Bo Zhang

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ibm ∙ Xiaomi ∙ Tsinghua University ∙ North China University of Technolege ∙ Stevens Institute of Technology ∙ NetEase, Inc

Professor of Department of Computer Science and Technology at Tsinghua University

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

The expressiveness of search space is a key concern in neural architectu...
01/16/2020 ∙ by Xiangxiang Chu, et al. ∙ 39 ∙ share

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Triple Generative Adversarial Networks

Generative adversarial networks (GANs) have shown promise in image gener...
12/20/2019 ∙ by Chongxuan Li, et al. ∙ 28 ∙ share

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Function Space Particle Optimization for Bayesian Neural Networks

While Bayesian neural networks (BNNs) have drawn increasing attention, t...
02/26/2019 ∙ by Ziyu Wang, et al. ∙ 24 ∙ share

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Pruning from Scratch

Network pruning is an important research field aiming at reducing comput...
09/27/2019 ∙ by Yulong Wang, et al. ∙ 24 ∙ share

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Bringing Old Photos Back to Life

We propose to restore old photos that suffer from severe degradation thr...
04/20/2020 ∙ by Ziyu Wan, et al. ∙ 23 ∙ share

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Fast, Accurate and Lightweight Super-Resolution with Neural Architecture Search

Deep convolution neural networks demonstrate impressive results in super...
01/22/2019 ∙ by Xiangxiang Chu, et al. ∙ 22 ∙ share

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Adversarial Variational Inference and Learning in Markov Random Fields

Markov random fields (MRFs) find applications in a variety of machine le...
01/24/2019 ∙ by Chongxuan Li, et al. ∙ 18 ∙ share

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LIA: Latently Invertible Autoencoder with Adversarial Learning

Deep generative models play an increasingly important role in machine le...
06/19/2019 ∙ by Jiapeng Zhu, et al. ∙ 17 ∙ share

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Realization of spatial sparseness by deep ReLU nets with massive data

The great success of deep learning poses urgent challenges for understan...
12/16/2019 ∙ by Charles K. Chui, et al. ∙ 16 ∙ share

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DBSN: Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structures

Bayesian neural networks (BNNs) introduce uncertainty estimation to deep...
11/22/2019 ∙ by Zhijie Deng, et al. ∙ 13 ∙ share

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Fair DARTS: Eliminating Unfair Advantages in Differentiable Architecture Search

Differential Architecture Search (DARTS) is now a widely disseminated we...
11/27/2019 ∙ by Xiangxiang Chu, et al. ∙ 11 ∙ share

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A Data-Center FPGA Acceleration Platform for Convolutional Neural Networks

Intensive computation is entering data centers with multiple workloads o...
09/17/2019 ∙ by Xiaoyu Yu, et al. ∙ 10 ∙ share

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A Wasserstein Minimum Velocity Approach to Learning Unnormalized Models

Score matching provides an effective approach to learning flexible unnor...
02/18/2020 ∙ by Ziyu Wang, et al. ∙ 9 ∙ share

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Deep Structured Generative Models

Deep generative models have shown promising results in generating realis...
07/10/2018 ∙ by Kun Xu, et al. ∙ 8 ∙ share

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Document Rectification and Illumination Correction using a Patch-based CNN

We propose a novel learning method to rectify document images with vario...
09/20/2019 ∙ by Xiaoyu Li, et al. ∙ 6 ∙ share

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

The quality control of fetal sonographic (FS) images is essential for th...
12/11/2019 ∙ by Hong Luo, et al. ∙ 6 ∙ share

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Blind Geometric Distortion Correction on Images Through Deep Learning

We propose the first general framework to automatically correct differen...
09/08/2019 ∙ by Xiaoyu Li, et al. ∙ 5 ∙ share

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Deep Exemplar-based Video Colorization

This paper presents the first end-to-end network for exemplar-based vide...
06/24/2019 ∙ by Bo Zhang, et al. ∙ 4 ∙ share

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Latent Variables on Spheres for Sampling and Spherical Inference

Variational inference is a fundamental problem in Variational Auto-Encod...
12/21/2019 ∙ by Deli Zhao, et al. ∙ 4 ∙ share

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

In deep learning tasks, the learning rate determines the update step siz...
04/07/2020 ∙ by Yingqiu Zhu, et al. ∙ 3 ∙ share

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Interlinked Convolutional Neural Networks for Face Parsing

Face parsing is a basic task in face image analysis. It amounts to label...
06/07/2018 ∙ by Yisu Zhou, et al. ∙ 2 ∙ share

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Cross-domain Correspondence Learning for Exemplar-based Image Translation

We present a general framework for exemplar-based image translation, whi...
04/12/2020 ∙ by Pan Zhang, et al. ∙ 1 ∙ share

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Analyzing and Improving Stein Variational Gradient Descent for High-dimensional Marginal Inference

Stein variational gradient descent (SVGD) is a nonparametric inference m...
11/13/2017 ∙ by Jingwei Zhuo, et al. ∙ 0 ∙ share

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Fast Deep Matting for Portrait Animation on Mobile Phone

Image matting plays an important role in image and video editing. Howeve...
07/26/2017 ∙ by Bingke Zhu, et al. ∙ 0 ∙ share

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Discriminatively Boosted Image Clustering with Fully Convolutional Auto-Encoders

Traditional image clustering methods take a two-step approach, feature l...
03/23/2017 ∙ by Fengfu Li, et al. ∙ 0 ∙ share

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Improving Interpretability of Deep Neural Networks with Semantic Information

Interpretability of deep neural networks (DNNs) is essential since it en...
03/12/2017 ∙ by Yinpeng Dong, et al. ∙ 0 ∙ share

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Triple Generative Adversarial Nets

Generative Adversarial Nets (GANs) have shown promise in image generatio...
03/07/2017 ∙ by Chongxuan Li, et al. ∙ 0 ∙ share

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

Deep generative models (DGMs) are effective on learning multilayered rep...
11/22/2016 ∙ by Chongxuan Li, et al. ∙ 0 ∙ share

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

The k-means clustering algorithm is popular but has the following main d...
11/21/2016 ∙ by Fengfu Li, et al. ∙ 0 ∙ share

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Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation

We present a discriminative nonparametric latent feature relational mode...
12/07/2015 ∙ by Bei Chen, et al. ∙ 0 ∙ share

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Scalable Discrete Supervised Hash Learning with Asymmetric Matrix Factorization

Hashing method maps similar data to binary hashcodes with smaller hammin...
09/28/2016 ∙ by Shifeng Zhang, et al. ∙ 0 ∙ share

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Bootstrapping Face Detection with Hard Negative Examples

Recently significant performance improvement in face detection was made ...
08/07/2016 ∙ by Shaohua Wan, et al. ∙ 0 ∙ share

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Fast Sampling for Bayesian Max-Margin Models

Bayesian max-margin models have shown superiority in various practical a...
04/27/2015 ∙ by Wenbo Hu, et al. ∙ 0 ∙ share

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Planning and Acting under Uncertainty: A New Model for Spoken Dialogue Systems

Uncertainty plays a central role in spoken dialogue systems. Some stocha...
01/10/2013 ∙ by Bo Zhang, et al. ∙ 0 ∙ share

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Big Learning with Bayesian Methods

Explosive growth in data and availability of cheap computing resources h...
11/24/2014 ∙ by Jun Zhu, et al. ∙ 0 ∙ share

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A Novel Biologically Mechanism-Based Visual Cognition Model--Automatic Extraction of Semantics, Formation of Integrated Concepts and Re-selection Features for Ambiguity

Integration between biology and information science benefits both fields...
03/25/2016 ∙ by Peijie Yin, et al. ∙ 0 ∙ share

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Learning to Generate with Memory

Memory units have been widely used to enrich the capabilities of deep ne...
02/24/2016 ∙ by Chongxuan Li, et al. ∙ 0 ∙ share

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Gibbs Max-margin Topic Models with Data Augmentation

Max-margin learning is a powerful approach to building classifiers and s...
10/10/2013 ∙ by Jun Zhu, et al. ∙ 0 ∙ share

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Discriminative Relational Topic Models

Many scientific and engineering fields involve analyzing network data. F...
10/09/2013 ∙ by Ning Chen, et al. ∙ 0 ∙ share

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Improved Bayesian Logistic Supervised Topic Models with Data Augmentation

Supervised topic models with a logistic likelihood have two issues that ...
10/09/2013 ∙ by Jun Zhu, et al. ∙ 0 ∙ share

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Max-margin Deep Generative Models

Deep generative models (DGMs) are effective on learning multilayered rep...
04/26/2015 ∙ by Chongxuan Li, et al. ∙ 0 ∙ share

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A new embedding quality assessment method for manifold learning

Manifold learning is a hot research topic in the field of computer scien...
08/08/2011 ∙ by Peng Zhang, et al. ∙ 0 ∙ share

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Intrinsic dimension estimation of data by principal component analysis

Estimating intrinsic dimensionality of data is a classic problem in patt...
02/10/2010 ∙ by Mingyu Fan, et al. ∙ 0 ∙ share

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An Explicit Nonlinear Mapping for Manifold Learning

Manifold learning is a hot research topic in the field of computer scien...
01/15/2010 ∙ by Hong Qiao, et al. ∙ 0 ∙ share

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Isometric Multi-Manifolds Learning

Isometric feature mapping (Isomap) is a promising manifold learning meth...
12/03/2009 ∙ by Mingyu Fan, et al. ∙ 0 ∙ share

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SAM: Semantic Attribute Modulation for Language Modeling and Style Variation

This paper presents a Semantic Attribute Modulation (SAM) for language m...
07/01/2017 ∙ by Wenbo Hu, et al. ∙ 0 ∙ share

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Jointly Modeling Topics and Intents with Global Order Structure

Modeling document structure is of great importance for discourse analysi...
12/07/2015 ∙ by Bei Chen, et al. ∙ 0 ∙ share

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Directional Modulation Design Based on Crossed-Dipole Arrays for Two Signals With Orthogonal Polarisations

Directional modulation (DM) is a physical layer security technique based...
01/01/2018 ∙ by Bo Zhang, et al. ∙ 0 ∙ share

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Smooth Neighbors on Teacher Graphs for Semi-supervised Learning

The paper proposes an inductive semi-supervised learning method, called ...
11/01/2017 ∙ by Yucen Luo, et al. ∙ 0 ∙ share

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Bearing fault diagnosis under varying working condition based on domain adaptation

Traditional intelligent fault diagnosis of rolling bearings work well on...
07/31/2017 ∙ by Bo Zhang, et al. ∙ 0 ∙ share

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Bo Zhang

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