with only 1/10 of the training data and is 2. 5x faster in decoding.

Feature Engineering Machine Translation +3

GRAINS: Generative Recursive Autoencoders for INdoor Scenes

no code implementations24 Jul 2018 Manyi Li, Akshay Gadi Patil, Kai Xu, Siddhartha Chaudhuri, Owais Khan, Ariel Shamir, Changhe Tu, Baoquan Chen, Daniel Cohen-Or, Hao Zhang

We present a generative neural network which enables us to generate plausible 3D indoor scenes in large quantities and varieties, easily and highly efficiently.


Spin-Orbit Protection of Induced Superconductivity in Majorana Nanowires

1 code implementation5 Jul 2018 Jouri D. S. Bommer, Hao Zhang, Önder Gül, Bas Nijholt, Michael Wimmer, Filipp N. Rybakov, Julien Garaud, Donjan Rodic, Egor Babaev, Matthias Troyer, Diana Car, Sébastien R. Plissard, Erik P. A. M. Bakkers, Kenji Watanabe, Takashi Taniguchi, Leo P. Kouwenhoven

Spin-orbit interaction (SOI) plays a key role in creating Majorana zero modes in semiconductor nanowires proximity coupled to a superconductor.

Mesoscale and Nanoscale Physics

Learning Multi-Instance Enriched Image Representations via Non-Greedy Ratio Maximization of the l1-Norm Distances

no code implementations CVPR 2018 Kai Liu, Hua Wang, Feiping Nie, Hao Zhang

To tackle these two challenges, in this paper we propose a novel image representation learning method that can integrate the local patches (the instances) of an input image (the bag) and its holistic representation into one single-vector representation.

Representation Learning

Semi-Supervised Co-Analysis of 3D Shape Styles from Projected Lines

no code implementations18 Apr 2018 Fenggen Yu, Yan Zhang, Kai Xu, Ali Mahdavi-Amiri, Hao Zhang

We present a semi-supervised co-analysis method for learning 3D shape styles from projected feature lines, achieving style patch localization with only weak supervision.

On the Selection of Anchors and Targets for Video Hyperlinking

no code implementations14 Apr 2018 Zhi-Qi Cheng, Hao Zhang, Xiao Wu, Chong-Wah Ngo

A principle way of hyperlinking can be carried out by picking centers of clusters as anchors and from there reach out to targets within or outside of clusters with consideration of neighborhood complexity.

P2P-NET: Bidirectional Point Displacement Net for Shape Transform

no code implementations25 Mar 2018 Kangxue Yin, Hui Huang, Daniel Cohen-Or, Hao Zhang

We introduce P2P-NET, a general-purpose deep neural network which learns geometric transformations between point-based shape representations from two domains, e. g., meso-skeletons and surfaces, partial and complete scans, etc.

BSD-GAN: Branched Generative Adversarial Network for Scale-Disentangled Representation Learning and Image Synthesis

2 code implementations22 Mar 2018 Zili Yi, Zhiqin Chen, Hao Cai, Wendong Mao, Minglun Gong, Hao Zhang

The key feature of BSD-GAN is that it is trained in multiple branches, progressively covering both the breadth and depth of the network, as resolutions of the training images increase to reveal finer-scale features.

Image Generation Representation Learning

WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling

1 code implementation ICLR 2018 Hao Zhang, Bo Chen, Dandan Guo, Mingyuan Zhou

To train an inference network jointly with a deep generative topic model, making it both scalable to big corpora and fast in out-of-sample prediction, we develop Weibull hybrid autoencoding inference (WHAI) for deep latent Dirichlet allocation, which infers posterior samples via a hybrid of stochastic-gradient MCMC and autoencoding variational Bayes.

High-throughput, high-resolution registration-free generated adversarial network microscopy

1 code implementation7 Jan 2018 Hao Zhang, Xinlin Xie, Chunyu Fang, Yicong Yang, Di Jin, Peng Fei

We combine generative adversarial network (GAN) with light microscopy to achieve deep learning super-resolution under a large field of view (FOV).

Image Registration Image Super-Resolution

Cavs: A Vertex-centric Programming Interface for Dynamic Neural Networks

no code implementations11 Dec 2017 Hao Zhang, Shizhen Xu, Graham Neubig, Wei Dai, Qirong Ho, Guangwen Yang, Eric P. Xing

Recent deep learning (DL) models have moved beyond static network architectures to dynamic ones, handling data where the network structure changes every example, such as sequences of variable lengths, trees, and graphs.

graph construction

Efficient and Effective Single-Document Summarizations and A Word-Embedding Measurement of Quality

no code implementations1 Oct 2017 Liqun Shao, Hao Zhang, Ming Jia, Jie Wang

We show that the orderings of the ROUGE and WESM scores of our algorithms are highly comparable, suggesting that WESM may serve as a viable alternative for measuring the quality of a summary.

Keyword Extraction

Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning

2 code implementations28 Sep 2017 Pinxin Long, Tingxiang Fan, Xinyi Liao, Wenxi Liu, Hao Zhang, Jia Pan

We validate the learned sensor-level collision avoidance policy in a variety of simulated scenarios with thorough performance evaluations and show that the final learned policy is able to find time efficient, collision-free paths for a large-scale robot system.

Mining Deep And-Or Object Structures via Cost-Sensitive Question-Answer-Based Active Annotations

no code implementations13 Aug 2017 Quanshi Zhang, Ying Nian Wu, Hao Zhang, Song-Chun Zhu

The loss is defined for nodes in all layers of the AOG, including the generative loss (measuring the likelihood of the images) and the discriminative loss (measuring the fitness to human answers).

Question Answering

Generative Semantic Manipulation with Contrasting GAN

no code implementations1 Aug 2017 Xiaodan Liang, Hao Zhang, Eric P. Xing

Generative Adversarial Networks (GANs) have recently achieved significant improvement on paired/unpaired image-to-image translation, such as photo$\rightarrow$ sketch and artist painting style transfer.

Image-to-Image Translation Style Transfer

Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters

no code implementations11 Jun 2017 Hao Zhang, Zeyu Zheng, Shizhen Xu, Wei Dai, Qirong Ho, Xiaodan Liang, Zhiting Hu, Jinliang Wei, Pengtao Xie, Eric P. Xing

We show that Poseidon enables Caffe and TensorFlow to achieve 15. 5x speed-up on 16 single-GPU machines, even with limited bandwidth (10GbE) and the challenging VGG19-22K network for image classification.

Image Classification

GRASS: Generative Recursive Autoencoders for Shape Structures

no code implementations5 May 2017 Jun Li, Kai Xu, Siddhartha Chaudhuri, Ersin Yumer, Hao Zhang, Leonidas Guibas

We introduce a novel neural network architecture for encoding and synthesis of 3D shapes, particularly their structures.