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

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

The learning and evaluation of energy-based latent variable models (EBLV...
10/16/2020 ∙ by Fan Bao, et al. ∙ 0 ∙ share

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

Score matching (SM) provides a compelling approach to learn energy-based...
10/15/2020 ∙ by Fan Bao, et al. ∙ 0 ∙ share

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Old Photo Restoration via Deep Latent Space Translation

We propose to restore old photos that suffer from severe degradation thr...
09/14/2020 ∙ by Ziyu Wan, et al. ∙ 55 ∙ share

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AutoKWS: Keyword Spotting with Differentiable Architecture Search

Smart audio devices are gated by an always-on lightweight keyword spotti...
09/08/2020 ∙ by Bo Zhang, et al. ∙ 0 ∙ share

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A Simple and General Graph Neural Network with Stochastic Message Passing

Graph neural networks (GNNs) are emerging machine learning models on gra...
09/05/2020 ∙ by Ziwei Zhang, et al. ∙ 0 ∙ share

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DARTS-: Robustly Stepping out of Performance Collapse Without Indicators

Despite the fast development of differentiable architecture search (DART...
09/02/2020 ∙ by Xiangxiang Chu, et al. ∙ 0 ∙ share

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Deep Sketch-guided Cartoon Video Synthesis

We propose a novel framework to produce cartoon videos by fetching the c...
08/10/2020 ∙ by Xiaoyu Li, et al. ∙ 0 ∙ share

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Training Interpretable Convolutional Neural Networks by Differentiating Class-specific Filters

Convolutional neural networks (CNNs) have been successfully used in a ra...
07/16/2020 ∙ by Haoyu Liang, et al. ∙ 0 ∙ share

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Bridging preference-based instrumental variable studies and cluster-randomized encouragement experiments: study design, noncompliance, and average cluster effect ratio

Instrumental variable methods are widely used in medical and social scie...
07/14/2020 ∙ by Bo Zhang, et al. ∙ 0 ∙ share

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Noisy Differentiable Architecture Search

Simplicity is the ultimate sophistication. Differentiable Architecture S...
05/07/2020 ∙ by Xiangxiang Chu, et al. ∙ 0 ∙ 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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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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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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Perceptual Image Super-Resolution with Progressive Adversarial Network

Single Image Super-Resolution (SISR) aims to improve resolution of small...
03/08/2020 ∙ by Lone Wong, et al. ∙ 0 ∙ share

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Performance Analysis and Optimization in Privacy-Preserving Federated Learning

As a means of decentralized machine learning, federated learning (FL) ha...
02/29/2020 ∙ by Kang Wei, et al. ∙ 0 ∙ share

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Selecting and ranking individualized treatment rules with unmeasured confounding

It is common to compare individualized treatment rules based on the valu...
02/24/2020 ∙ by Bo Zhang, et al. ∙ 0 ∙ share

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

Session-based target behavior prediction aims to predict the next item t...
02/19/2020 ∙ by Wen Wang, et al. ∙ 0 ∙ 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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Estimating Optimal Treatment Rules with an Instrumental Variable: A Partial Identification Learning Approach

Individualized treatment rules (ITRs) are considered a promising recipe ...
02/07/2020 ∙ by Hongming Pu, et al. ∙ 0 ∙ share

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Estimating Optimal Treatment Rules with an Instrumental Variable: A Semi-Supervised Learning Approach

Individualized treatment rules (ITRs) are regarded as a promising recipe...
02/07/2020 ∙ by Hongming Pu, et al. ∙ 0 ∙ share

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Imaging of buried obstacles in a two-layered medium with phaseless far-field data

The inverse problem we consider is to reconstruct the location and shape...
01/28/2020 ∙ by Long Li, et al. ∙ 0 ∙ share

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Privacy for All: Demystify Vulnerability Disparity of Differential Privacy against Membership Inference Attack

Machine learning algorithms, when applied to sensitive data, pose a pote...
01/24/2020 ∙ by Bo Zhang, et al. ∙ 0 ∙ share

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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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Neural Architecture Search on Acoustic Scene Classification

Convolutional neural networks are widely adopted in Acoustic Scene Class...
12/30/2019 ∙ by Jixiang Li, et al. ∙ 0 ∙ 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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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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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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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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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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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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Instrumental Variables: to Strengthen or not to Strengthen?

Instrumental variables (IV) are extensively used to estimate treatment e...
11/20/2019 ∙ by Siyu Heng, et al. ∙ 0 ∙ share

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In Vitro Fertilization (IVF) Cumulative Pregnancy Rate Prediction from Basic Patient Characteristics

Tens of millions of women suffer from infertility worldwide each year. I...
11/10/2019 ∙ by Bo Zhang, et al. ∙ 0 ∙ share

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Regularized Adversarial Sampling and Deep Time-aware Attention for Click-Through Rate Prediction

Improving the performance of click-through rate (CTR) prediction remains...
11/03/2019 ∙ by Yikai Wang, et al. ∙ 0 ∙ share

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A Semiparametric Approach to Model-based Sensitivity Analysis in Observational Studies

When drawing causal inference from observational data, there is always c...
10/30/2019 ∙ by Bo Zhang, et al. ∙ 0 ∙ share

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Understanding and Stabilizing GANs' Training Dynamics with Control Theory

Generative adversarial networks (GANs) have made significant progress on...
09/29/2019 ∙ by Kun Xu, et al. ∙ 0 ∙ 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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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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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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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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Multi-Task Deep Learning with Dynamic Programming for Embryo Early Development Stage Classification from Time-Lapse Videos

Time-lapse is a technology used to record the development of embryos dur...
08/22/2019 ∙ by Zihan Liu, et al. ∙ 0 ∙ share

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ScarletNAS: Bridging the Gap Between Scalability and Fairness in Neural Architecture Search

One-shot neural architecture search features fast training of a supernet...
08/16/2019 ∙ by Xiangxiang Chu, et al. ∙ 0 ∙ share

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An approximate factorization method for inverse acoustic scattering with phaseless near-field data

This paper is concerned with the inverse acoustic scattering problem wit...
08/10/2019 ∙ by Bo Zhang, et al. ∙ 0 ∙ share

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MoGA: Searching Beyond MobileNetV3

The evolution of MobileNets has laid a solid foundation for neural netwo...
08/04/2019 ∙ by Xiangxiang Chu, et al. ∙ 0 ∙ share

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Convergence of the perfectly matched layer method for transient acoustic-elastic interaction above an unbounded rough surface

This paper is concerned with the time-dependent acoustic-elastic interac...
07/23/2019 ∙ by Changkun Wei, et al. ∙ 0 ∙ share

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Convergence analysis of the PML method for time-domain electromagnetic scattering problems

In this paper, a perfectly matched layer (PML) method is proposed to sol...
07/21/2019 ∙ by Changkun Wei, et al. ∙ 0 ∙ share

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FairNAS: Rethinking Evaluation Fairness of Weight Sharing Neural Architecture Search

The ability to rank models by its real strength is the key to Neural Arc...
07/03/2019 ∙ by Xiangxiang Chu, et al. ∙ 0 ∙ share

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Curriculum Learning for Deep Generative Models with Clustering

Training generative models like generative adversarial networks (GANs) a...
06/27/2019 ∙ by Deli Zhao, et al. ∙ 0 ∙ 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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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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Multi-objects Generation with Amortized Structural Regularization

Deep generative models (DGMs) have shown promise in image generation. Ho...
06/10/2019 ∙ by Kun Xu, et al. ∙ 0 ∙ share

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Bo Zhang

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