Search Results for author: Xiao Zhang

Found 125 papers, 49 papers with code

RBF-Softmax: Learning Deep Representative Prototypes with Radial Basis Function Softmax

1 code implementation ECCV 2020 Xiao Zhang, Rui Zhao, Yu Qiao, Hongsheng Li

To address this problem, this paper introduces a novel Radial Basis Function (RBF) distances to replace the commonly used inner products in the softmax loss function, such that it can adaptively assign losses to regularize the intra-class and inter-class distances by reshaping the relative differences, and thus creating more representative prototypes of classes to improve optimization.

软件标识符的自然语言规范性研究(Research on the Natural Language Normalness of Software Identifiers)

no code implementations CCL 2021 Dongzhen Wen, Fan Zhang, Xiao Zhang, Liang Yang, Yuan Lin, Bo Xu, Hongfei Lin

“软件源代码的理解则是软件协同开发与维护的核心, 而源代码中占半数以上的标识符的理解则在软件理解中起到重要作用, 传统软件工程主要研究通过命名规范限制标识符的命名过程以构造更易理解和交流的标识符。本文则在梳理分析常见编程语言命名规范的基础上, 提出一种全新的标识符可理解性评价标准。具体而言, 本文首先总结梳理了常见主流编程语言中的命名规范并类比自然语言语素概念本文提出基于软件语素的标识符构成过程, 即标识符的构成可被视为软件语素的生成、排列和连接过程。在此基础上, 本文提出一种结合自然语料库的软件标识符规范性评价方法, 用来衡量软件标识符是否易于理解。最后, 本文通过源代码理解数据集和乇乩乴乨乵乢平台中开源项目对规范性指标进行了验证性实验, 结果表明本文提出的规范性分数能够很好衡量软件项目的可理解性。”

PINF: Continuous Normalizing Flows for Physics-Constrained Deep Learning

no code implementations26 Sep 2023 Feng Liu, Faguo Wu, Xiao Zhang

The normalization constraint on probability density poses a significant challenge for solving the Fokker-Planck equation.

Generative Retrieval with Semantic Tree-Structured Item Identifiers via Contrastive Learning

no code implementations23 Sep 2023 Zihua Si, Zhongxiang Sun, Jiale Chen, Guozhang Chen, Xiaoxue Zang, Kai Zheng, Yang song, Xiao Zhang, Jun Xu

To obtain efficiency and effectiveness, this paper introduces a generative retrieval framework, namely SEATER, which learns SEmAntic Tree-structured item identifiERs via contrastive learning.

Contrastive Learning Recommendation Systems +1

How to Fine-tune the Model: Unified Model Shift and Model Bias Policy Optimization

no code implementations22 Sep 2023 Hai Zhang, Hang Yu, Junqiao Zhao, Di Zhang, ChangHuang, Hongtu Zhou, Xiao Zhang, Chen Ye

Designing and deriving effective model-based reinforcement learning (MBRL) algorithms with a performance improvement guarantee is challenging, mainly attributed to the high coupling between model learning and policy optimization.

Model-based Reinforcement Learning

HyperBandit: Contextual Bandit with Hypernewtork for Time-Varying User Preferences in Streaming Recommendation

no code implementations14 Aug 2023 Chenglei Shen, Xiao Zhang, Wei Wei, Jun Xu

In real-world streaming recommender systems, user preferences often dynamically change over time (e. g., a user may have different preferences during weekdays and weekends).

Recommendation Systems

LTP-MMF: Towards Long-term Provider Max-min Fairness Under Recommendation Feedback Loops

1 code implementation11 Aug 2023 Chen Xu, Xiaopeng Ye, Jun Xu, Xiao Zhang, Weiran Shen, Ji-Rong Wen

RFL means that recommender system can only receive feedback on exposed items from users and update recommender models incrementally based on this feedback.

Fairness Recommendation Systems

When Can Linear Learners be Robust to Indiscriminate Poisoning Attacks?

no code implementations3 Jul 2023 Fnu Suya, Xiao Zhang, Yuan Tian, David Evans

We study indiscriminate poisoning for linear learners where an adversary injects a few crafted examples into the training data with the goal of forcing the induced model to incur higher test error.

Data Poisoning

SciMRC: Multi-perspective Scientific Machine Reading Comprehension

no code implementations25 Jun 2023 Xiao Zhang, Heqi Zheng, Yuxiang Nie, Heyan Huang, Xian-Ling Mao

However, the dataset has ignored the fact that different readers may have different levels of understanding of the text, and only includes single-perspective question-answer pairs, leading to a lack of consideration of different perspectives.

Machine Reading Comprehension

KuaiSAR: A Unified Search And Recommendation Dataset

no code implementations13 Jun 2023 Zhongxiang Sun, Zihua Si, Xiaoxue Zang, Dewei Leng, Yanan Niu, Yang song, Xiao Zhang, Jun Xu

We believe this dataset will serve as a catalyst for innovative research and bridge the gap between academia and industry in understanding the S&R services in practical, real-world applications.

Multi-Task Learning Recommendation Systems

Controllable Multi-Objective Re-ranking with Policy Hypernetworks

1 code implementation8 Jun 2023 Sirui Chen, YuAn Wang, Zijing Wen, Zhiyu Li, Changshuo Zhang, Xiao Zhang, Quan Lin, Cheng Zhu, Jun Xu

In this paper, we propose a framework called controllable multi-objective re-ranking (CMR) which incorporates a hypernetwork to generate parameters for a re-ranking model according to different preference weights.

Recommendation Systems Re-Ranking

PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance

1 code implementation8 Jun 2023 Qianqian Xie, Weiguang Han, Xiao Zhang, Yanzhao Lai, Min Peng, Alejandro Lopez-Lira, Jimin Huang

This paper introduces PIXIU, a comprehensive framework including the first financial LLM based on fine-tuning LLaMA with instruction data, the first instruction data with 136K data samples to support the fine-tuning, and an evaluation benchmark with 5 tasks and 9 datasets.

Conversational Question Answering Language Modelling +5

When Search Meets Recommendation: Learning Disentangled Search Representation for Recommendation

1 code implementation18 May 2023 Zihua Si, Zhongxiang Sun, Xiao Zhang, Jun Xu, Xiaoxue Zang, Yang song, Kun Gai, Ji-Rong Wen

In our paper, we propose a Search-Enhanced framework for the Sequential Recommendation (SESRec) that leverages users' search interests for recommendation, by disentangling similar and dissimilar representations within S&R behaviors.

Contrastive Learning Disentanglement +1

Uncovering ChatGPT's Capabilities in Recommender Systems

1 code implementation3 May 2023 Sunhao Dai, Ninglu Shao, Haiyuan Zhao, Weijie Yu, Zihua Si, Chen Xu, Zhongxiang Sun, Xiao Zhang, Jun Xu

The debut of ChatGPT has recently attracted the attention of the natural language processing (NLP) community and beyond.

Explainable Recommendation Information Retrieval +2

A Lightweight Recurrent Learning Network for Sustainable Compressed Sensing

1 code implementation23 Apr 2023 Yu Zhou, Yu Chen, Xiao Zhang, Pan Lai, Lei Huang, Jianmin Jiang

While the initial reconstruction sub-network has a hierarchical structure to progressively recover the image, reducing the number of parameters, the residual reconstruction sub-network facilitates recurrent residual feature extraction via recurrent learning to perform both feature fusion and deep reconstructions across different scales.

Transition System Representation of Boolean Control Networks

no code implementations22 Apr 2023 Daizhan Cheng, Xiao Zhang, Zhengping Ji

The first kind of representation is state-based, which converts a BCN into a TS with either distinct control or non-distinct control.

Aggregated (Bi-)Simulation of Finite Valued Networks

no code implementations25 Mar 2023 Zhengping Ji, Xiao Zhang, Daizhan Cheng

Then the overall network can be approximated by the quotient systems of each blocks, which is called the aggregated simulation.

P-MMF: Provider Max-min Fairness Re-ranking in Recommender System

1 code implementation12 Mar 2023 Chen Xu, Sirui Chen, Jun Xu, Weiran Shen, Xiao Zhang, Gang Wang, Zhenghua Dong

In this paper, we proposed an online re-ranking model named Provider Max-min Fairness Re-ranking (P-MMF) to tackle the problem.

Fairness Recommendation Systems +1

Semi-Tensor Product of Hypermatrices with Application to Compound Hypermatrices

no code implementations11 Mar 2023 Daizhan Cheng, Xiao Zhang, Zhengping Ji

Some basic properties of the STP of matrices are extended to the STP of hypermatrices.

Analysis of Discrete-Time Switched Linear Systems under Logic Dynamic Switchings

no code implementations23 Nov 2022 Xiao Zhang, Zhengping Ji, Daizhan Cheng

The control properties of discrete-time switched linear systems (SLSs) with switching signals generated by logical dynamic systems are studied using the semi-tensor product approach.

PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Clouds

no code implementations24 Oct 2022 Zhaoqi Leng, Shuyang Cheng, Benjamin Caine, Weiyue Wang, Xiao Zhang, Jonathon Shlens, Mingxing Tan, Dragomir Anguelov

To alleviate the cost of hyperparameter tuning and iterative pseudo labeling, we develop a population-based data augmentation framework for 3D detection, named AutoPseudoAugment.

Data Augmentation Pseudo Label

Law Article-Enhanced Legal Case Matching: a Causal Learning Approach

1 code implementation20 Oct 2022 Zhongxiang Sun, Jun Xu, Xiao Zhang, Zhenhua Dong, Ji-Rong Wen

We show that the framework is model-agnostic, and a number of legal case matching models can be applied as the underlying models.

Semantic Text Matching Text Matching

Partial Information as Full: Reward Imputation with Sketching in Bandits

no code implementations13 Oct 2022 Xiao Zhang, Ninglu Shao, Zihua Si, Jun Xu, Wenhan Wang, Hanjing Su, Ji-Rong Wen

In this paper, we propose an efficient reward imputation approach using sketching for CBB, which completes the unobserved rewards with the imputed rewards approximating the full-information feedbacks.

Imputation regression

ET5: A Novel End-to-end Framework for Conversational Machine Reading Comprehension

1 code implementation COLING 2022 Xiao Zhang, Heyan Huang, Zewen Chi, Xian-Ling Mao

Conversational machine reading comprehension (CMRC) aims to assist computers to understand an natural language text and thereafter engage in a multi-turn conversation to answer questions related to the text.

Decision Making Machine Reading Comprehension

MICO: Selective Search with Mutual Information Co-training

1 code implementation COLING 2022 Zhanyu Wang, Xiao Zhang, Hyokun Yun, Choon Hui Teo, Trishul Chilimbi

In contrast to traditional exhaustive search, selective search first clusters documents into several groups before all the documents are searched exhaustively by a query, to limit the search executed within one group or only a few groups.


Invariant and Dual Invariant Subspaces of $k$-valued Networks

no code implementations1 Sep 2022 Daizhan Cheng, HongSheng Qi, Xiao Zhang, Zhengping Ji

Finally, the relationship between state invariant subspace and dual invariant subspace of a network is investigated.

Handling Data Heterogeneity in Federated Learning via Knowledge Fusion

no code implementations23 Jul 2022 Xu Zhou, Xinyu Lei, Cong Yang, Yichun Shi, Xiao Zhang, Jingwen Shi

The key idea in FedKF is to let the server return the global knowledge to be fused with the local knowledge in each training round so that the local model can be regularized towards the global optima.

Fairness Federated Learning +2

Feature Forgetting in Continual Representation Learning

no code implementations26 May 2022 Xiao Zhang, Dejing Dou, Ji Wu

To study the feature forgetting problem, we create a synthetic dataset to identify and visualize the prevalence of feature forgetting in neural networks.

Continual Learning Representation Learning

Cross-Lingual Phrase Retrieval

1 code implementation ACL 2022 Heqi Zheng, Xiao Zhang, Zewen Chi, Heyan Huang, Tan Yan, Tian Lan, Wei Wei, Xian-Ling Mao

In this paper, we propose XPR, a cross-lingual phrase retriever that extracts phrase representations from unlabeled example sentences.


Reinforcement Re-ranking with 2D Grid-based Recommendation Panels

no code implementations11 Apr 2022 Sirui Chen, Xiao Zhang, Xu Chen, Zhiyu Li, YuAn Wang, Quan Lin, Jun Xu

Then, it defines \emph{the MDP discrete time steps as the ranks in the initial ranking list, and the actions as the prediction of the user-item preference and the selection of the slots}.

Recommendation Systems Re-Ranking

A Model-Agnostic Causal Learning Framework for Recommendation using Search Data

1 code implementation9 Feb 2022 Zihua Si, Xueran Han, Xiao Zhang, Jun Xu, Yue Yin, Yang song, Ji-Rong Wen

In this paper, we propose a model-agnostic framework named IV4Rec that can effectively decompose the embedding vectors into these two parts, hence enhancing recommendation results.

Recommendation Systems

Combining Reinforcement Learning and Inverse Reinforcement Learning for Asset Allocation Recommendations

no code implementations6 Jan 2022 Igor Halperin, Jiayu Liu, Xiao Zhang

We suggest a simple practical method to combine the human and artificial intelligence to both learn best investment practices of fund managers, and provide recommendations to improve them.

reinforcement-learning Reinforcement Learning (RL)

Hidden Order of Boolean Networks

no code implementations25 Nov 2021 Xiao Zhang, Zhengping Ji, Daizhan Cheng

It is a common belief that the order of a Boolean network is mainly determined by its attractors, including fixed points and cycles.

Understanding Intrinsic Robustness Using Label Uncertainty

1 code implementation ICLR 2022 Xiao Zhang, David Evans

A fundamental question in adversarial machine learning is whether a robust classifier exists for a given task.

Adversarial Robustness Classification +1

Practical Assessment of Generalization Performance Robustness for Deep Networks via Contrastive Examples

no code implementations20 Jun 2021 Xuanyu Wu, Xuhong LI, Haoyi Xiong, Xiao Zhang, Siyu Huang, Dejing Dou

Incorporating with a set of randomized strategies for well-designed data transformations over the training set, ContRE adopts classification errors and Fisher ratios on the generated contrastive examples to assess and analyze the generalization performance of deep models in complement with a testing set.

Contrastive Learning

Refining Pseudo Labels with Clustering Consensus over Generations for Unsupervised Object Re-identification

1 code implementation CVPR 2021 Xiao Zhang, Yixiao Ge, Yu Qiao, Hongsheng Li

Unsupervised object re-identification targets at learning discriminative representations for object retrieval without any annotations.

Clustering Pseudo Label +1

Optimization Variance: Exploring Generalization Properties of DNNs

1 code implementation3 Jun 2021 Xiao Zhang, Dongrui Wu, Haoyi Xiong, Bo Dai

Unlike the conventional wisdom in statistical learning theory, the test error of a deep neural network (DNN) often demonstrates double descent: as the model complexity increases, it first follows a classical U-shaped curve and then shows a second descent.

Learning Theory

Multi-Grained Knowledge Distillation for Named Entity Recognition

1 code implementation NAACL 2021 Xuan Zhou, Xiao Zhang, Chenyang Tao, Junya Chen, Bing Xu, Wei Wang, Jing Xiao

To maximally assimilate knowledge into the student model, we propose a multi-grained distillation scheme, which integrates cross entropy involved in conditional random field (CRF) and fuzzy learning. To validate the effectiveness of our proposal, we conducted a comprehensive evaluation on five NER benchmarks, reporting cross-the-board performance gains relative to competing prior-arts.

Knowledge Distillation named-entity-recognition +2

DCAP: Deep Cross Attentional Product Network for User Response Prediction

1 code implementation18 May 2021 Zekai Chen, Fangtian Zhong, Zhumin Chen, Xiao Zhang, Robert Pless, Xiuzhen Cheng

Prior studies in predicting user response leveraged the feature interactions by enhancing feature vectors with products of features to model second-order or high-order cross features, either explicitly or implicitly.

Recommendation Systems

Learning Graph Structures with Transformer for Multivariate Time Series Anomaly Detection in IoT

1 code implementation8 Apr 2021 Zekai Chen, Dingshuo Chen, Xiao Zhang, Zixuan Yuan, Xiuzhen Cheng

This paper presented GTA, a new framework for multivariate time series anomaly detection that involves automatically learning a graph structure, graph convolution, and modeling temporal dependency using a Transformer-based architecture.

Anomaly Detection Time Series +1

Improved Estimation of Concentration Under $\ell_p$-Norm Distance Metrics Using Half Spaces

1 code implementation ICLR 2021 Jack Prescott, Xiao Zhang, David Evans

Mahloujifar et al. presented an empirical way to measure the concentration of a data distribution using samples, and employed it to find lower bounds on intrinsic robustness for several benchmark datasets.

Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and Beyond

1 code implementation19 Mar 2021 Xuhong LI, Haoyi Xiong, Xingjian Li, Xuanyu Wu, Xiao Zhang, Ji Liu, Jiang Bian, Dejing Dou

Then, to understand the interpretation results, we also survey the performance metrics for evaluating interpretation algorithms.

Adversarial Robustness

Multi-Task Time Series Forecasting With Shared Attention

no code implementations24 Jan 2021 Zekai Chen, Jiaze E, Xiao Zhang, Hao Sheng, Xiuzheng Cheng

Time series forecasting is a key component in many industrial and business decision processes and recurrent neural network (RNN) based models have achieved impressive progress on various time series forecasting tasks.

Time Series Time Series Forecasting

Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction

no code implementations18 Jan 2021 Qiang Zhou, Jingjing Gu, Xinjiang Lu, Fuzhen Zhuang, Yanchao Zhao, Qiuhong Wang, Xiao Zhang

Intuitively, the potential crowd flow of the new coming site can be implied by exploring the nearby sites.

Information distance for neural network functions

no code implementations1 Jan 2021 Xiao Zhang, Dejing Dou, Ji Wu

We provide a practical distance measure in the space of functions parameterized by neural networks.

Model information as an analysis tool in deep learning

no code implementations1 Jan 2021 Xiao Zhang, Di Hu, Xingjian Li, Dejing Dou, Ji Wu

We demonstrate using model information as a general analysis tool to gain insight into problems that arise in deep learning.

Guidance Module Network for Video Captioning

no code implementations20 Dec 2020 Xiao Zhang, Chunsheng Liu, Faliang Chang

In this paper, we present a novel architecture which introduces a guidance module to encourage the encoder-decoder model to generate words related to the past and future words in a caption.

Video Captioning

Using Enhanced Gaussian Cross-Entropy in Imitation Learning to Digging the First Diamond in Minecraft

no code implementations CUHK Course IERG5350 2020 Yingjie Cai, Xiao Zhang

Although state-ofthe-art reinforcement learning (RL) systems has led to breakthroughs in many difficult tasks, the sample inefficiency of standard reinforcement learning methods still precludes their application to more extremely complex tasks.

Imitation Learning reinforcement-learning +1

Self-Supervised Visual Representation Learning from Hierarchical Grouping

no code implementations NeurIPS 2020 Xiao Zhang, Michael Maire

We create a framework for bootstrapping visual representation learning from a primitive visual grouping capability.

Representation Learning

Cross-Lingual Document Retrieval with Smooth Learning

1 code implementation COLING 2020 Jiapeng Liu, Xiao Zhang, Dan Goldwasser, Xiao Wang

Cross-lingual document search is an information retrieval task in which the queries' language differs from the documents' language.

Information Retrieval Retrieval

Semi-supervised Autoencoding Projective Dependency Parsing

no code implementations COLING 2020 Xiao Zhang, Dan Goldwasser

We describe two end-to-end autoencoding models for semi-supervised graph-based projective dependency parsing.

Dependency Parsing

Measuring Information Transfer in Neural Networks

no code implementations16 Sep 2020 Xiao Zhang, Xingjian Li, Dejing Dou, Ji Wu

We propose a practical measure of the generalizable information in a neural network model based on prequential coding, which we term Information Transfer ($L_{IT}$).

Continual Learning Transfer Learning

Variance Reduction for Deep Q-Learning using Stochastic Recursive Gradient

no code implementations25 Jul 2020 Haonan Jia, Xiao Zhang, Jun Xu, Wei Zeng, Hao Jiang, Xiaohui Yan, Ji-Rong Wen

Deep Q-learning algorithms often suffer from poor gradient estimations with an excessive variance, resulting in unstable training and poor sampling efficiency.

Q-Learning reinforcement-learning +1

Semi-supervised Parsing with a Variational Autoencoding Parser

no code implementations WS 2020 Xiao Zhang, Dan Goldwasser

We propose an end-to-end variational autoencoding parsing (VAP) model for semi-supervised graph-based projective dependency parsing.

Dependency Parsing

Rethink the Connections among Generalization, Memorization and the Spectral Bias of DNNs

1 code implementation29 Apr 2020 Xiao Zhang, Haoyi Xiong, Dongrui Wu

Over-parameterized deep neural networks (DNNs) with sufficient capacity to memorize random noise can achieve excellent generalization performance, challenging the bias-variance trade-off in classical learning theory.

Learning Theory Memorization

Understanding the Intrinsic Robustness of Image Distributions using Conditional Generative Models

1 code implementation1 Mar 2020 Xiao Zhang, Jinghui Chen, Quanquan Gu, David Evans

Starting with Gilmer et al. (2018), several works have demonstrated the inevitability of adversarial examples based on different assumptions about the underlying input probability space.

Adversarial Robustness

Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization

1 code implementation ICML 2020 Sicheng Zhu, Xiao Zhang, David Evans

We develop a notion of representation vulnerability that captures the maximum change of mutual information between the input and output distributions, under the worst-case input perturbation.

Adversarial Robustness

Label-guided Learning for Text Classification

no code implementations25 Feb 2020 Xien Liu, Song Wang, Xiao Zhang, Xinxin You, Ji Wu, Dejing Dou

In this study, we propose a label-guided learning framework LguidedLearn for text representation and classification.

General Classification Representation Learning +2

Empirical Studies on the Properties of Linear Regions in Deep Neural Networks

no code implementations ICLR 2020 Xiao Zhang, Dongrui Wu

A deep neural network (DNN) with piecewise linear activations can partition the input space into numerous small linear regions, where different linear functions are fitted.

Universal Adversarial Perturbations for CNN Classifiers in EEG-Based BCIs

1 code implementation3 Dec 2019 Zihan Liu, Lubin Meng, Xiao Zhang, Weili Fang, Dongrui Wu

Multiple convolutional neural network (CNN) classifiers have been proposed for electroencephalogram (EEG) based brain-computer interfaces (BCIs).

EEG Electroencephalogram (EEG)

ACE -- An Anomaly Contribution Explainer for Cyber-Security Applications

no code implementations1 Dec 2019 Xiao Zhang, Manish Marwah, I-Ta Lee, Martin Arlitt, Dan Goldwasser

In this paper, we introduce Anomaly Contribution Explainer or ACE, a tool to explain security anomaly detection models in terms of the model features through a regression framework, and its variant, ACE-KL, which highlights the important anomaly contributors.

Anomaly Detection

Active Learning for Black-Box Adversarial Attacks in EEG-Based Brain-Computer Interfaces

no code implementations7 Nov 2019 Xue Jiang, Xiao Zhang, Dongrui Wu

Learning a good substitute model is critical to the success of these attacks, but it requires a large number of queries to the target model.

Active Learning EEG +1

An Adaptive Empirical Bayesian Method for Sparse Deep Learning

1 code implementation NeurIPS 2019 Wei Deng, Xiao Zhang, Faming Liang, Guang Lin

We propose a novel adaptive empirical Bayesian method for sparse deep learning, where the sparsity is ensured via a class of self-adaptive spike-and-slab priors.

SegSort: Segmentation by Discriminative Sorting of Segments

1 code implementation ICCV 2019 Jyh-Jing Hwang, Stella X. Yu, Jianbo Shi, Maxwell D. Collins, Tien-Ju Yang, Xiao Zhang, Liang-Chieh Chen

The proposed SegSort further produces an interpretable result, as each choice of label can be easily understood from the retrieved nearest segments.

Ranked #8 on Unsupervised Semantic Segmentation on PASCAL VOC 2012 val (using extra training data)

Clustering Metric Learning +1

Low-cost LIDAR based Vehicle Pose Estimation and Tracking

no code implementations3 Oct 2019 Chen Fu, Chiyu Dong, Xiao Zhang, John M. Dolan

Based on our previous optimization/criteria-based L-Shape fitting algorithm, we here propose a data-driven and model-based method for robust vehicle segmentation and tracking.

Vehicle Pose Estimation

Language-independent Cross-lingual Contextual Representations

no code implementations25 Sep 2019 Xiao Zhang, Song Wang, Dejing Dou, Xien Liu, Thien Huu Nguyen, Ji Wu

Contextual representation models like BERT have achieved state-of-the-art performance on a diverse range of NLP tasks.

Transfer Learning Zero-Shot Cross-Lingual Transfer

Learning Conceptual-Contextual Embeddings for Medical Text

no code implementations16 Aug 2019 Xiao Zhang, Dejing Dou, Ji Wu

External knowledge is often useful for natural language understanding tasks.

Natural Language Understanding

The iMaterialist Fashion Attribute Dataset

1 code implementation13 Jun 2019 Sheng Guo, Weilin Huang, Xiao Zhang, Prasanna Srikhanta, Yin Cui, Yuan Li, Matthew R. Scott, Hartwig Adam, Serge Belongie

The dataset is constructed from over one million fashion images with a label space that includes 8 groups of 228 fine-grained attributes in total.

General Classification Image Classification +1

Sentiment Tagging with Partial Labels using Modular Architectures

1 code implementation ACL 2019 Xiao Zhang, Dan Goldwasser

Many NLP learning tasks can be decomposed into several distinct sub-tasks, each associated with a partial label.

Sentiment Analysis

Empirically Measuring Concentration: Fundamental Limits on Intrinsic Robustness

1 code implementation NeurIPS 2019 Saeed Mahloujifar, Xiao Zhang, Mohammad Mahmoody, David Evans

Many recent works have shown that adversarial examples that fool classifiers can be found by minimally perturbing a normal input.

Image Classification

Joint Learning of Neural Networks via Iterative Reweighted Least Squares

1 code implementation16 May 2019 Zaiwei Zhang, Xiangru Huang, Qi-Xing Huang, Xiao Zhang, Yuan Li

We formulate this problem as joint learning of multiple copies of the same network architecture and enforce the network weights to be shared across these networks.

General Classification Image Classification +1

Normalized Diversification

1 code implementation CVPR 2019 Shaohui Liu, Xiao Zhang, Jianqiao Wangni, Jianbo Shi

We introduce the concept of normalized diversity which force the model to preserve the normalized pairwise distance between the sparse samples from a latent parametric distribution and their corresponding high-dimensional outputs.

Conditional Image Generation Hand Pose Estimation

On the Vulnerability of CNN Classifiers in EEG-Based BCIs

no code implementations31 Mar 2019 Xiao Zhang, Dongrui Wu

Deep learning has been successfully used in numerous applications because of its outstanding performance and the ability to avoid manual feature engineering.

EEG Electroencephalogram (EEG) +1

Delta Embedding Learning

no code implementations ACL 2019 Xiao Zhang, Ji Wu, Dejing Dou

Evaluation also confirms the tuned word embeddings have better semantic properties.

Reading Comprehension Word Embeddings

Tidal surface states as fingerprints of non-Hermitian nodal knot metals

no code implementations3 Dec 2018 Ching Hua Lee, Guangjie Li, YuHan Liu, Tommy Tai, Ronny Thomale, Xiao Zhang

Non-Hermitian nodal knot metals (NKMs) contains intricate complex-valued energy bands gives rise to knotted exceptional loops and new topological surface states.

Mesoscale and Nanoscale Physics Materials Science Other Condensed Matter Mathematical Physics Mathematical Physics Quantum Physics

Cost-Sensitive Robustness against Adversarial Examples

1 code implementation ICLR 2019 Xiao Zhang, David Evans

Several recent works have developed methods for training classifiers that are certifiably robust against norm-bounded adversarial perturbations.

General Classification

A Primal-Dual Analysis of Global Optimality in Nonconvex Low-Rank Matrix Recovery

no code implementations ICML 2018 Xiao Zhang, Lingxiao Wang, Yaodong Yu, Quanquan Gu

We propose a primal-dual based framework for analyzing the global optimality of nonconvex low-rank matrix recovery.

Matrix Completion

Learning One-hidden-layer ReLU Networks via Gradient Descent

no code implementations20 Jun 2018 Xiao Zhang, Yaodong Yu, Lingxiao Wang, Quanquan Gu

We study the problem of learning one-hidden-layer neural networks with Rectified Linear Unit (ReLU) activation function, where the inputs are sampled from standard Gaussian distribution and the outputs are generated from a noisy teacher network.

Multi-UAV Cooperative Trajectory for Servicing Dynamic Demands and Charging Battery

no code implementations22 May 2018 Xiao Zhang, Xuehe Wang, Xinping Xu, Lingjie Duan

To our best knowledge, this paper is the first to design and analyze cooperative path planning algorithms of a large UAV swarm for optimally servicing many spatial locations, where ground users' demands are released dynamically in the long time horizon.

Networking and Internet Architecture

OMG - Emotion Challenge Solution

no code implementations30 Apr 2018 Yuqi Cui, Xiao Zhang, Yang Wang, Chenfeng Guo, Dongrui Wu

This short paper describes our solution to the 2018 IEEE World Congress on Computational Intelligence One-Minute Gradual-Emotional Behavior Challenge, whose goal was to estimate continuous arousal and valence values from short videos.


NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications

4 code implementations ECCV 2018 Tien-Ju Yang, Andrew Howard, Bo Chen, Xiao Zhang, Alec Go, Mark Sandler, Vivienne Sze, Hartwig Adam

This work proposes an algorithm, called NetAdapt, that automatically adapts a pre-trained deep neural network to a mobile platform given a resource budget.

Image Classification

Entanglement-guided architectures of machine learning by quantum tensor network

1 code implementation24 Mar 2018 Yuhan Liu, Xiao Zhang, Maciej Lewenstein, Shi-Ju Ran

In this work, we implement simple numerical experiments, related to pattern/images classification, in which we represent the classifiers by many-qubit quantum states written in the matrix product states (MPS).

BIG-bench Machine Learning

Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow

1 code implementation ICML 2018 Xiao Zhang, Simon S. Du, Quanquan Gu

We revisit the inductive matrix completion problem that aims to recover a rank-$r$ matrix with ambient dimension $d$ given $n$ features as the side prior information.

Matrix Completion

Medical Exam Question Answering with Large-scale Reading Comprehension

no code implementations28 Feb 2018 Xiao Zhang, Ji Wu, Zhiyang He, Xien Liu, Ying Su

Reading and understanding text is one important component in computer aided diagnosis in clinical medicine, also being a major research problem in the field of NLP.

Question Answering Reading Comprehension

Range Loss for Deep Face Recognition With Long-Tailed Training Data

no code implementations ICCV 2017 Xiao Zhang, Zhiyuan Fang, Yandong Wen, Zhifeng Li, Yu Qiao

Unlike these work, this paper investigated how long-tailed data impact the training of face CNNs and develop a novel loss function, called range loss, to effectively utilize the tailed data in training process.

Face Recognition

Semi-supervised Structured Prediction with Neural CRF Autoencoder

1 code implementation EMNLP 2017 Xiao Zhang, Yong Jiang, Hao Peng, Kewei Tu, Dan Goldwasser

In this paper we propose an end-to-end neural CRF autoencoder (NCRF-AE) model for semi-supervised learning of sequential structured prediction problems.

Part-Of-Speech Tagging POS +1

A Unified Variance Reduction-Based Framework for Nonconvex Low-Rank Matrix Recovery

no code implementations ICML 2017 Lingxiao Wang, Xiao Zhang, Quanquan Gu

We propose a generic framework based on a new stochastic variance-reduced gradient descent algorithm for accelerating nonconvex low-rank matrix recovery.

Learning Unified Embedding for Apparel Recognition

no code implementations19 Jul 2017 Yang Song, Yuan Li, Bo Wu, Chao-Yeh Chen, Xiao Zhang, Hartwig Adam

To ease the training difficulty, a novel learning scheme is proposed by using the output from specialized models as learning targets so that L2 loss can be used instead of triplet loss.


Robust Wirtinger Flow for Phase Retrieval with Arbitrary Corruption

no code implementations20 Apr 2017 Jinghui Chen, Lingxiao Wang, Xiao Zhang, Quanquan Gu

We consider the robust phase retrieval problem of recovering the unknown signal from the magnitude-only measurements, where the measurements can be contaminated by both sparse arbitrary corruption and bounded random noise.


A Unified Framework for Low-Rank plus Sparse Matrix Recovery

no code implementations21 Feb 2017 Xiao Zhang, Lingxiao Wang, Quanquan Gu

We propose a unified framework to solve general low-rank plus sparse matrix recovery problems based on matrix factorization, which covers a broad family of objective functions satisfying the restricted strong convexity and smoothness conditions.

A Universal Variance Reduction-Based Catalyst for Nonconvex Low-Rank Matrix Recovery

no code implementations9 Jan 2017 Lingxiao Wang, Xiao Zhang, Quanquan Gu

We propose a generic framework based on a new stochastic variance-reduced gradient descent algorithm for accelerating nonconvex low-rank matrix recovery.

Stochastic Variance-reduced Gradient Descent for Low-rank Matrix Recovery from Linear Measurements

no code implementations2 Jan 2017 Xiao Zhang, Lingxiao Wang, Quanquan Gu

And in the noiseless setting, our algorithm is guaranteed to linearly converge to the unknown low-rank matrix and achieves exact recovery with optimal sample complexity.

Range Loss for Deep Face Recognition with Long-tail

2 code implementations28 Nov 2016 Xiao Zhang, Zhiyuan Fang, Yandong Wen, Zhifeng Li, Yu Qiao

Convolutional neural networks have achieved great improvement on face recognition in recent years because of its extraordinary ability in learning discriminative features of people with different identities.

Face Recognition

Composing Music with Grammar Argumented Neural Networks and Note-Level Encoding

no code implementations16 Nov 2016 Zheng Sun, Jiaqi Liu, Zewang Zhang, Jingwen Chen, Zhao Huo, Ching Hua Lee, Xiao Zhang

Creating aesthetically pleasing pieces of art, including music, has been a long-term goal for artificial intelligence research.

Music Generation

A Unified Computational and Statistical Framework for Nonconvex Low-Rank Matrix Estimation

no code implementations17 Oct 2016 Lingxiao Wang, Xiao Zhang, Quanquan Gu

In the general case with noisy observations, we show that our algorithm is guaranteed to linearly converge to the unknown low-rank matrix up to minimax optimal statistical error, provided an appropriate initial estimator.

Matrix Completion

Rademacher Complexity of the Restricted Boltzmann Machine

no code implementations7 Dec 2015 Xiao Zhang

Boltzmann machine, as a fundamental construction block of deep belief network and deep Boltzmann machines, is widely used in deep learning community and great success has been achieved.

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