Search Results for author: Yue Yu

Found 91 papers, 43 papers with code

AcTune: Uncertainty-Based Active Self-Training for Active Fine-Tuning of Pretrained Language Models

1 code implementation NAACL 2022 Yue Yu, Lingkai Kong, Jieyu Zhang, Rongzhi Zhang, Chao Zhang

We develop AcTune, a new framework that improves the label efficiency of active PLM fine-tuning by unleashing the power of unlabeled data via self-training.

Active Learning text-classification +1

Prompt-Based Rule Discovery and Boosting for Interactive Weakly-Supervised Learning

1 code implementation ACL 2022 Rongzhi Zhang, Yue Yu, Pranav Shetty, Le Song, Chao Zhang

Weakly-supervised learning (WSL) has shown promising results in addressing label scarcity on many NLP tasks, but manually designing a comprehensive, high-quality labeling rule set is tedious and difficult.

Weakly-supervised Learning

At Which Training Stage Does Cocde Data Help LLMs Reasoning?

1 code implementation28 Sep 2023 Yingwei Ma, Yue Liu, Yue Yu, Yuanliang Zhang, Yu Jiang, Changjian Wang, Shanshan Li

Inspired by the great success of code data in training LLMs, we naturally wonder at which training stage introducing code data can really help LLMs reasoning.

Question Answering

Provable Training for Graph Contrastive Learning

1 code implementation25 Sep 2023 Yue Yu, Xiao Wang, Mengmei Zhang, Nian Liu, Chuan Shi

To this end, we propose the PrOvable Training (POT) for GCL, which regularizes the training of GCL to encode node embeddings that follows the GCL principle better.

Contrastive Learning

Active Inverse Learning in Stackelberg Trajectory Games

no code implementations15 Aug 2023 Yue Yu, Jacob Levy, Negar Mehr, David Fridovich-Keil, Ufuk Topcu

We formulate an inverse learning problem in a Stackelberg game between a leader and a follower, where each player's action is the trajectory of a dynamical system.

Intelligence-Endogenous Management Platform for Computing and Network Convergence

no code implementations7 Aug 2023 Zicong Hong, Xiaoyu Qiu, Jian Lin, Wuhui Chen, Yue Yu, Hui Wang, Song Guo, Wen Gao

Therefore, in this article, we present the concept of an intelligence-endogenous management platform for CNCs called \emph{CNC brain} based on artificial intelligence technologies.

Management Scheduling

Model Provenance via Model DNA

no code implementations4 Aug 2023 Xin Mu, Yu Wang, Yehong Zhang, JiaQi Zhang, Hui Wang, Yang Xiang, Yue Yu

Understanding the life cycle of the machine learning (ML) model is an intriguing area of research (e. g., understanding where the model comes from, how it is trained, and how it is used).

Representation Learning

Personalized Federated Learning via Amortized Bayesian Meta-Learning

no code implementations5 Jul 2023 Shiyu Liu, Shaogao Lv, Dun Zeng, Zenglin Xu, Hui Wang, Yue Yu

Federated learning is a decentralized and privacy-preserving technique that enables multiple clients to collaborate with a server to learn a global model without exposing their private data.

Meta-Learning Personalized Federated Learning +2

Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias

2 code implementations28 Jun 2023 Yue Yu, Yuchen Zhuang, Jieyu Zhang, Yu Meng, Alexander Ratner, Ranjay Krishna, Jiaming Shen, Chao Zhang

Additionally, we present a comprehensive empirical study on data generation encompassing vital aspects like bias, diversity, and efficiency, and highlight three key observations: firstly, synthetic datasets generated by simple prompts exhibit significant biases, such as regional bias; secondly, attribute diversity plays a pivotal role in enhancing model performance; lastly, attributed prompts achieve the performance of simple class-conditional prompts while utilizing only 5\% of the querying cost of ChatGPT associated with the latter.

Language Modelling Large Language Model

Practical Privacy-Preserving Gaussian Process Regression via Secret Sharing

no code implementations26 Jun 2023 Jinglong Luo, Yehong Zhang, JiaQi Zhang, Shuang Qin, Hui Wang, Yue Yu, Zenglin Xu

In contrast to existing studies that protect the data privacy of GPR via homomorphic encryption, differential privacy, or federated learning, our proposed method is more practical and can be used to preserve the data privacy of both the model inputs and outputs for various data-sharing scenarios (e. g., horizontally/vertically-partitioned data).

Federated Learning GPR +2

ToolQA: A Dataset for LLM Question Answering with External Tools

1 code implementation23 Jun 2023 Yuchen Zhuang, Yue Yu, Kuan Wang, Haotian Sun, Chao Zhang

To address this issue, we introduce a new dataset called ToolQA, which is designed to faithfully evaluate LLMs' ability to use external tools for question answering.

Question Answering

MUBen: Benchmarking the Uncertainty of Pre-Trained Models for Molecular Property Prediction

1 code implementation14 Jun 2023 Yinghao Li, Lingkai Kong, Yuanqi Du, Yue Yu, Yuchen Zhuang, Wenhao Mu, Chao Zhang

While some studies have used UQ to improve molecular pre-trained models, the process of selecting suitable backbone and UQ methods for reliable molecular uncertainty estimation remains underexplored.

Benchmarking Drug Discovery +3

Weakly-Supervised Scientific Document Classification via Retrieval-Augmented Multi-Stage Training

1 code implementation12 Jun 2023 ran Xu, Yue Yu, Joyce C. Ho, Carl Yang

To address this challenge, we propose a weakly-supervised approach for scientific document classification using label names only.

Document Classification Retrieval

A Survey on Knowledge Graphs for Healthcare: Resources, Applications, and Promises

no code implementations7 Jun 2023 Hejie Cui, Jiaying Lu, Shiyu Wang, ran Xu, Wenjing Ma, Shaojun Yu, Yue Yu, Xuan Kan, Chen Ling, Liang Zhao, Joyce Ho, Fei Wang, Carl Yang

Healthcare knowledge graphs (HKGs) have emerged as a promising tool for organizing medical knowledge in a structured and interpretable way, which provides a comprehensive view of medical concepts and their relationships.

Knowledge Graphs

R-Mixup: Riemannian Mixup for Biological Networks

no code implementations5 Jun 2023 Xuan Kan, Zimu Li, Hejie Cui, Yue Yu, ran Xu, Shaojun Yu, Zilong Zhang, Ying Guo, Carl Yang

Biological networks are commonly used in biomedical and healthcare domains to effectively model the structure of complex biological systems with interactions linking biological entities.

Data Augmentation

Local Boosting for Weakly-Supervised Learning

no code implementations5 Jun 2023 Rongzhi Zhang, Yue Yu, Jiaming Shen, Xiquan Cui, Chao Zhang

In this work, we show that the standard implementation of the convex combination of base learners can hardly work due to the presence of noisy labels.

Weakly-supervised Learning

DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling

1 code implementation30 May 2023 Yuchen Zhuang, Yue Yu, Lingkai Kong, Xiang Chen, Chao Zhang

Most existing methods for learning from noisy labels use static input features for denoising, but these methods are limited by the information they can provide on true label distributions and can result in biased or incorrect predictions.


Higher Order Gauge Equivariant CNNs on Riemannian Manifolds and Applications

no code implementations26 May 2023 Gianfranco Cortes, Yue Yu, Robin Chen, Melissa Armstrong, David Vaillancourt, Baba C. Vemuri

With the advent of group equivariant convolutions in deep networks literature, spherical CNNs with $\mathsf{SO}(3)$-equivariant layers have been developed to cope with data that are samples of signals on the sphere $S^2$.

Dynamic Routing in Stochastic Urban Air Mobility Networks: A Markov Decision Process Approach

no code implementations11 May 2023 Qinshuang Wei, Yue Yu, Ufuk Topcu

Urban air mobility (UAM) is an emerging concept in short-range aviation transportation, where the aircraft will take off, land, and charge their batteries at a set of vertistops, and travel only through a set of flight corridors connecting these vertistops.

Decision Making

Domain Agnostic Fourier Neural Operators

no code implementations30 Apr 2023 Ning Liu, Siavash Jafarzadeh, Yue Yu

To lift such a restriction and permit FFT on irregular geometries as well as topology changes, we introduce domain agnostic Fourier neural operator (DAFNO), a novel neural operator architecture for learning surrogates with irregular geometries and evolving domains.

Stochastic Clustered Federated Learning

no code implementations2 Mar 2023 Dun Zeng, Xiangjing Hu, Shiyu Liu, Yue Yu, Qifan Wang, Zenglin Xu

Federated learning is a distributed learning framework that takes full advantage of private data samples kept on edge devices.

Federated Learning

MetaNO: How to Transfer Your Knowledge on Learning Hidden Physics

no code implementations28 Jan 2023 Lu Zhang, Huaiqian You, Tian Gao, Mo Yu, Chung-Hao Lee, Yue Yu

Gradient-based meta-learning methods have primarily been applied to classical machine learning tasks such as image classification.

Image Classification Meta-Learning

Towards a unified nonlocal, peridynamics framework for the coarse-graining of molecular dynamics data with fractures

no code implementations11 Jan 2023 Huaiqian You, Xiao Xu, Yue Yu, Stewart Silling, Marta D'Elia, John Foster

Then, based on the coarse-grained MD data, a two-phase optimization-based learning approach is proposed to infer the optimal peridynamics model with damage criterion.

Neighborhood-Regularized Self-Training for Learning with Few Labels

1 code implementation10 Jan 2023 ran Xu, Yue Yu, Hejie Cui, Xuan Kan, Yanqiao Zhu, Joyce Ho, Chao Zhang, Carl Yang

Our further analysis demonstrates that our proposed data selection strategy reduces the noise of pseudo labels by 36. 8% and saves 57. 3% of the time when compared with the best baseline.

INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation

no code implementations29 Dec 2022 Ning Liu, Yue Yu, Huaiqian You, Neeraj Tatikola

Neural operators, which emerge as implicit solution operators of hidden governing equations, have recently become popular tools for learning responses of complex real-world physical systems.

EDoG: Adversarial Edge Detection For Graph Neural Networks

no code implementations27 Dec 2022 Xiaojun Xu, Yue Yu, Hanzhang Wang, Alok Lal, Carl A. Gunter, Bo Li

In this paper, we propose a general adversarial edge detection pipeline EDoG without requiring knowledge of the attack strategies based on graph generation.

Edge Detection Graph Generation +2

Transferability Estimation Based On Principal Gradient Expectation

no code implementations29 Nov 2022 Huiyan Qi, Lechao Cheng, Jingjing Chen, Yue Yu, Xue Song, Zunlei Feng, Yu-Gang Jiang

Transfer learning aims to improve the performance of target tasks by transferring knowledge acquired in source tasks.

Transfer Learning

Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind

1 code implementation9 Nov 2022 Mo Yu, Yisi Sang, Kangsheng Pu, Zekai Wei, Han Wang, Jing Li, Yue Yu, Jie zhou

When reading a story, humans can rapidly understand new fictional characters with a few observations, mainly by drawing analogy to fictional and real people they met before in their lives.

Meta-Learning Metric Learning

Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks

1 code implementation1 Nov 2022 Yue Yu, Xuan Kan, Hejie Cui, ran Xu, Yujia Zheng, Xiangchen Song, Yanqiao Zhu, Kun Zhang, Razieh Nabi, Ying Guo, Chao Zhang, Carl Yang

To better adapt GNNs for fMRI analysis, we propose TBDS, an end-to-end framework based on \underline{T}ask-aware \underline{B}rain connectivity \underline{D}AG (short for Directed Acyclic Graph) \underline{S}tructure generation for fMRI analysis.

Time Series Time Series Analysis

Reduce Catastrophic Forgetting of Dense Retrieval Training with Teleportation Negatives

1 code implementation31 Oct 2022 Si Sun, Chenyan Xiong, Yue Yu, Arnold Overwijk, Zhiyuan Liu, Jie Bao

In this paper, we investigate the instability in the standard dense retrieval training, which iterates between model training and hard negative selection using the being-trained model.


COCO-DR: Combating Distribution Shifts in Zero-Shot Dense Retrieval with Contrastive and Distributionally Robust Learning

1 code implementation27 Oct 2022 Yue Yu, Chenyan Xiong, Si Sun, Chao Zhang, Arnold Overwijk

We present a new zero-shot dense retrieval (ZeroDR) method, COCO-DR, to improve the generalization ability of dense retrieval by combating the distribution shifts between source training tasks and target scenarios.

Language Modelling Retrieval +2

Online Poisoning Attacks Against Data-Driven Predictive Control

no code implementations19 Sep 2022 Yue Yu, Ruihan Zhao, Sandeep Chinchali, Ufuk Topcu

Data-driven predictive control (DPC) is a feedback control method for systems with unknown dynamics.

Cold-Start Data Selection for Few-shot Language Model Fine-tuning: A Prompt-Based Uncertainty Propagation Approach

1 code implementation15 Sep 2022 Yue Yu, Rongzhi Zhang, ran Xu, Jieyu Zhang, Jiaming Shen, Chao Zhang

Large Language Models have demonstrated remarkable few-shot performance, but the performance can be sensitive to the selection of few-shot instances.

Language Modelling Text Classification

OpenMedIA: Open-Source Medical Image Analysis Toolbox and Benchmark under Heterogeneous AI Computing Platforms

no code implementations11 Aug 2022 Jia-Xin Zhuang, Xiansong Huang, Yang Yang, Jiancong Chen, Yue Yu, Wei Gao, Ge Li, Jie Chen, Tong Zhang

In this paper, we present OpenMedIA, an open-source toolbox library containing a rich set of deep learning methods for medical image analysis under heterogeneous Artificial Intelligence (AI) computing platforms.

Image Classification Medical Image Classification +2

Physics-Informed Deep Neural Operator Networks

no code implementations8 Jul 2022 Somdatta Goswami, Aniruddha Bora, Yue Yu, George Em Karniadakis

Standard neural networks can approximate general nonlinear operators, represented either explicitly by a combination of mathematical operators, e. g., in an advection-diffusion-reaction partial differential equation, or simply as a black box, e. g., a system-of-systems.

PolyU-BPCoMa: A Dataset and Benchmark Towards Mobile Colorized Mapping Using a Backpack Multisensorial System

1 code implementation15 Jun 2022 Wenzhong Shi, Pengxin Chen, Muyang Wang, Sheng Bao, Haodong Xiang, Yue Yu, Daping Yang

Color checker boards are pasted in each surveyed area as targets and ground truth data are collected by an advanced terrestrial laser scanner (TLS).


MetaNOR: A Meta-Learnt Nonlocal Operator Regression Approach for Metamaterial Modeling

no code implementations4 Jun 2022 Lu Zhang, Huaiqian You, Yue Yu

We propose MetaNOR, a meta-learnt approach for transfer-learning operators based on the nonlocal operator regression.

regression Transfer Learning

Nonparametric learning of kernels in nonlocal operators

no code implementations23 May 2022 Fei Lu, Qingci An, Yue Yu

In this work, we provide a rigorous identifiability analysis and convergence study for the learning of kernels in nonlocal operators.

Nebula-I: A General Framework for Collaboratively Training Deep Learning Models on Low-Bandwidth Cloud Clusters

1 code implementation19 May 2022 Yang Xiang, Zhihua Wu, Weibao Gong, Siyu Ding, Xianjie Mo, Yuang Liu, Shuohuan Wang, Peng Liu, Yongshuai Hou, Long Li, Bin Wang, Shaohuai Shi, Yaqian Han, Yue Yu, Ge Li, Yu Sun, Yanjun Ma, dianhai yu

We took natural language processing (NLP) as an example to show how Nebula-I works in different training phases that include: a) pre-training a multilingual language model using two remote clusters; and b) fine-tuning a machine translation model using knowledge distilled from pre-trained models, which run through the most popular paradigm of recent deep learning.

Cross-Lingual Natural Language Inference Distributed Computing +2

Modality-Balanced Embedding for Video Retrieval

no code implementations18 Apr 2022 Xun Wang, Bingqing Ke, Xuanping Li, Fangyu Liu, Mingyu Zhang, Xiao Liang, Qiushi Xiao, Cheng Luo, Yue Yu

This modality imbalanceresults from a) modality gap: the relevance between a query and a video text is much easier to learn as the query is also a piece of text, with the same modality as the video text; b) data bias: most training samples can be solved solely by text matching.

Retrieval Text Matching +1

A Physics-Guided Neural Operator Learning Approach to Model Biological Tissues from Digital Image Correlation Measurements

1 code implementation1 Apr 2022 Huaiqian You, Quinn Zhang, Colton J. Ross, Chung-Hao Lee, Ming-Chen Hsu, Yue Yu

To improve the generalizability of our framework, we propose a physics-guided neural operator learning model via imposing partial physics knowledge.

Operator learning

PRBoost: Prompt-Based Rule Discovery and Boosting for Interactive Weakly-Supervised Learning

1 code implementation18 Mar 2022 Rongzhi Zhang, Yue Yu, Pranav Shetty, Le Song, Chao Zhang

Weakly-supervised learning (WSL) has shown promising results in addressing label scarcity on many NLP tasks, but manually designing a comprehensive, high-quality labeling rule set is tedious and difficult.

Weakly-supervised Learning

Learning Deep Implicit Fourier Neural Operators (IFNOs) with Applications to Heterogeneous Material Modeling

1 code implementation15 Mar 2022 Huaiqian You, Quinn Zhang, Colton J. Ross, Chung-Hao Lee, Yue Yu

In this work, we propose to use data-driven modeling, which directly utilizes high-fidelity simulation and/or experimental measurements to predict a material's response without using conventional constitutive models.

Interfacing Finite Elements with Deep Neural Operators for Fast Multiscale Modeling of Mechanics Problems

no code implementations25 Feb 2022 Minglang Yin, Enrui Zhang, Yue Yu, George Em Karniadakis

In this work, we explore the idea of multiscale modeling with machine learning and employ DeepONet, a neural operator, as an efficient surrogate of the expensive solver.

Excitement Surfeited Turns to Errors: Deep Learning Testing Framework Based on Excitable Neurons

1 code implementation12 Feb 2022 Haibo Jin, Ruoxi Chen, Haibin Zheng, Jinyin Chen, Yao Cheng, Yue Yu, Xianglong Liu

By maximizing the number of excitable neurons concerning various wrong behaviors of models, DeepSensor can generate testing examples that effectively trigger more errors due to adversarial inputs, polluted data and incomplete training.

Image Classification Speaker Recognition

A Survey on Programmatic Weak Supervision

1 code implementation11 Feb 2022 Jieyu Zhang, Cheng-Yu Hsieh, Yue Yu, Chao Zhang, Alexander Ratner

Labeling training data has become one of the major roadblocks to using machine learning.

Multi-task Joint Strategies of Self-supervised Representation Learning on Biomedical Networks for Drug Discovery

2 code implementations12 Jan 2022 Xiaoqi Wang, Yingjie Cheng, Yaning Yang, Yue Yu, Fei Li, Shaoliang Peng

Therefore, we conjecture that the multimodal and local-global combination strategies can be treated as the guideline of multi-task SSL for drug discovery.

Drug Discovery Graph Attention +2

Nonlocal Kernel Network (NKN): a Stable and Resolution-Independent Deep Neural Network

no code implementations6 Jan 2022 Huaiqian You, Yue Yu, Marta D'Elia, Tian Gao, Stewart Silling

In this work, we propose a novel nonlocal neural operator, which we refer to as nonlocal kernel network (NKN), that is resolution independent, characterized by deep neural networks, and capable of handling a variety of tasks such as learning governing equations and classifying images.

Image Classification

NeuronFair: Interpretable White-Box Fairness Testing through Biased Neuron Identification

1 code implementation25 Dec 2021 Haibin Zheng, Zhiqing Chen, Tianyu Du, Xuhong Zhang, Yao Cheng, Shouling Ji, Jingyi Wang, Yue Yu, Jinyin Chen

To overcome the challenges, we propose NeuronFair, a new DNN fairness testing framework that differs from previous work in several key aspects: (1) interpretable - it quantitatively interprets DNNs' fairness violations for the biased decision; (2) effective - it uses the interpretation results to guide the generation of more diverse instances in less time; (3) generic - it can handle both structured and unstructured data.


NIP: Neuron-level Inverse Perturbation Against Adversarial Attacks

no code implementations24 Dec 2021 Ruoxi Chen, Haibo Jin, Jinyin Chen, Haibin Zheng, Yue Yu, Shouling Ji

From the perspective of image feature space, some of them cannot reach satisfying results due to the shift of features.

CatchBackdoor: Backdoor Testing by Critical Trojan Neural Path Identification via Differential Fuzzing

no code implementations24 Dec 2021 Haibo Jin, Ruoxi Chen, Jinyin Chen, Yao Cheng, Chong Fu, Ting Wang, Yue Yu, Zhaoyan Ming

Existing DNN testing methods are mainly designed to find incorrect corner case behaviors in adversarial settings but fail to discover the backdoors crafted by strong trojan attacks.

DNN Testing

A revised comparison between FF five-factor model and three-factor model,based on China's A-share market

no code implementations16 Oct 2021 Zhijing Zhang, Yue Yu, Qinghua Ma, Haixiang Yao

In allusion to some contradicting results in existing research, this paper selects China's latest stock data from 2005 to 2020 for empirical analysis.


WRENCH: A Comprehensive Benchmark for Weak Supervision

1 code implementation23 Sep 2021 Jieyu Zhang, Yue Yu, Yinghao Li, Yujing Wang, Yaming Yang, Mao Yang, Alexander Ratner

To address these problems, we introduce a benchmark platform, WRENCH, for thorough and standardized evaluation of WS approaches.

Self-Training with Differentiable Teacher

no code implementations Findings (NAACL) 2022 Simiao Zuo, Yue Yu, Chen Liang, Haoming Jiang, Siawpeng Er, Chao Zhang, Tuo Zhao, Hongyuan Zha

In self-training, the student contributes to the prediction performance, and the teacher controls the training process by generating pseudo-labels.

named-entity-recognition Named Entity Recognition +3

A physics-informed variational DeepONet for predicting the crack path in brittle materials

no code implementations16 Aug 2021 Somdatta Goswami, Minglang Yin, Yue Yu, George Karniadakis

We propose a physics-informed variational formulation of DeepONet (V-DeepONet) for brittle fracture analysis.

Advances in Trajectory Optimization for Space Vehicle Control

1 code implementation5 Aug 2021 Danylo Malyuta, Yue Yu, Purnanand Elango, Behcet Acikmese

Space mission design places a premium on cost and operational efficiency.

A data-driven peridynamic continuum model for upscaling molecular dynamics

no code implementations4 Aug 2021 Huaiqian You, Yue Yu, Stewart Silling, Marta D'Elia

Nonlocal models, including peridynamics, often use integral operators that embed lengthscales in their definition.

GGT: Graph-Guided Testing for Adversarial Sample Detection of Deep Neural Network

no code implementations9 Jul 2021 Zuohui Chen, Renxuan Wang, Jingyang Xiang, Yue Yu, Xin Xia, Shouling Ji, Qi Xuan, Xiaoniu Yang

Deep Neural Networks (DNN) are known to be vulnerable to adversarial samples, the detection of which is crucial for the wide application of these DNN models.

DAGs with No Curl: An Efficient DAG Structure Learning Approach

1 code implementation14 Jun 2021 Yue Yu, Tian Gao, Naiyu Yin, Qiang Ji

To further improve efficiency, we propose a novel learning framework to model and learn the weighted adjacency matrices in the DAG space directly.

deGraphCS: Embedding Variable-based Flow Graph for Neural Code Search

1 code implementation24 Mar 2021 Chen Zeng, Yue Yu, Shanshan Li, Xin Xia, Zhiming Wang, Mingyang Geng, Bailin Xiao, Wei Dong, Xiangke Liao

With the rapid increase in the amount of public code repositories, developers maintain a great desire to retrieve precise code snippets by using natural language.

Code Search

On Controllability and Persistency of Excitation in Data-Driven Control: Extensions of Willems' Fundamental Lemma

no code implementations5 Feb 2021 Yue Yu, Shahriar Talebi, Henk J. van Waarde, Ufuk Topcu, Mehran Mesbahi, Behçet Açıkmeşe

Willems' fundamental lemma asserts that all trajectories of a linear time-invariant system can be obtained from a finite number of measured ones, assuming that controllability and a persistency of excitation condition hold.


An asymptotically compatible treatment of traction loading in linearly elastic peridynamic fracture

no code implementations5 Jan 2021 Yue Yu, Huaiqian You, Nathaniel Trask

In the absence of fracture, when a corresponding classical continuum mechanics model exists, our improvements provide asymptotically compatible convergence to corresponding local solutions, eliminating surface effects and issues with traction loading which have historically plagued peridynamic discretizations.

Numerical Analysis Computational Engineering, Finance, and Science Numerical Analysis Analysis of PDEs

Data-driven learning of nonlocal models: from high-fidelity simulations to constitutive laws

no code implementations8 Dec 2020 Huaiqian You, Yue Yu, Stewart Silling, Marta D'Elia

We show that machine learning can improve the accuracy of simulations of stress waves in one-dimensional composite materials.

DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks

1 code implementation NeurIPS 2020 Dennis Wei, Tian Gao, Yue Yu

This paper re-examines a continuous optimization framework dubbed NOTEARS for learning Bayesian networks.

MCMH: Learning Multi-Chain Multi-Hop Rules for Knowledge Graph Reasoning

no code implementations Findings of the Association for Computational Linguistics 2020 Lu Zhang, Mo Yu, Tian Gao, Yue Yu

Multi-hop reasoning approaches over knowledge graphs infer a missing relationship between entities with a multi-hop rule, which corresponds to a chain of relationships.

Knowledge Graphs

SeqMix: Augmenting Active Sequence Labeling via Sequence Mixup

1 code implementation EMNLP 2020 Rongzhi Zhang, Yue Yu, Chao Zhang

Our method, SeqMix, simply augments the queried samples by generating extra labeled sequences in each iteration.

Active Learning Data Augmentation +4

SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization

1 code implementation4 Oct 2020 Yue Yu, Kexin Huang, Chao Zhang, Lucas M. Glass, Jimeng Sun, Cao Xiao

Furthermore, most previous works focus on binary DDI prediction whereas the multi-typed DDI pharmacological effect prediction is a more meaningful but harder task.

Data Integration Knowledge Graphs

STEAM: Self-Supervised Taxonomy Expansion with Mini-Paths

1 code implementation18 Jun 2020 Yue Yu, Yinghao Li, Jiaming Shen, Hao Feng, Jimeng Sun, Chao Zhang

We propose a self-supervised taxonomy expansion model named STEAM, which leverages natural supervision in the existing taxonomy for expansion.

Taxonomy Expansion

Data-driven learning of robust nonlocal physics from high-fidelity synthetic data

no code implementations17 May 2020 Huaiqian You, Yue Yu, Nathaniel Trask, Mamikon Gulian, Marta D'Elia

A key challenge to nonlocal models is the analytical complexity of deriving them from first principles, and frequently their use is justified a posteriori.

Urban Anomaly Analytics: Description, Detection, and Prediction

no code implementations25 Apr 2020 Mingyang Zhang, Tong Li, Yue Yu, Yong Li, Pan Hui, Yu Zheng

Urban anomalies may result in loss of life or property if not handled properly.

SPAN: A Stochastic Projected Approximate Newton Method

no code implementations10 Feb 2020 Xunpeng Huang, Xianfeng Liang, Zhengyang Liu, Yitan Li, Linyun Yu, Yue Yu, Lei LI

SPAN computes the inverse of the Hessian matrix via low-rank approximation and stochastic Hessian-vector products.

Acutum: When Generalization Meets Adaptability

no code implementations25 Sep 2019 Xunpeng Huang, Zhengyang Liu, Zhe Wang, Yue Yu, Lei LI

To the best of our knowledge, Acutum is the first adaptive gradient method without second moments.

BIG-bench Machine Learning

Modeling Long-Range Context for Concurrent Dialogue Acts Recognition

no code implementations2 Sep 2019 Yue Yu, Siyao Peng, Grace Hui Yang

Previous work on DA recognition either assumes one DA per utterance or fails to realize the sequential nature of dialogues.

DAG-GNN: DAG Structure Learning with Graph Neural Networks

3 code implementations22 Apr 2019 Yue Yu, Jie Chen, Tian Gao, Mo Yu

Learning a faithful directed acyclic graph (DAG) from samples of a joint distribution is a challenging combinatorial problem, owing to the intractable search space superexponential in the number of graph nodes.

Characterizing Malicious Edges targeting on Graph Neural Networks

no code implementations27 Sep 2018 Xiaojun Xu, Yue Yu, Bo Li, Le Song, Chengfeng Liu, Carl Gunter

Extensive experiments are conducted to show that the proposed detection mechanism can achieve AUC above 90% against the two attack strategies on both Cora and Citeseer datasets.

Graph Generation Link Prediction +1

Double Quantization for Communication-Efficient Distributed Optimization

no code implementations NeurIPS 2019 Yue Yu, Jiaxiang Wu, Longbo Huang

In this paper, to reduce the communication complexity, we propose \emph{double quantization}, a general scheme for quantizing both model parameters and gradients.

Distributed Optimization Quantization

Aurora: Providing Trusted System Services for Enclaves On an Untrusted System

1 code implementation10 Feb 2018 Hongliang Liang, Mingyu Li, Qiong Zhang, Yue Yu, Lin Jiang, Yixiu Chen

Intel SGX provisions shielded executions for security-sensitive computation, but lacks support for trusted system services (TSS), such as clock, network and filesystem.

Cryptography and Security

Optimal Cooperative Inference

no code implementations24 May 2017 Scott Cheng-Hsin Yang, Yue Yu, Arash Givchi, Pei Wang, Wai Keen Vong, Patrick Shafto

Cooperative transmission of data fosters rapid accumulation of knowledge by efficiently combining experiences across learners.

BIG-bench Machine Learning

Fast Stochastic Variance Reduced ADMM for Stochastic Composition Optimization

no code implementations11 May 2017 Yue Yu, Longbo Huang

We consider the stochastic composition optimization problem proposed in \cite{wang2017stochastic}, which has applications ranging from estimation to statistical and machine learning.

BIG-bench Machine Learning

A Mandarin-English Code-Switching Corpus

no code implementations LREC 2012 Ying Li, Yue Yu, Pascale Fung

Generally the existing monolingual corpora are not suitable for large vocabulary continuous speech recognition (LVCSR) of code-switching speech.

Boundary Detection Language Identification +3

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