Jun Zhu

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Nanjing University of Aeronautics and Astronautics ∙ Qualcomm ∙ University of Wisconsin-Madison ∙ ibm ∙ Carnegie Mellon University

Associate Professor, Computer Science Department at Tsinghua University. Adjunct Faculty, Machine Learning Department at Carnegie Mellon University.

Query2Label: A Simple Transformer Way to Multi-Label Classification

This paper presents a simple and effective approach to solving the multi...
07/22/2021 ∙ by Shilong Liu, et al. ∙ 10 ∙ share

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On the Convergence of Prior-Guided Zeroth-Order Optimization Algorithms

Zeroth-order (ZO) optimization is widely used to handle challenging task...
07/21/2021 ∙ by Shuyu Cheng, et al. ∙ 0 ∙ share

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Boosting Transferability of Targeted Adversarial Examples via Hierarchical Generative Networks

Transfer-based adversarial attacks can effectively evaluate model robust...
07/05/2021 ∙ by Xiao Yang, et al. ∙ 0 ∙ share

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Understanding Adversarial Attacks on Observations in Deep Reinforcement Learning

Recent works demonstrate that deep reinforcement learning (DRL) models a...
06/30/2021 ∙ by You Qiaoben, et al. ∙ 0 ∙ share

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Regularized OFU: an Efficient UCB Estimator forNon-linear Contextual Bandit

Balancing exploration and exploitation (EE) is a fundamental problem in ...
06/29/2021 ∙ by Yichi Zhou, et al. ∙ 0 ∙ share

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Improving Transferability of Adversarial Patches on Face Recognition with Generative Models

Face recognition is greatly improved by deep convolutional neural networ...
06/29/2021 ∙ by Zihao Xiao, et al. ∙ 5 ∙ share

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Accumulative Poisoning Attacks on Real-time Data

Collecting training data from untrusted sources exposes machine learning...
06/18/2021 ∙ by Tianyu Pang, et al. ∙ 0 ∙ share

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Scalable Quasi-Bayesian Inference for Instrumental Variable Regression

Recent years have witnessed an upsurge of interest in employing flexible...
06/16/2021 ∙ by Ziyu Wang, et al. ∙ 5 ∙ share

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Understanding Softmax Confidence and Uncertainty

It is often remarked that neural networks fail to increase their uncerta...
06/09/2021 ∙ by Tim Pearce, et al. ∙ 0 ∙ share

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Nonlinear Hawkes Processes in Time-Varying System

Hawkes processes are a class of point processes that have the ability to...
06/09/2021 ∙ by Feng Zhou, et al. ∙ 0 ∙ share

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Stability and Generalization of Bilevel Programming in Hyperparameter Optimization

Recently, the (gradient-based) bilevel programming framework is widely u...
06/08/2021 ∙ by Fan Bao, et al. ∙ 0 ∙ share

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Exploring Memorization in Adversarial Training

It is well known that deep learning models have a propensity for fitting...
06/03/2021 ∙ by Yinpeng Dong, et al. ∙ 0 ∙ share

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KO-PDE: Kernel Optimized Discovery of Partial Differential Equations with Varying Coefficients

Partial differential equations (PDEs) fitting scientific data can repres...
06/02/2021 ∙ by Yingtao Luo, et al. ∙ 18 ∙ share

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Adversarial Training with Rectified Rejection

Adversarial training (AT) is one of the most effective strategies for pr...
05/31/2021 ∙ by Tianyu Pang, et al. ∙ 0 ∙ share

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Unsupervised Part Segmentation through Disentangling Appearance and Shape

We study the problem of unsupervised discovery and segmentation of objec...
05/26/2021 ∙ by Shilong Liu, et al. ∙ 11 ∙ share

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Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization

(Partial) ranking loss is a commonly used evaluation measure for multi-l...
05/10/2021 ∙ by Guoqiang Wu, et al. ∙ 0 ∙ share

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Automated Decision-based Adversarial Attacks

Deep learning models are vulnerable to adversarial examples, which can f...
05/09/2021 ∙ by Qi-An Fu, et al. ∙ 0 ∙ share

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MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering

We present Mixture of Contrastive Experts (MiCE), a unified probabilisti...
05/05/2021 ∙ by Tsung Wei Tsai, et al. ∙ 0 ∙ share

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Few-shot Continual Learning: a Brain-inspired Approach

It is an important yet challenging setting to continually learn new task...
04/19/2021 ∙ by Liyuan Wang, et al. ∙ 0 ∙ share

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Counter-Strike Deathmatch with Large-Scale Behavioural Cloning

This paper describes an AI agent that plays the popular first-person-sho...
04/09/2021 ∙ by Tim Pearce, et al. ∙ 16 ∙ share

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Accurate and Reliable Forecasting using Stochastic Differential Equations

It is critical yet challenging for deep learning models to properly char...
03/28/2021 ∙ by Peng Cui, et al. ∙ 0 ∙ share

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LiBRe: A Practical Bayesian Approach to Adversarial Detection

Despite their appealing flexibility, deep neural networks (DNNs) are vul...
03/27/2021 ∙ by Zhijie Deng, et al. ∙ 0 ∙ share

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Black-box Detection of Backdoor Attacks with Limited Information and Data

Although deep neural networks (DNNs) have made rapid progress in recent ...
03/24/2021 ∙ by Yinpeng Dong, et al. ∙ 0 ∙ share

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Implicit Normalizing Flows

Normalizing flows define a probability distribution by an explicit inver...
03/17/2021 ∙ by Cheng Lu, et al. ∙ 23 ∙ share

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DNN2LR: Automatic Feature Crossing for Credit Scoring

Credit scoring is a major application of machine learning for financial ...
02/24/2021 ∙ by Qiang Liu, et al. ∙ 4 ∙ share

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Rethinking Natural Adversarial Examples for Classification Models

Recently, it was found that many real-world examples without intentional...
02/23/2021 ∙ by Xiao Li, et al. ∙ 11 ∙ share

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Deep Learning-Based Autoencoder for Data-Driven Modeling of an RF Photoinjector

We adopt a data-driven approach to model the longitudinal phase-space di...
01/25/2021 ∙ by Jun Zhu, et al. ∙ 0 ∙ share

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Cognitive Visual Inspection Service for LCD Manufacturing Industry

With the rapid growth of display devices, quality inspection via machine...
01/11/2021 ∙ by Yuanyuan Ding, et al. ∙ 3 ∙ share

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Relaxed Conditional Image Transfer for Semi-supervised Domain Adaptation

Semi-supervised domain adaptation (SSDA), which aims to learn models in ...
01/05/2021 ∙ by Qijun Luo, et al. ∙ 10 ∙ share

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ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-supervised Continual Learning

Continual learning usually assumes the incoming data are fully labeled, ...
01/02/2021 ∙ by Liyuan Wang, et al. ∙ 6 ∙ share

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Series Saliency: Temporal Interpretation for Multivariate Time Series Forecasting

Time series forecasting is an important yet challenging task. Though dee...
12/16/2020 ∙ by Qingyi Pan, et al. ∙ 0 ∙ share

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Fork or Fail: Cycle-Consistent Training with Many-to-One Mappings

Cycle-consistent training is widely used for jointly learning a forward ...
12/14/2020 ∙ by Qipeng Guo, et al. ∙ 10 ∙ share

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Multi-label classification: do Hamming loss and subset accuracy really conflict with each other?

Various evaluation measures have been developed for multi-label classifi...
11/16/2020 ∙ by Guoqiang Wu, et al. ∙ 0 ∙ share

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Further Analysis of Outlier Detection with Deep Generative Models

The recent, counter-intuitive discovery that deep generative models (DGM...
10/25/2020 ∙ by Ziyu Wang, et al. ∙ 6 ∙ share

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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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Bag of Tricks for Adversarial Training

Adversarial training (AT) is one of the most effective strategies for pr...
10/01/2020 ∙ by Tianyu Pang, et al. ∙ 0 ∙ share

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Deep Active Learning by Model Interpretability

Recent successes of Deep Neural Networks (DNNs) in a variety of research...
07/23/2020 ∙ by Qiang Liu, 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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A quasi-conservative discontinuous Galerkin method for multi-component flows using the non-oscillatory kinetic flux

In this paper, a high order quasi-conservative discontinuous Galerkin (D...
07/12/2020 ∙ by Dongmi Luo, et al. ∙ 0 ∙ share

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Delving into the Adversarial Robustness on Face Recognition

Face recognition has recently made substantial progress and achieved hig...
07/08/2020 ∙ by Xiao Yang, et al. ∙ 10 ∙ share

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Efficient Inference of Nonparametric Interaction in Spiking-neuron Networks

Hawkes process provides an effective statistical framework for analyzing...
06/23/2020 ∙ by Feng Zhou, et al. ∙ 6 ∙ share

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Absolutely convergent fixed-point fast sweeping WENO methods for steady state of hyperbolic conservation laws

Fixed-point iterative sweeping methods were developed in the literature ...
06/21/2020 ∙ by Liang Li, et al. ∙ 0 ∙ share

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Calibrated Reliable Regression using Maximum Mean Discrepancy

Accurate quantification of uncertainty is crucial for real-world applica...
06/18/2020 ∙ by Peng Cui, et al. ∙ 0 ∙ share

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Dynamic Window-level Granger Causality of Multi-channel Time Series

Granger causality method analyzes the time series causalities without bu...
06/14/2020 ∙ by Zhiheng Zhang, et al. ∙ 0 ∙ share

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Brain-inspired global-local hybrid learning towards human-like intelligence

The combination of neuroscience-oriented and computer-science-oriented a...
06/05/2020 ∙ by Yujie Wu, et al. ∙ 0 ∙ share

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Nonparametric Score Estimators

Estimating the score, i.e., the gradient of log density function, from a...
05/20/2020 ∙ by Yuhao Zhou, et al. ∙ 0 ∙ share

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SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models

Standard variational lower bounds used to train latent variable models p...
04/01/2020 ∙ by Yucen Luo, et al. ∙ 8 ∙ share

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Towards Privacy Protection by Generating Adversarial Identity Masks

As billions of personal data such as photos are shared through social me...
03/15/2020 ∙ by Xiao Yang, et al. ∙ 5 ∙ share

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Triple Memory Networks: a Brain-Inspired Method for Continual Learning

Continual acquisition of novel experience without interfering previously...
03/06/2020 ∙ by Liyuan Wang, et al. ∙ 0 ∙ share

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Jun Zhu

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