b'Jun Zhu'

research

∙ 08/11/2022

Regret Analysis for Hierarchical Experts Bandit Problem

We study an extension of standard bandit problem in which there are R la...

Qihan Guo, et al. ∙

research

∙ 08/03/2022

Robust Learning of Deep Time Series Anomaly Detection Models with Contaminated Training Data

Time series anomaly detection (TSAD) is an important data mining task wi...

Wenkai Li, et al. ∙

research

∙ 07/14/2022

EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations

Score-based diffusion generative models (SDGMs) have achieved the SOTA F...

Min Zhao, et al. ∙

research

∙ 07/13/2022

CoSCL: Cooperation of Small Continual Learners is Stronger than a Big One

Continual learning requires incremental compatibility with a sequence of...

Liyuan Wang, et al. ∙

research

∙ 07/12/2022

DGPO: Discovering Multiple Strategies with Diversity-Guided Policy Optimization

Recent algorithms designed for reinforcement learning tasks focus on fin...

Wenze Chen, et al. ∙

research

∙ 06/18/2022

Thompson Sampling for (Combinatorial) Pure Exploration

Existing methods of combinatorial pure exploration mainly focus on the U...

Siwei Wang, et al. ∙

research

∙ 06/17/2022

Fast Lossless Neural Compression with Integer-Only Discrete Flows

By applying entropy codecs with learned data distributions, neural compr...

Siyu Wang, et al. ∙

research

∙ 06/16/2022

Maximum Likelihood Training for Score-Based Diffusion ODEs by High-Order Denoising Score Matching

Score-based generative models have excellent performance in terms of gen...

Cheng Lu, et al. ∙

research

∙ 06/15/2022

Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models

Diffusion probabilistic models (DPMs) are a class of powerful deep gener...

Fan Bao, et al. ∙

research

∙ 06/12/2022

Consistent Attack: Universal Adversarial Perturbation on Embodied Vision Navigation

Embodied agents in vision navigation coupled with deep neural networks h...

You Qiaoben, et al. ∙

research

∙ 06/09/2022

Towards Safe Reinforcement Learning via Constraining Conditional Value-at-Risk

Though deep reinforcement learning (DRL) has obtained substantial succes...

Chengyang Ying, et al. ∙

research

∙ 06/09/2022

Diagnosing Ensemble Few-Shot Classifiers

The base learners and labeled samples (shots) in an ensemble few-shot cl...

Weikai Yang, et al. ∙

research

∙ 06/09/2022

GSmooth: Certified Robustness against Semantic Transformations via Generalized Randomized Smoothing

Certified defenses such as randomized smoothing have shown promise towar...

Zhongkai Hao, et al. ∙

research

∙ 06/02/2022

DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps

Diffusion probabilistic models (DPMs) are emerging powerful generative m...

Cheng Lu, et al. ∙

research

∙ 05/28/2022

BadDet: Backdoor Attacks on Object Detection

Deep learning models have been deployed in numerous real-world applicati...

Shih-Han Chan, et al. ∙

research

∙ 05/26/2022

Censored Quantile Regression Neural Networks

This paper considers doing quantile regression on censored data using ne...

Tim Pearce, et al. ∙

research

∙ 05/22/2022

Fast Instrument Learning with Faster Rates

We investigate nonlinear instrumental variable (IV) regression given hig...

Ziyu Wang, et al. ∙

research

∙ 04/30/2022

NeuralEF: Deconstructing Kernels by Deep Neural Networks

Learning the principal eigenfunctions of an integral operator defined by...

Zhijie Deng, et al. ∙

research

∙ 04/30/2022

Deep Ensemble as a Gaussian Process Approximate Posterior

Deep Ensemble (DE) is an effective alternative to Bayesian neural networ...

Zhijie Deng, et al. ∙

research

∙ 03/13/2022

Policy Learning for Robust Markov Decision Process with a Mismatched Generative Model

In high-stake scenarios like medical treatment and auto-piloting, it's r...

Jialian Li, et al. ∙

research

∙ 03/13/2022

Query-Efficient Black-box Adversarial Attacks Guided by a Transfer-based Prior

Adversarial attacks have been extensively studied in recent years since ...

Yinpeng Dong, et al. ∙

research

∙ 03/09/2022

Controllable Evaluation and Generation of Physical Adversarial Patch on Face Recognition

Recent studies have revealed the vulnerability of face recognition model...

Xiao Yang, et al. ∙

research

∙ 02/21/2022

Robustness and Accuracy Could Be Reconcilable by (Proper) Definition

The trade-off between robustness and accuracy has been widely studied in...

Tianyu Pang, et al. ∙

research

∙ 02/14/2022

Memory Replay with Data Compression for Continual Learning

Continual learning needs to overcome catastrophic forgetting of the past...

Liyuan Wang, et al. ∙

research

∙ 01/17/2022

Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models

Diffusion probabilistic models (DPMs) represent a class of powerful gene...

Fan Bao, et al. ∙

research

∙ 11/30/2021

Scalable Semiparametric Spatio-temporal Regression for Large Data Analysis

With the rapid advances of data acquisition techniques, spatio-temporal ...

Ting Fung Ma, et al. ∙

research

∙ 11/09/2021

Improving Next-Application Prediction with Deep Personalized-Attention Neural Network

Recently, due to the ubiquity and supremacy of E-recruitment platforms, ...

Jun Zhu, et al. ∙

research

∙ 10/23/2021

AFEC: Active Forgetting of Negative Transfer in Continual Learning

Continual learning aims to learn a sequence of tasks from dynamic data d...

Liyuan Wang, et al. ∙

research

∙ 10/15/2021

Adversarial Attacks on ML Defense Models Competition

Due to the vulnerability of deep neural networks (DNNs) to adversarial e...

Yinpeng Dong, et al. ∙

research

∙ 10/13/2021

Model-Agnostic Meta-Attack: Towards Reliable Evaluation of Adversarial Robustness

The vulnerability of deep neural networks to adversarial examples has mo...

Xiao Yang, et al. ∙

research

∙ 10/09/2021

TiKick: Toward Playing Multi-agent Football Full Games from Single-agent Demonstrations

Deep reinforcement learning (DRL) has achieved super-human performance o...

Shiyu Huang, et al. ∙

research

∙ 10/08/2021

Ranking Cost: Building An Efficient and Scalable Circuit Routing Planner with Evolution-Based Optimization

Circuit routing has been a historically challenging problem in designing...

Shiyu Huang, et al. ∙

research

∙ 09/30/2021

Adversarial Semantic Contour for Object Detection

Modern object detectors are vulnerable to adversarial examples, which br...

Yichi Zhang, et al. ∙

research

∙ 09/27/2021

Query-based Adversarial Attacks on Graph with Fake Nodes

While deep neural networks have achieved great success on the graph anal...

Zhengyi Wang, et al. ∙

research

∙ 07/29/2021

Tianshou: a Highly Modularized Deep Reinforcement Learning Library

We present Tianshou, a highly modularized python library for deep reinfo...

Jiayi Weng, et al. ∙

research

∙ 07/22/2021

Query2Label: A Simple Transformer Way to Multi-Label Classification

This paper presents a simple and effective approach to solving the multi...

Shilong Liu, et al. ∙

research

∙ 07/21/2021

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

Zeroth-order (ZO) optimization is widely used to handle challenging task...

Shuyu Cheng, et al. ∙

research

∙ 07/05/2021

Boosting Transferability of Targeted Adversarial Examples via Hierarchical Generative Networks

Transfer-based adversarial attacks can effectively evaluate model robust...

Xiao Yang, et al. ∙

research

∙ 06/30/2021

Understanding Adversarial Attacks on Observations in Deep Reinforcement Learning

Recent works demonstrate that deep reinforcement learning (DRL) models a...

You Qiaoben, et al. ∙

research

∙ 06/29/2021

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

Balancing exploration and exploitation (EE) is a fundamental problem in ...

Yichi Zhou, et al. ∙

research

∙ 06/29/2021

Improving Transferability of Adversarial Patches on Face Recognition with Generative Models

Face recognition is greatly improved by deep convolutional neural networ...

Zihao Xiao, et al. ∙

research

∙ 06/18/2021

Accumulative Poisoning Attacks on Real-time Data

Collecting training data from untrusted sources exposes machine learning...

Tianyu Pang, et al. ∙

research

∙ 06/16/2021

Scalable Quasi-Bayesian Inference for Instrumental Variable Regression

Recent years have witnessed an upsurge of interest in employing flexible...

Ziyu Wang, et al. ∙

research

∙ 06/09/2021

Understanding Softmax Confidence and Uncertainty

It is often remarked that neural networks fail to increase their uncerta...

Tim Pearce, et al. ∙

research

∙ 06/09/2021

Nonlinear Hawkes Processes in Time-Varying System

Hawkes processes are a class of point processes that have the ability to...

Feng Zhou, et al. ∙

research

∙ 06/08/2021

Stability and Generalization of Bilevel Programming in Hyperparameter Optimization

Recently, the (gradient-based) bilevel programming framework is widely u...

Fan Bao, et al. ∙

research

∙ 06/03/2021

Exploring Memorization in Adversarial Training

It is well known that deep learning models have a propensity for fitting...

Yinpeng Dong, et al. ∙

research

∙ 06/02/2021

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

Partial differential equations (PDEs) fitting scientific data can repres...

Yingtao Luo, et al. ∙

research

∙ 05/31/2021

Adversarial Training with Rectified Rejection

Adversarial training (AT) is one of the most effective strategies for pr...

Tianyu Pang, et al. ∙

research

∙ 05/26/2021

Unsupervised Part Segmentation through Disentangling Appearance and Shape

We study the problem of unsupervised discovery and segmentation of objec...

Shilong Liu, et al. ∙

Jun Zhu

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