b'Yong Jiang'

Loss Function Discovery for Object Detection via Convergence-Simulation Driven Search

Designing proper loss functions for vision tasks has been a long-standin...
02/09/2021 ∙ by Peidong Liu, et al. ∙ 0 ∙ share

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FenceBox: A Platform for Defeating Adversarial Examples with Data Augmentation Techniques

It is extensively studied that Deep Neural Networks (DNNs) are vulnerabl...
12/03/2020 ∙ by Han Qiu, et al. ∙ 0 ∙ share

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An Investigation of Potential Function Designs for Neural CRF

The neural linear-chain CRF model is one of the most widely-used approac...
11/11/2020 ∙ by Zechuan Hu, et al. ∙ 16 ∙ share

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Neural Latent Dependency Model for Sequence Labeling

Sequence labeling is a fundamental problem in machine learning, natural ...
11/10/2020 ∙ by Yang Zhou, et al. ∙ 0 ∙ share

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Reducing the Annotation Effort for Video Object Segmentation Datasets

For further progress in video object segmentation (VOS), larger, more di...
11/02/2020 ∙ by Paul Voigtlaender, et al. ∙ 0 ∙ share

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Second-Order Unsupervised Neural Dependency Parsing

Most of the unsupervised dependency parsers are based on first-order pro...
10/28/2020 ∙ by Songlin Yang, et al. ∙ 0 ∙ share

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When Machine Learning Meets Congestion Control: A Survey and Comparison

Machine learning (ML) has seen a significant surge and uptake across man...
10/22/2020 ∙ by Huiling Jiang, et al. ∙ 0 ∙ share

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Structural Knowledge Distillation

Knowledge distillation is a critical technique to transfer knowledge bet...
10/10/2020 ∙ by Xinyu Wang, et al. ∙ 8 ∙ share

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Automated Concatenation of Embeddings for Structured Prediction

Pretrained contextualized embeddings are powerful word representations f...
10/10/2020 ∙ by Xinyu Wang, et al. ∙ 4 ∙ share

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Adversarial Attack and Defense of Structured Prediction Models

Building an effective adversarial attacker and elaborating on countermea...
10/04/2020 ∙ by Wenjuan Han, et al. ∙ 0 ∙ share

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A Survey of Unsupervised Dependency Parsing

Syntactic dependency parsing is an important task in natural language pr...
10/04/2020 ∙ by Wenjuan Han, et al. ∙ 0 ∙ share

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Improving Query Efficiency of Black-box Adversarial Attack

Deep neural networks (DNNs) have demonstrated excellent performance on v...
09/24/2020 ∙ by Yang Bai, et al. ∙ 11 ∙ share

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More Embeddings, Better Sequence Labelers?

Recent work proposes a family of contextual embeddings that significantl...
09/17/2020 ∙ by Xinyu Wang, et al. ∙ 0 ∙ share

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Fast and Accurate Sequence Labeling with Approximate Inference Network

The linear-chain Conditional Random Field (CRF) model is one of the most...
09/17/2020 ∙ by Xinyu Wang, et al. ∙ 4 ∙ share

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Rectified Decision Trees: Exploring the Landscape of Interpretable and Effective Machine Learning

Interpretability and effectiveness are two essential and indispensable r...
08/21/2020 ∙ by Yiming Li, et al. ∙ 33 ∙ share

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Neural Network-based Automatic Factor Construction

Instead of conducting manual factor construction based on traditional an...
08/14/2020 ∙ by Jie Fang, et al. ∙ 0 ∙ share

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A Large-Scale Chinese Short-Text Conversation Dataset

The advancements of neural dialogue generation models show promising res...
08/10/2020 ∙ by Yida Wang, et al. ∙ 0 ∙ share

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Backdoor Learning: A Survey

Deep neural networks (DNNs) have demonstrated their power on many widely...
07/17/2020 ∙ by Yiming Li, et al. ∙ 47 ∙ share

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Stochastic Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization

In this paper, we introduce a simplified and unified method for finite-s...
06/18/2020 ∙ by Chaobing Song, et al. ∙ 0 ∙ share

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Enhanced Universal Dependency Parsing with Second-Order Inference and Mixture of Training Data

This paper presents the system used in our submission to the IWPT 2020 S...
06/02/2020 ∙ by Xinyu Wang, et al. ∙ 0 ∙ share

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Rethinking the Trigger of Backdoor Attack

In this work, we study the problem of backdoor attacks, which add a spec...
04/09/2020 ∙ by Yiming Li, et al. ∙ 7 ∙ share

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Structure-Level Knowledge Distillation For Multilingual Sequence Labeling

Multilingual sequence labeling is a task of predicting label sequences u...
04/08/2020 ∙ by Xinyu Wang, et al. ∙ 8 ∙ share

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Detecting Suspected Epidemic Cases Using Trajectory Big Data

Emerging infectious diseases are crucial threats to human health and glo...
04/02/2020 ∙ by Chuansai Zhou, et al. ∙ 0 ∙ share

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Toward Adversarial Robustness via Semi-supervised Robust Training

Adversarial examples have been shown to be the severe threat to deep neu...
03/16/2020 ∙ by Yiming Li, et al. ∙ 4 ∙ share

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Alpha Discovery Neural Network based on Prior Knowledge

In financial automatic feature construction task, genetic programming is...
12/26/2019 ∙ by Jie Fang, et al. ∙ 0 ∙ share

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Deep Flow Collaborative Network for Online Visual Tracking

The deep learning-based visual tracking algorithms such as MDNet achieve...
11/05/2019 ∙ by Peidong Liu, et al. ∙ 7 ∙ share

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Visual Privacy Protection via Mapping Distortion

Data privacy protection is an important research area, which is especial...
11/05/2019 ∙ by Peidong Liu, et al. ∙ 0 ∙ share

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Adversarial Defense Via Local Flatness Regularization

Adversarial defense is a popular and important research area. Due to its...
10/27/2019 ∙ by Jia Xu, et al. ∙ 0 ∙ share

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DAL: Dual Adversarial Learning for Dialogue Generation

In open-domain dialogue systems, generative approaches have attracted mu...
06/23/2019 ∙ by Shaobo Cui, et al. ∙ 0 ∙ share

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Rectified Decision Trees: Towards Interpretability, Compression and Empirical Soundness

How to obtain a model with good interpretability and performance has alw...
03/14/2019 ∙ by Jiawang Bai, et al. ∙ 0 ∙ share

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Multinomial Random Forests: Fill the Gap between Theoretical Consistency and Empirical Soundness

Random forests (RF) are one of the most widely used ensemble learning me...
03/10/2019 ∙ by Yiming Li, et al. ∙ 0 ∙ share

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Interface-Based Side Channel Attack Against Intel SGX

Intel has introduced a trusted computing technology, Intel Software Guar...
10/08/2018 ∙ by Jinwen Wang, et al. ∙ 0 ∙ share

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Fully Implicit Online Learning

Regularized online learning is widely used in machine learning. In this ...
09/25/2018 ∙ by Chaobing Song, et al. ∙ 8 ∙ share

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Maximum A Posteriori Inference in Sum-Product Networks

Sum-product networks (SPNs) are a class of probabilistic graphical model...
08/16/2017 ∙ by Jun Mei, et al. ∙ 0 ∙ share

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CRF Autoencoder for Unsupervised Dependency Parsing

Unsupervised dependency parsing, which tries to discover linguistic depe...
08/03/2017 ∙ by Jiong Cai, et al. ∙ 0 ∙ share

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Dependency Grammar Induction with Neural Lexicalization and Big Training Data

We study the impact of big models (in terms of the degree of lexicalizat...
08/02/2017 ∙ by Wenjuan Han, et al. ∙ 0 ∙ share

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Combining Generative and Discriminative Approaches to Unsupervised Dependency Parsing via Dual Decomposition

Unsupervised dependency parsing aims to learn a dependency parser from u...
08/02/2017 ∙ by Yong Jiang, et al. ∙ 0 ∙ share

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Latent Dependency Forest Models

Probabilistic modeling is one of the foundations of modern machine learn...
09/08/2016 ∙ by Shanbo Chu, et al. ∙ 0 ∙ share

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Yong Jiang

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