Search Results for author: Bo Zhang

Found 145 papers, 57 papers with code

Understanding and Stabilizing GANs' Training Dynamics Using Control Theory

no code implementations ICML 2020 Kun Xu, Chongxuan Li, Jun Zhu, Bo Zhang

There are existing efforts that model the training dynamics of GANs in the parameter space but the analysis cannot directly motivate practically effective stabilizing methods.

Entity Relation Extraction as Dependency Parsing in Visually Rich Documents

no code implementations EMNLP 2021 Yue Zhang, Bo Zhang, Rui Wang, Junjie Cao, Chen Li, Zuyi Bao

Previous works on key information extraction from visually rich documents (VRDs) mainly focus on labeling the text within each bounding box (i. e., semantic entity), while the relations in-between are largely unexplored.

Dependency Parsing Key Information Extraction +1

Multiplex Behavioral Relation Learning for Recommendation via Memory Augmented Transformer Network

1 code implementation8 Oct 2021 Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Bo Zhang, Liefeng Bo

The overlook of multiplex behavior relations can hardly recognize the multi-modal contextual signals across different types of interactions, which limit the feasibility of current recommendation methods.

Recommendation Systems

Generating Transferable Adversarial Patch by Simultaneously Optimizing its Position and Perturbations

no code implementations29 Sep 2021 Xingxing Wei, Ying Guo, Jie Yu, Huanqian Yan, Bo Zhang

In this paper, we propose a method to simultaneously optimize the position and perturbation to generate transferable adversarial patches, and thus obtain high attack success rates in the black-box setting.

Face Recognition

Enhancing the Transferability of Adversarial Attacks via Scale Ensemble

no code implementations29 Sep 2021 Xianfeng Gao, Zhikai Chen, Bo Zhang

The experiments on ImageNet show that our method successfully mitigates the gap of transferability between models with different input sizes and achieves about 8% higher success rate comparing with the state-of-the-art input transformation methods.

Fast Density Estimation for Density-based Clustering Methods

no code implementations23 Sep 2021 Difei Cheng, Ruihang Xu, Bo Zhang

Density-based clustering algorithms are widely used for discovering clusters in pattern recognition and machine learning since they can deal with non-hyperspherical clusters and are robustness to handle outliers.

Density Estimation

Joint Distribution Alignment via Adversarial Learning for Domain Adaptive Object Detection

no code implementations19 Sep 2021 Bo Zhang, Tao Chen, Bin Wang, Ruoyao Li

Unsupervised domain adaptive object detection aims to adapt a well-trained detector from its original source domain with rich labeled data to a new target domain with unlabeled data.

Object Detection Unsupervised Domain Adaptation

Object-aware Long-short-range Spatial Alignment for Few-Shot Fine-Grained Image Classification

no code implementations30 Aug 2021 Yike Wu, Bo Zhang, Gang Yu, Weixi Zhang, Bin Wang, Tao Chen, Jiayuan Fan

The goal of few-shot fine-grained image classification is to recognize rarely seen fine-grained objects in the query set, given only a few samples of this class in the support set.

Fine-Grained Image Classification Semantic correspondence +2

Densely Semantic Enhancement for Domain Adaptive Region-free Detectors

no code implementations30 Aug 2021 Bo Zhang, Tao Chen, Bin Wang, Xiaofeng Wu, Liming Zhang, Jiayuan Fan

Unsupervised domain adaptive object detection aims to adapt a well-trained detector from its original source domain with rich labeled data to a new target domain with unlabeled data.

Object Detection Region Proposal

OPA: Object Placement Assessment Dataset

1 code implementation5 Jul 2021 Liu Liu, Bo Zhang, Jiangtong Li, Li Niu, Qingyang Liu, Liqing Zhang

Image composition aims to generate realistic composite image by inserting an object from one image into another background image, where the placement (e. g., location, size, occlusion) of inserted object may be unreasonable, which would significantly degrade the quality of the composite image.

Understanding Adversarial Attacks on Observations in Deep Reinforcement Learning

no code implementations30 Jun 2021 You Qiaoben, Chengyang Ying, Xinning Zhou, Hang Su, Jun Zhu, Bo Zhang

Following the analysis of the function space, we design a generic two-stage framework in the subspace where the adversary lures the agent to a target trajectory or a deceptive policy.

Making Images Real Again: A Comprehensive Survey on Deep Image Composition

1 code implementation28 Jun 2021 Li Niu, Wenyan Cong, Liu Liu, Yan Hong, Bo Zhang, Jing Liang, Liqing Zhang

Datasets and codes for image composition are summarized at https://github. com/bcmi/Awesome-Image-Composition.

Stability and Generalization of Bilevel Programming in Hyperparameter Optimization

1 code implementation NeurIPS 2021 Fan Bao, Guoqiang Wu, Chongxuan Li, Jun Zhu, Bo Zhang

Our results can explain some mysterious behaviours of the bilevel programming in practice, for instance, overfitting to the validation set.

Hyperparameter Optimization

Robust Mutual Learning for Semi-supervised Semantic Segmentation

no code implementations1 Jun 2021 Pan Zhang, Bo Zhang, Ting Zhang, Dong Chen, Fang Wen

The proposed robust mutual learning demonstrates state-of-the-art performance on semantic segmentation in low-data regime.

Rectification Semi-Supervised Semantic Segmentation

A Unified Span-Based Approach for Opinion Mining with Syntactic Constituents

1 code implementation NAACL 2021 Qingrong Xia, Bo Zhang, Rui Wang, Zhenghua Li, Yue Zhang, Fei Huang, Luo Si, Min Zhang

Fine-grained opinion mining (OM) has achieved increasing attraction in the natural language processing (NLP) community, which aims to find the opinion structures of {``}Who expressed what opinions towards what{''} in one sentence.

Multi-Task Learning Opinion Mining

Twins: Revisiting the Design of Spatial Attention in Vision Transformers

5 code implementations NeurIPS 2021 Xiangxiang Chu, Zhi Tian, Yuqing Wang, Bo Zhang, Haibing Ren, Xiaolin Wei, Huaxia Xia, Chunhua Shen

Very recently, a variety of vision transformer architectures for dense prediction tasks have been proposed and they show that the design of spatial attention is critical to their success in these tasks.

Image Classification Semantic Segmentation

Microshift: An Efficient Image Compression Algorithm for Hardware

1 code implementation20 Apr 2021 Bo Zhang, Pedro V. Sander, Chi-Ying Tsui, Amine Bermak

In our method, the image is first micro-shifted, then the sub-quantized values are further compressed.

Image Compression

Let's See Clearly: Contaminant Artifact Removal for Moving Cameras

no code implementations ICCV 2021 Xiaoyu Li, Bo Zhang, Jing Liao, Pedro V. Sander

This new dataset and our novel framework lead to our method that is able to address different contaminants and outperforms competitive restoration approaches both qualitatively and quantitatively.

Video Restoration

Estimating and Improving Dynamic Treatment Regimes With a Time-Varying Instrumental Variable

no code implementations15 Apr 2021 Shuxiao Chen, Bo Zhang

Estimating dynamic treatment regimes (DTRs) from retrospective observational data is challenging as some degree of unmeasured confounding is often expected.

Meaningful Adversarial Stickers for Face Recognition in Physical World

no code implementations14 Apr 2021 Ying Guo, Xingxing Wei, Guoqiu Wang, Bo Zhang

Face recognition (FR) systems have been widely applied in safety-critical fields with the introduction of deep learning.

Face Recognition Time Series

Image Composition Assessment with Saliency-augmented Multi-pattern Pooling

1 code implementation7 Apr 2021 Bo Zhang, Li Niu, Liqing Zhang

Image composition assessment is crucial in aesthetic assessment, which aims to assess the overall composition quality of a given image.

Aesthetics Quality Assessment

MagDR: Mask-guided Detection and Reconstruction for Defending Deepfakes

no code implementations CVPR 2021 Zhikai Chen, Lingxi Xie, Shanmin Pang, Yong He, Bo Zhang

This paper presents MagDR, a mask-guided detection and reconstruction pipeline for defending deepfakes from adversarial attacks.

Extragalactic HI 21-cm absorption line observations with the Five-hundred-meter Aperture Spherical radio Telescope

no code implementations11 Mar 2021 Bo Zhang, Ming Zhu, Zhong-Zu Wu, Qing-Zheng Yu, Peng Jiang, You-Ling Yue, Meng-Lin Huang, Qiao-Li Hao

Our observations successfully confirmed the existence of HI absorption lines in all these systems, including two sources that were marginally detected by ALFALFA.

Astrophysics of Galaxies

Style-based Point Generator with Adversarial Rendering for Point Cloud Completion

1 code implementation CVPR 2021 Chulin Xie, Chuxin Wang, Bo Zhang, Hao Yang, Dong Chen, Fang Wen

In this paper, we proposed a novel Style-based Point Generator with Adversarial Rendering (SpareNet) for point cloud completion.

 Ranked #1 on Point Cloud Completion on ShapeNet (Earth Mover's Distance metric)

Point Cloud Completion

A Minimax Probability Machine for Non-Decomposable Performance Measures

no code implementations28 Feb 2021 JunRu Luo, Hong Qiao, Bo Zhang

On the other hand, the minimax probability machine is a popular method for binary classification problems and aims at learning a linear classifier by maximizing the accuracy rate, which makes it unsuitable to deal with imbalanced classification tasks.

Classification General Classification +1

Learning with Smooth Hinge Losses

no code implementations27 Feb 2021 JunRu Luo, Hong Qiao, Bo Zhang

Due to the non-smoothness of the Hinge loss in SVM, it is difficult to obtain a faster convergence rate with modern optimization algorithms.

Text Classification

Conditional Positional Encodings for Vision Transformers

1 code implementation22 Feb 2021 Xiangxiang Chu, Zhi Tian, Bo Zhang, Xinlong Wang, Xiaolin Wei, Huaxia Xia, Chunhua Shen

Benefit from the conditional positional encoding scheme, we obtain state-of-the-art results on the ImageNet classification task compared with vision Transformers to date.

AutoML Classification +3

Improving Accuracy and Diversity in Matching of Recommendation with Diversified Preference Network

no code implementations7 Feb 2021 Ruobing Xie, Qi Liu, Shukai Liu, Ziwei Zhang, Peng Cui, Bo Zhang, Leyu Lin

In this paper, we propose a novel Heterogeneous graph neural network framework for diversified recommendation (GraphDR) in matching to improve both recommendation accuracy and diversity.

Graph Attention Recommendation Systems

The Flare and Warp of the Young Stellar Disk traced with LAMOST DR5 OB-type stars

no code implementations1 Feb 2021 Yang Yu, Hai-Feng Wang, Wen-Yuan Cui, Lin-Lin Li, Chao Liu, Bo Zhang, Hao Tian, Zhen-Yan Huo, Jie Ju, Zhi-Cun Liu, Fang Wen, Shuai Feng

We present analysis of the spatial density structure for the outer disk from 8$-$14 \, kpc with the LAMOST DR5 13534 OB-type stars and observe similar flaring on north and south sides of the disk implying that the flaring structure is symmetrical about the Galactic plane, for which the scale height at different Galactocentric distance is from 0. 14 to 0. 5 \, kpc.

Astrophysics of Galaxies

Robust Dynamical Decoupling for the Manipulation of a Spin Network via a Single Spin

no code implementations11 Jan 2021 Xiaodong Yang, Yunrui Ge, Bo Zhang, Jun Li

High-fidelity control of quantum systems is crucial for quantum information processing, but is often limited by perturbations from the environment and imperfections in the applied control fields.

Quantum Physics

Exploring the Galactic Anticenter substructure with LAMOST & Gaia DR2

no code implementations7 Jan 2021 Jing Li, Xiang-Xiang Xue, Chao Liu, Bo Zhang, Hans-Walter Rix, Jeffrey L. Carlin, Chengqun Yang, Rene A. Mendez, Jing Zhong, Hao Tian, Lan Zhang, Yan Xu, Yaqian Wu, Gang Zhao, Ruixiang Chang

Their location in [$\alpha$/M] vs. [M/H] space is more metal poor than typical thin disk stars, with [$\alpha$/M] \textbf{lower} than the thick disk.

Astrophysics of Galaxies

HCGrid: A Convolution-based Gridding Framework for RadioAstronomy in Hybrid Computing Environments

1 code implementation24 Dec 2020 Hao Wang, Ce Yu, Bo Zhang, Jian Xiao, Qi Luo

Gridding operation, which is to map non-uniform data samples onto a uniformly distributedgrid, is one of the key steps in radio astronomical data reduction process.

Instrumentation and Methods for Astrophysics

Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models

1 code implementation NeurIPS Workshop ICBINB 2020 Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang

The learning and evaluation of energy-based latent variable models (EBLVMs) without any structural assumptions are highly challenging, because the true posteriors and the partition functions in such models are generally intractable.

Latent Variable Models

Bi-level Score Matching for Learning Energy-based Latent Variable Models

1 code implementation NeurIPS 2020 Fan Bao, Chongxuan Li, Kun Xu, Hang Su, Jun Zhu, Bo Zhang

This paper presents a bi-level score matching (BiSM) method to learn EBLVMs with general structures by reformulating SM as a bi-level optimization problem.

Latent Variable Models Stochastic Optimization

Old Photo Restoration via Deep Latent Space Translation

5 code implementations14 Sep 2020 Zi-Yu Wan, Bo Zhang, Dong-Dong Chen, Pan Zhang, Dong Chen, Jing Liao, Fang Wen

Unlike conventional restoration tasks that can be solved through supervised learning, the degradation in real photos is complex and the domain gap between synthetic images and real old photos makes the network fail to generalize.

Image Restoration Translation

A Simple and General Graph Neural Network with Stochastic Message Passing

no code implementations5 Sep 2020 Ziwei Zhang, Chenhao Niu, Peng Cui, Bo Zhang, Wei Cui, Wenwu Zhu

Specifically, we augment the existing GNNs with stochastic node representations learned to preserve node proximities.

Link Prediction Node Classification

Deep Sketch-guided Cartoon Video Inbetweening

1 code implementation10 Aug 2020 Xiaoyu Li, Bo Zhang, Jing Liao, Pedro V. Sander

The key idea of the proposed approach is to estimate the dense cross-domain correspondence between the sketch and cartoon video frames, and employ a blending module with occlusion estimation to synthesize the middle frame guided by the sketch.

Image Generation Occlusion Estimation

Training Interpretable Convolutional Neural Networks by Differentiating Class-specific Filters

1 code implementation ECCV 2020 Haoyu Liang, Zhihao Ouyang, Yuyuan Zeng, Hang Su, Zihao He, Shu-Tao Xia, Jun Zhu, Bo Zhang

Most existing works attempt post-hoc interpretation on a pre-trained model, while neglecting to reduce the entanglement underlying the model.

Object Localization

Free-Space Optical Communication Using Non-mode-Selective Photonic Lantern Based Coherent Receiver

no code implementations3 Jul 2020 Bo Zhang, Renzhi Yuan, Jianfeng Sun, Julian Cheng, Mohamed-Slim Alouini

A free-space optical communication system using non-mode-selective photonic lantern (PL) based coherent receiver is studied.

Syntax-Aware Opinion Role Labeling with Dependency Graph Convolutional Networks

no code implementations ACL 2020 Bo Zhang, Yue Zhang, Rui Wang, Zhenghua Li, Min Zhang

The experimental results show that syntactic information is highly valuable for ORL, and our final MTL model effectively boosts the F1 score by 9. 29 over the syntax-agnostic baseline.

Fine-Grained Opinion Analysis Multi-Task Learning

Noisy Differentiable Architecture Search

1 code implementation7 May 2020 Xiangxiang Chu, Bo Zhang

However, it largely suffers from the well-known performance collapse issue due to the aggregation of skip connections.

Image Classification Neural Architecture Search

Bringing Old Photos Back to Life

5 code implementations CVPR 2020 Zi-Yu Wan, Bo Zhang, Dong-Dong Chen, Pan Zhang, Dong Chen, Jing Liao, Fang Wen

Unlike conventional restoration tasks that can be solved through supervised learning, the degradation in real photos is complex and the domain gap between synthetic images and real old photos makes the network fail to generalize.

Image Restoration Translation

Automatic, Dynamic, and Nearly Optimal Learning Rate Specification by Local Quadratic Approximation

1 code implementation7 Apr 2020 Yingqiu Zhu, Yu Chen, Danyang Huang, Bo Zhang, Hansheng Wang

In each update step, given the gradient direction, we locally approximate the loss function by a standard quadratic function of the learning rate.

Sex Differences in Severity and Mortality Among Patients With COVID-19: Evidence from Pooled Literature Analysis and Insights from Integrated Bioinformatic Analysis

no code implementations30 Mar 2020 Xiyi Wei, Yu-Tian Xiao, Jian Wang, Rui Chen, Wei zhang, Yue Yang, Daojun Lv, Chao Qin, Di Gu, Bo Zhang, Weidong Chen, Jianquan Hou, Ninghong Song, Guohua Zeng, Shancheng Ren

Objective: To conduct a meta-analysis of current studies that examined sex differences in severity and mortality in patients with COVID-19, and identify potential mechanisms underpinning these differences.

Perceptual Image Super-Resolution with Progressive Adversarial Network

no code implementations8 Mar 2020 Lone Wong, Deli Zhao, Shaohua Wan, Bo Zhang

Progressive growing enhances image resolution gradually, thereby preserving precision of recovered image.

Image Super-Resolution

User-Level Privacy-Preserving Federated Learning: Analysis and Performance Optimization

no code implementations29 Feb 2020 Kang Wei, Jun Li, Ming Ding, Chuan Ma, Hang Su, Bo Zhang, H. Vincent Poor

According to our analysis, the UDP framework can realize $(\epsilon_{i}, \delta_{i})$-LDP for the $i$-th MT with adjustable privacy protection levels by varying the variances of the artificial noise processes.

Federated Learning

Beyond Clicks: Modeling Multi-Relational Item Graph for Session-Based Target Behavior Prediction

1 code implementation19 Feb 2020 Wen Wang, Wei zhang, Shukai Liu, Qi Liu, Bo Zhang, Leyu Lin, Hongyuan Zha

Specifically, we build a Multi-Relational Item Graph (MRIG) based on all behavior sequences from all sessions, involving target and auxiliary behavior types.

Representation Learning

A Wasserstein Minimum Velocity Approach to Learning Unnormalized Models

1 code implementation pproximateinference AABI Symposium 2019 Ziyu Wang, Shuyu Cheng, Yueru Li, Jun Zhu, Bo Zhang

Score matching provides an effective approach to learning flexible unnormalized models, but its scalability is limited by the need to evaluate a second-order derivative.

MixPath: A Unified Approach for One-shot Neural Architecture Search

1 code implementation16 Jan 2020 Xiangxiang Chu, Xudong Li, Shun Lu, Bo Zhang, Jixiang Li

Blending multiple convolutional kernels is proved advantageous in neural architectural design.

Neural Architecture Search

Neural Architecture Search on Acoustic Scene Classification

no code implementations30 Dec 2019 Jixiang Li, Chuming Liang, Bo Zhang, Zhao Wang, Fei Xiang, Xiangxiang Chu

Convolutional neural networks are widely adopted in Acoustic Scene Classification (ASC) tasks, but they generally carry a heavy computational burden.

Acoustic Scene Classification Classification +3

Latent Variables on Spheres for Autoencoders in High Dimensions

no code implementations21 Dec 2019 Deli Zhao, Jiapeng Zhu, Bo Zhang

Variational Auto-Encoder (VAE) has been widely applied as a fundamental generative model in machine learning.

Triple Generative Adversarial Networks

1 code implementation20 Dec 2019 Chongxuan Li, Kun Xu, Jiashuo Liu, Jun Zhu, Bo Zhang

It is formulated as a three-player minimax game consisting of a generator, a classifier and a discriminator, and therefore is referred to as Triple Generative Adversarial Network (Triple-GAN).

Classification Conditional Image Generation +3

Realization of spatial sparseness by deep ReLU nets with massive data

no code implementations16 Dec 2019 Charles K. Chui, Shao-Bo Lin, Bo Zhang, Ding-Xuan Zhou

The great success of deep learning poses urgent challenges for understanding its working mechanism and rationality.

Learning Theory

Automatic quality assessment for 2D fetal sonographic standard plane based on multi-task learning

no code implementations11 Dec 2019 Hong Luo, Han Liu, Kejun Li, Bo Zhang

An essential criterion for FS image quality control is that all the essential anatomical structures in the section should appear full and remarkable with a clear boundary.

Image Quality Assessment Multi-Task Learning +1

Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structure

1 code implementation22 Nov 2019 Zhijie Deng, Yucen Luo, Jun Zhu, Bo Zhang

Bayesian neural networks (BNNs) augment deep networks with uncertainty quantification by Bayesian treatment of the network weights.

Bayesian Inference Neural Architecture Search +1

Hierarchy Response Learning for Neural Conversation Generation

no code implementations IJCNLP 2019 Bo Zhang, Xiao-Ming Zhang

Specifically, a hierarchical response generation (HRG) framework is proposed to capture the conversation intention in a natural and coherent way.

Understanding and Stabilizing GANs' Training Dynamics with Control Theory

1 code implementation29 Sep 2019 Kun Xu, Chongxuan Li, Jun Zhu, Bo Zhang

There are existing efforts that model the training dynamics of GANs in the parameter space but the analysis cannot directly motivate practically effective stabilizing methods.

Ranked #23 on Image Generation on CIFAR-10 (Inception score metric)

Image Generation L2 Regularization

Pruning from Scratch

1 code implementation27 Sep 2019 Yulong Wang, Xiaolu Zhang, Lingxi Xie, Jun Zhou, Hang Su, Bo Zhang, Xiaolin Hu

Network pruning is an important research field aiming at reducing computational costs of neural networks.

Network Pruning

Latent Variables on Spheres for Sampling and Inference

no code implementations25 Sep 2019 Deli Zhao, Jiapeng Zhu, Bo Zhang

Variational inference is a fundamental problem in Variational AutoEncoder (VAE).

Variational Inference

Deep Bayesian Structure Networks

1 code implementation25 Sep 2019 Zhijie Deng, Yucen Luo, Jun Zhu, Bo Zhang

Bayesian neural networks (BNNs) introduce uncertainty estimation to deep networks by performing Bayesian inference on network weights.

Bayesian Inference Neural Architecture Search +1

Training Interpretable Convolutional Neural Networks towards Class-specific Filters

no code implementations25 Sep 2019 Haoyu Liang, Zhihao Ouyang, Hang Su, Yuyuan Zeng, Zihao He, Shu-Tao Xia, Jun Zhu, Bo Zhang

Convolutional neural networks (CNNs) have often been treated as “black-box” and successfully used in a range of tasks.

LIA: Latently Invertible Autoencoder with Adversarial Learning

no code implementations25 Sep 2019 Jiapeng Zhu, Deli Zhao, Bolei Zhou, Bo Zhang

A two-stage stochasticity-free training scheme is designed to train LIA via adversarial learning, in the sense that the decoder of LIA is first trained as a standard GAN with the invertible network and then the partial encoder is learned from an autoencoder by detaching the invertible network from LIA.

Variational Inference

Document Rectification and Illumination Correction using a Patch-based CNN

1 code implementation20 Sep 2019 Xiaoyu Li, Bo Zhang, Jing Liao, Pedro V. Sander

We propose a novel learning method to rectify document images with various distortion types from a single input image.

Optical Character Recognition Rectification

Blind Geometric Distortion Correction on Images Through Deep Learning

no code implementations CVPR 2019 Xiaoyu Li, Bo Zhang, Pedro V. Sander, Jing Liao

We propose the first general framework to automatically correct different types of geometric distortion in a single input image.

Deriving the stellar labels of LAMOST spectra with Stellar LAbel Machine (SLAM)

1 code implementation23 Aug 2019 Bo Zhang, Chao Liu, Li-Cai Deng

To illustrate this capability, we test the performance of SLAM on stars ranging from Teff$\sim$4000 to $\sim$8000 K trained on LAMOST spectra and stellar labels.

Solar and Stellar Astrophysics Astrophysics of Galaxies Instrumentation and Methods for Astrophysics

Multi-Task Deep Learning with Dynamic Programming for Embryo Early Development Stage Classification from Time-Lapse Videos

no code implementations22 Aug 2019 Zihan Liu, Bo Huang, Yuqi Cui, Yifan Xu, Bo Zhang, Lixia Zhu, Yang Wang, Lei Jin, Dongrui Wu

Accurate classification of embryo early development stages can provide embryologists valuable information for assessing the embryo quality, and hence is critical to the success of IVF.

General Classification

MoGA: Searching Beyond MobileNetV3

2 code implementations4 Aug 2019 Xiangxiang Chu, Bo Zhang, Ruijun Xu

Bearing the target hardware in mind, we propose the first Mobile GPU-Aware (MoGA) neural architecture search in order to be precisely tailored for real-world applications.

Image Classification Neural Architecture Search

Curriculum Learning for Deep Generative Models with Clustering

no code implementations27 Jun 2019 Deli Zhao, Jiapeng Zhu, Zhenfang Guo, Bo Zhang

The experiments on cat and human-face data validate that our algorithm is able to learn the optimal generative models (e. g. ProGAN) with respect to specified quality metrics for noisy data.

Curriculum Learning

Disentangled Inference for GANs with Latently Invertible Autoencoder

3 code implementations19 Jun 2019 Jiapeng Zhu, Deli Zhao, Bo Zhang, Bolei Zhou

In this paper, we show that the entanglement of the latent space for the VAE/GAN framework poses the main challenge for encoder learning.

Learning Semantic Vector Representations of Source Code via a Siamese Neural Network

no code implementations26 Apr 2019 David Wehr, Halley Fede, Eleanor Pence, Bo Zhang, Guilherme Ferreira, John Walczyk, Joseph Hughes

The abundance of open-source code, coupled with the success of recent advances in deep learning for natural language processing, has given rise to a promising new application of machine learning to source code.

Deep Hierarchical Reinforcement Learning Based Recommendations via Multi-goals Abstraction

no code implementations22 Mar 2019 Dongyang Zhao, Liang Zhang, Bo Zhang, Lizhou Zheng, Yongjun Bao, Weipeng Yan

To tackle this challenge, we propose a deep hierarchical reinforcement learning based recommendation framework, which consists of two components, i. e., high-level agent and low-level agent.

Hierarchical Reinforcement Learning Recommendation Systems

A Matrix-in-matrix Neural Network for Image Super Resolution

1 code implementation19 Mar 2019 Hailong Ma, Xiangxiang Chu, Shaohua Wan, Bo Zhang

In recent years, deep learning methods have achieved impressive results with higher peak signal-to-noise ratio in single image super-resolution (SISR) tasks by utilizing deeper layers.

Image Super-Resolution

Artificial Intelligence in Intelligent Tutoring Robots: A Systematic Review and Design Guidelines

no code implementations26 Feb 2019 Jinyu Yang, Bo Zhang

We first analyse the environment of the ITR and propose a relationship model for describing interactions of ITR with the students, the social milieu and the curriculum.

Function Space Particle Optimization for Bayesian Neural Networks

1 code implementation ICLR 2019 Ziyu Wang, Tongzheng Ren, Jun Zhu, Bo Zhang

While Bayesian neural networks (BNNs) have drawn increasing attention, their posterior inference remains challenging, due to the high-dimensional and over-parameterized nature.

Variational Inference

Pairwise Teacher-Student Network for Semi-Supervised Hashing

no code implementations2 Feb 2019 Shifeng Zhang, Jianmin Li, Bo Zhang

Hashing method maps similar high-dimensional data to binary hashcodes with smaller hamming distance, and it has received broad attention due to its low storage cost and fast retrieval speed.

To Relieve Your Headache of Training an MRF, Take AdVIL

no code implementations ICLR 2020 Chongxuan Li, Chao Du, Kun Xu, Max Welling, Jun Zhu, Bo Zhang

We propose a black-box algorithm called {\it Adversarial Variational Inference and Learning} (AdVIL) to perform inference and learning on a general Markov random field (MRF).

Variational Inference

Multi-Objective Reinforced Evolution in Mobile Neural Architecture Search

1 code implementation4 Jan 2019 Xiangxiang Chu, Bo Zhang, Ruijun Xu, Hailong Ma

In this paper, we present a new multi-objective oriented algorithm called MoreMNAS (Multi-Objective Reinforced Evolution in Mobile Neural Architecture Search) by leveraging good virtues from both EA and RL.

Image Classification Neural Architecture Search +1

The Entropy of Artificial Intelligence and a Case Study of AlphaZero from Shannon's Perspective

no code implementations14 Dec 2018 Bo Zhang, Bin Chen, Jin-lin Peng

Firstly, as there is a finite number of possibilities in the game, is there a quantifiable intelligence measurement for evaluating intelligent systems, e. g. AlphaZero?

DeepExposure: Learning to Expose Photos with Asynchronously Reinforced Adversarial Learning

no code implementations NeurIPS 2018 Runsheng Yu, Wenyu Liu, Yasen Zhang, Zhi Qu, Deli Zhao, Bo Zhang

Based on these sub-images, a local exposure for each sub-image is automatically learned by virtue of policy network sequentially while the reward of learning is globally designed for striking a balance of overall exposures.

An Unified Intelligence-Communication Model for Multi-Agent System Part-I: Overview

no code implementations25 Nov 2018 Bo Zhang, Bin Chen, Jinyu Yang, Wenjing Yang, Jiankang Zhang

Motivated by Shannon's model and recent rehabilitation of self-supervised artificial intelligence having a "World Model", this paper propose an unified intelligence-communication (UIC) model for describing a single agent and any multi-agent system.

Semi-crowdsourced Clustering with Deep Generative Models

1 code implementation NeurIPS 2018 Yucen Luo, Tian Tian, Jiaxin Shi, Jun Zhu, Bo Zhang

We propose a new approach that includes a deep generative model (DGM) to characterize low-level features of the data, and a statistical relational model for noisy pairwise annotations on its subset.

Variational Inference

Deep Structured Generative Models

no code implementations10 Jul 2018 Kun Xu, Haoyu Liang, Jun Zhu, Hang Su, Bo Zhang

Deep generative models have shown promising results in generating realistic images, but it is still non-trivial to generate images with complicated structures.

Supervised Treebank Conversion: Data and Approaches

no code implementations ACL 2018 Xinzhou Jiang, Zhenghua Li, Bo Zhang, Min Zhang, Sheng Li, Luo Si

Treebank conversion is a straightforward and effective way to exploit various heterogeneous treebanks for boosting parsing performance.

Dependency Parsing Multi-Task Learning

Interlinked Convolutional Neural Networks for Face Parsing

no code implementations7 Jun 2018 Yisu Zhou, Xiaolin Hu, Bo Zhang

It amounts to labeling each pixel with appropriate facial parts such as eyes and nose.

Face Parsing

Interpret Neural Networks by Identifying Critical Data Routing Paths

no code implementations CVPR 2018 Yulong Wang, Hang Su, Bo Zhang, Xiaolin Hu

Interpretability of a deep neural network aims to explain the rationale behind its decisions and enable the users to understand the intelligent agents, which has become an important issue due to its importance in practical applications.

Semantic Cluster Unary Loss for Efficient Deep Hashing

1 code implementation15 May 2018 Shifeng Zhang, Jianmin Li, Bo Zhang

The resultant hashcodes form several compact clusters, which means hashcodes in the same cluster have similar semantic information.

Information Retrieval

Adversarial adaptive 1-D convolutional neural networks for bearing fault diagnosis under varying working condition

no code implementations1 May 2018 Bo Zhang, Wei Li, Jie Hao, Xiao-Li Li, Meng Zhang

The layers between the source and target feature extractor are partially untied during the training stage to take both training efficiency and domain adaptation into consideration.

Domain Adaptation

Graphical Generative Adversarial Networks

1 code implementation NeurIPS 2018 Chongxuan Li, Max Welling, Jun Zhu, Bo Zhang

We propose Graphical Generative Adversarial Networks (Graphical-GAN) to model structured data.

Message Passing Stein Variational Gradient Descent

no code implementations ICML 2018 Jingwei Zhuo, Chang Liu, Jiaxin Shi, Jun Zhu, Ning Chen, Bo Zhang

Stein variational gradient descent (SVGD) is a recently proposed particle-based Bayesian inference method, which has attracted a lot of interest due to its remarkable approximation ability and particle efficiency compared to traditional variational inference and Markov Chain Monte Carlo methods.

Bayesian Inference Variational Inference

Smooth Neighbors on Teacher Graphs for Semi-supervised Learning

1 code implementation CVPR 2018 Yucen Luo, Jun Zhu, Mengxi Li, Yong Ren, Bo Zhang

In SNTG, a graph is constructed based on the predictions of the teacher model, i. e., the implicit self-ensemble of models.

Fast Deep Matting for Portrait Animation on Mobile Phone

1 code implementation26 Jul 2017 Bingke Zhu, Yingying Chen, Jinqiao Wang, Si Liu, Bo Zhang, Ming Tang

Finally, an automatic portrait animation system based on fast deep matting is built on mobile devices, which does not need any interaction and can realize real-time matting with 15 fps.

Image Matting Video Editing

PBODL : Parallel Bayesian Online Deep Learning for Click-Through Rate Prediction in Tencent Advertising System

no code implementations4 Jul 2017 Xun Liu, Wei Xue, Lei Xiao, Bo Zhang

Then we extend the model family to a variety of bayesian online models with increasing feature embedding capabilities, such as Sparse-MLP, FM-MLP and FFM-MLP.

Click-Through Rate Prediction

SAM: Semantic Attribute Modulation for Language Modeling and Style Variation

no code implementations1 Jul 2017 Wenbo Hu, Lifeng Hua, Lei LI, Hang Su, Tian Wang, Ning Chen, Bo Zhang

This paper presents a Semantic Attribute Modulation (SAM) for language modeling and style variation.

Language Modelling

Discriminatively Boosted Image Clustering with Fully Convolutional Auto-Encoders

2 code implementations23 Mar 2017 Fengfu Li, Hong Qiao, Bo Zhang, Xuanyang Xi

Traditional image clustering methods take a two-step approach, feature learning and clustering, sequentially.

Image Clustering

Improving Interpretability of Deep Neural Networks with Semantic Information

no code implementations CVPR 2017 Yinpeng Dong, Hang Su, Jun Zhu, Bo Zhang

Interpretability of deep neural networks (DNNs) is essential since it enables users to understand the overall strengths and weaknesses of the models, conveys an understanding of how the models will behave in the future, and how to diagnose and correct potential problems.

Action Recognition Video Captioning

Triple Generative Adversarial Nets

1 code implementation NeurIPS 2017 Chongxuan Li, Kun Xu, Jun Zhu, Bo Zhang

Generative Adversarial Nets (GANs) have shown promise in image generation and semi-supervised learning (SSL).

Image Generation

Max-Margin Deep Generative Models for (Semi-)Supervised Learning

1 code implementation22 Nov 2016 Chongxuan Li, Jun Zhu, Bo Zhang

Deep generative models (DGMs) are effective on learning multilayered representations of complex data and performing inference of input data by exploring the generative ability.

A Unified Framework for Community Detection and Network Representation Learning

no code implementations21 Nov 2016 Cunchao Tu, Xiangkai Zeng, Hao Wang, Zhengyan Zhang, Zhiyuan Liu, Maosong Sun, Bo Zhang, Leyu Lin

Network representation learning (NRL) aims to learn low-dimensional vectors for vertices in a network.

Social and Information Networks Physics and Society

Effective Deterministic Initialization for $k$-Means-Like Methods via Local Density Peaks Searching

no code implementations21 Nov 2016 Fengfu Li, Hong Qiao, Bo Zhang

Based on these two components, we search for the local density peaks which are characterized with high local densities and high LDIs to deal with 1) and 2).

Scalable Discrete Supervised Hash Learning with Asymmetric Matrix Factorization

no code implementations28 Sep 2016 Shifeng Zhang, Jianmin Li, Jinma Guo, Bo Zhang

Hashing method maps similar data to binary hashcodes with smaller hamming distance, and it has received a broad attention due to its low storage cost and fast retrieval speed.

Bootstrapping Face Detection with Hard Negative Examples

no code implementations7 Aug 2016 Shaohua Wan, Zhijun Chen, Tao Zhang, Bo Zhang, Kong-kat Wong

Recently significant performance improvement in face detection was made possible by deeply trained convolutional networks.

Face Detection

Ternary Weight Networks

3 code implementations16 May 2016 Fengfu Li, Bo Zhang, Bin Liu

We introduce ternary weight networks (TWNs) - neural networks with weights constrained to +1, 0 and -1.

Model Compression

A New Manifold Distance Measure for Visual Object Categorization

no code implementations12 May 2016 Fengfu Li, Xiayuan Huang, Hong Qiao, Bo Zhang

The proposed distance is more robust to rotations and translations of images than the traditional manifold distance and the CW-SSIM index based distance.

Object Recognition SSIM

Learning to Generate with Memory

1 code implementation24 Feb 2016 Chongxuan Li, Jun Zhu, Bo Zhang

Memory units have been widely used to enrich the capabilities of deep networks on capturing long-term dependencies in reasoning and prediction tasks, but little investigation exists on deep generative models (DGMs) which are good at inferring high-level invariant representations from unlabeled data.

Density Estimation Image Generation +2

Fast Parallel SVM using Data Augmentation

no code implementations24 Dec 2015 Hugh Perkins, Minjie Xu, Jun Zhu, Bo Zhang

As one of the most popular classifiers, linear SVMs still have challenges in dealing with very large-scale problems, even though linear or sub-linear algorithms have been developed recently on single machines.

Bayesian Inference Data Augmentation

Jointly Modeling Topics and Intents with Global Order Structure

no code implementations7 Dec 2015 Bei Chen, Jun Zhu, Nan Yang, Tian Tian, Ming Zhou, Bo Zhang

Modeling document structure is of great importance for discourse analysis and related applications.

Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation

no code implementations7 Dec 2015 Bei Chen, Ning Chen, Jun Zhu, Jiaming Song, Bo Zhang

We present a discriminative nonparametric latent feature relational model (LFRM) for link prediction to automatically infer the dimensionality of latent features.

Bayesian Inference Data Augmentation +1

Convolutional Neural Networks with Intra-Layer Recurrent Connections for Scene Labeling

no code implementations NeurIPS 2015 Ming Liang, Xiaolin Hu, Bo Zhang

We adopt a deep recurrent convolutional neural network (RCNN) for this task, which is originally proposed for object recognition.

Object Recognition Scene Labeling

RIDE: Reversal Invariant Descriptor Enhancement

no code implementations ICCV 2015 Lingxi Xie, Jingdong Wang, Weiyao Lin, Bo Zhang, Qi Tian

In many fine-grained object recognition datasets, image orientation (left/right) might vary from sample to sample.

Object Recognition

Learning Deep Generative Models with Doubly Stochastic MCMC

no code implementations15 Jun 2015 Chao Du, Jun Zhu, Bo Zhang

We present doubly stochastic gradient MCMC, a simple and generic method for (approximate) Bayesian inference of deep generative models (DGMs) in a collapsed continuous parameter space.

Bayesian Inference Density Estimation +1

Fast Sampling for Bayesian Max-Margin Models

no code implementations27 Apr 2015 Wenbo Hu, Jun Zhu, Bo Zhang

Bayesian max-margin models have shown superiority in various practical applications, such as text categorization, collaborative prediction, social network link prediction and crowdsourcing, and they conjoin the flexibility of Bayesian modeling and predictive strengths of max-margin learning.

Link Prediction Text Categorization

Max-margin Deep Generative Models

2 code implementations NeurIPS 2015 Chongxuan Li, Jun Zhu, Tianlin Shi, Bo Zhang

Deep generative models (DGMs) are effective on learning multilayered representations of complex data and performing inference of input data by exploring the generative ability.

Distributed Bayesian Posterior Sampling via Moment Sharing

no code implementations NeurIPS 2014 Minjie Xu, Balaji Lakshminarayanan, Yee Whye Teh, Jun Zhu, Bo Zhang

We propose a distributed Markov chain Monte Carlo (MCMC) inference algorithm for large scale Bayesian posterior simulation.

Big Learning with Bayesian Methods

no code implementations24 Nov 2014 Jun Zhu, Jianfei Chen, Wen-Bo Hu, Bo Zhang

Explosive growth in data and availability of cheap computing resources have sparked increasing interest in Big learning, an emerging subfield that studies scalable machine learning algorithms, systems, and applications with Big Data.

Bayesian Inference Distributed Computing

Orientational Pyramid Matching for Recognizing Indoor Scenes

no code implementations CVPR 2014 Lingxi Xie, Jingdong Wang, Baining Guo, Bo Zhang, Qi Tian

The novelty lies in that OPM uses the 3D orientations to form the pyramid and produce the pooling regions, which is unlike SPM that uses the spatial positions to form the pyramid.

General Classification Scene Classification +1

Dropout Training for Support Vector Machines

no code implementations16 Apr 2014 Ning Chen, Jun Zhu, Jianfei Chen, Bo Zhang

To deal with the intractable expectation of the non-smooth hinge loss under corrupting distributions, we develop an iteratively re-weighted least square (IRLS) algorithm by exploring data augmentation techniques.

Data Augmentation

Gibbs Max-margin Topic Models with Data Augmentation

no code implementations10 Oct 2013 Jun Zhu, Ning Chen, Hugh Perkins, Bo Zhang

Gibbs max-margin supervised topic models minimize an expected margin loss, which is an upper bound of the existing margin loss derived from an expected prediction rule.

Classification Data Augmentation +4

Improved Bayesian Logistic Supervised Topic Models with Data Augmentation

no code implementations ACL 2013 Jun Zhu, Xun Zheng, Bo Zhang

Supervised topic models with a logistic likelihood have two issues that potentially limit their practical use: 1) response variables are usually over-weighted by document word counts; and 2) existing variational inference methods make strict mean-field assumptions.

Bayesian Inference Data Augmentation +2

Super-Bit Locality-Sensitive Hashing

no code implementations NeurIPS 2012 Jianqiu Ji, Jianmin Li, Shuicheng Yan, Bo Zhang, Qi Tian

Sign-random-projection locality-sensitive hashing (SRP-LSH) is a probabilistic dimension reduction method which provides an unbiased estimate of angular similarity, yet suffers from the large variance of its estimation.

Dimensionality Reduction

Partially Observed Maximum Entropy Discrimination Markov Networks

no code implementations NeurIPS 2008 Jun Zhu, Eric P. Xing, Bo Zhang

Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unattainable fully annotated training data.

Structured Prediction

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