Search Results for author: Yuan Tian

Found 52 papers, 20 papers with code

PLUE: Language Understanding Evaluation Benchmark for Privacy Policies in English

no code implementations20 Dec 2022 Jianfeng Chi, Wasi Uddin Ahmad, Yuan Tian, Kai-Wei Chang

To this end, we introduce the Privacy Policy Language Understanding Evaluation (PLUE) benchmark, a multi-task benchmark for evaluating the privacy policy language understanding across various tasks.

Language Modelling Natural Language Understanding

FastClass: A Time-Efficient Approach to Weakly-Supervised Text Classification

1 code implementation11 Dec 2022 Tingyu Xia, Yue Wang, Yuan Tian, Yi Chang

Weakly-supervised text classification aims to train a classifier using only class descriptions and unlabeled data.

text-classification Text Classification +1

Conditional Supervised Contrastive Learning for Fair Text Classification

1 code implementation23 May 2022 Jianfeng Chi, William Shand, Yaodong Yu, Kai-Wei Chang, Han Zhao, Yuan Tian

Contrastive representation learning has gained much attention due to its superior performance in learning representations from both image and sequential data.

Contrastive Learning Fairness +3

CNN-Augmented Visual-Inertial SLAM with Planar Constraints

no code implementations5 May 2022 Pan Ji, Yuan Tian, Qingan Yan, Yuxin Ma, Yi Xu

The CNN depth effectively bootstraps the back-end optimization of SLAM and meanwhile the CNN uncertainty adaptively weighs the contribution of each feature point to the back-end optimization.

FisheyeDistill: Self-Supervised Monocular Depth Estimation with Ordinal Distillation for Fisheye Cameras

no code implementations5 May 2022 Qingan Yan, Pan Ji, Nitin Bansal, Yuxin Ma, Yuan Tian, Yi Xu

In this paper, we deal with the problem of monocular depth estimation for fisheye cameras in a self-supervised manner.

Monocular Depth Estimation

Retrieval Enhanced Data Augmentation for Question Answering on Privacy Policies

no code implementations19 Apr 2022 Md Rizwan Parvez, Jianfeng Chi, Wasi Uddin Ahmad, Yuan Tian, Kai-Wei Chang

Prior studies in privacy policies frame the question answering (QA) tasks as identifying the most relevant text segment or a list of sentences from the policy document for a user query.

Data Augmentation Question Answering +1

Multi-agent Actor-Critic with Time Dynamical Opponent Model

no code implementations12 Apr 2022 Yuan Tian, Klaus-Rudolf Kladny, Qin Wang, Zhiwu Huang, Olga Fink

In this paper, we propose to exploit the fact that the agents seek to improve their expected cumulative reward and introduce a novel \textit{Time Dynamical Opponent Model} (TDOM) to encode the knowledge that the opponent policies tend to improve over time.

Multi-agent Reinforcement Learning

A Coding Framework and Benchmark towards Compressed Video Understanding

no code implementations6 Feb 2022 Yuan Tian, Guo Lu, Yichao Yan, Guangtao Zhai, Li Chen, Zhiyong Gao

However, in real-world scenarios, the videos are first compressed before the transportation and then decompressed for understanding.

Video Understanding

A Prescriptive Dirichlet Power Allocation Policy with Deep Reinforcement Learning

no code implementations20 Jan 2022 Yuan Tian, Minghao Han, Chetan Kulkarni, Olga Fink

Moreover, we demonstrate the applicability of the proposed algorithm on a prescriptive operation case, where we propose the Dirichlet power allocation policy and evaluate the performance on a case study of a set of multiple lithium-ion (Li-I) battery systems.

reinforcement-learning Reinforcement Learning (RL)

Towards Return Parity in Markov Decision Processes

1 code implementation19 Nov 2021 Jianfeng Chi, Jian Shen, Xinyi Dai, Weinan Zhang, Yuan Tian, Han Zhao

We first provide a decomposition theorem for return disparity, which decomposes the return disparity of any two MDPs sharing the same state and action spaces into the distance between group-wise reward functions, the discrepancy of group policies, and the discrepancy between state visitation distributions induced by the group policies.

Fairness Recommendation Systems

Automated Detection of GDPR Disclosure Requirements in Privacy Policies using Deep Active Learning

no code implementations8 Nov 2021 Tamjid Al Rahat, Tu Le, Yuan Tian

Since GDPR came into force in May 2018, companies have worked on their data practices to comply with this privacy law.

Active Learning

AnANet: Modeling Association and Alignment for Cross-modal Correlation Classification

no code implementations2 Sep 2021 Nan Xu, Junyan Wang, Yuan Tian, Ruike Zhang, Wenji Mao

Thus researchers study the definition of cross-modal correlation category and construct various classification systems and predictive models.

Association Classification

Self-Conditioned Probabilistic Learning of Video Rescaling

1 code implementation ICCV 2021 Yuan Tian, Guo Lu, Xiongkuo Min, Zhaohui Che, Guangtao Zhai, Guodong Guo, Zhiyong Gao

After optimization, the downscaled video by our framework preserves more meaningful information, which is beneficial for both the upscaling step and the downstream tasks, e. g., video action recognition task.

Video Compression Video Super-Resolution

EAN: Event Adaptive Network for Enhanced Action Recognition

1 code implementation22 Jul 2021 Yuan Tian, Yichao Yan, Guangtao Zhai, Guodong Guo, Zhiyong Gao

In this paper, we propose a unified action recognition framework to investigate the dynamic nature of video content by introducing the following designs.

Action Recognition

What and How long: Prediction of Mobile App Engagement

no code implementations2 Jun 2021 Yuan Tian, Ke Zhou, Dan Pelleg

Based on the analysis, we further investigate a novel mobile app engagement prediction problem -- can we predict simultaneously what app the user will use next and how long he/she will stay on that app?

CryptGPU: Fast Privacy-Preserving Machine Learning on the GPU

1 code implementation22 Apr 2021 Sijun Tan, Brian Knott, Yuan Tian, David J. Wu

We then identify a sequence of "GPU-friendly" cryptographic protocols to enable privacy-preserving evaluation of both linear and non-linear operations on the GPU.

BIG-bench Machine Learning Privacy Preserving +1

Understanding and Mitigating Accuracy Disparity in Regression

1 code implementation24 Feb 2021 Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon, Han Zhao

With the widespread deployment of large-scale prediction systems in high-stakes domains, e. g., face recognition, criminal justice, etc., disparity in prediction accuracy between different demographic subgroups has called for fundamental understanding on the source of such disparity and algorithmic intervention to mitigate it.

Face Recognition regression

Using Prior Knowledge to Guide BERT's Attention in Semantic Textual Matching Tasks

1 code implementation22 Feb 2021 Tingyu Xia, Yue Wang, Yuan Tian, Yi Chang

We study the problem of incorporating prior knowledge into a deep Transformer-based model, i. e., Bidirectional Encoder Representations from Transformers (BERT), to enhance its performance on semantic textual matching tasks.

Meta Federated Learning

no code implementations10 Feb 2021 Omid Aramoon, Pin-Yu Chen, Gang Qu, Yuan Tian

Due to its distributed methodology alongside its privacy-preserving features, Federated Learning (FL) is vulnerable to training time adversarial attacks.

Federated Learning Privacy Preserving

SkillBot: Identifying Risky Content for Children in Alexa Skills

no code implementations5 Feb 2021 Tu Le, Danny Yuxing Huang, Noah Apthorpe, Yuan Tian

Finally, we identify a novel risk in the VPA ecosystem: confounding utterances, or voice commands shared by multiple apps that may cause a user to interact with a different app than intended.

Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning

no code implementations1 Feb 2021 Syed Zawad, Ahsan Ali, Pin-Yu Chen, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Yuan Tian, Feng Yan

Data heterogeneity has been identified as one of the key features in federated learning but often overlooked in the lens of robustness to adversarial attacks.

Federated Learning

Intent Classification and Slot Filling for Privacy Policies

1 code implementation ACL 2021 Wasi Uddin Ahmad, Jianfeng Chi, Tu Le, Thomas Norton, Yuan Tian, Kai-Wei Chang

We refer to predicting the privacy practice explained in a sentence as intent classification and identifying the text spans sharing specific information as slot filling.

General Classification intent-classification +2

Battery Model Calibration with Deep Reinforcement Learning

no code implementations7 Dec 2020 Ajaykumar Unagar, Yuan Tian, Manuel Arias-Chao, Olga Fink

In this paper, we implement a Reinforcement Learning-based framework for reliably and efficiently inferring calibration parameters of battery models.

BIG-bench Machine Learning reinforcement-learning +1

ToHRE: A Top-Down Classification Strategy with Hierarchical Bag Representation for Distantly Supervised Relation Extraction

no code implementations COLING 2020 Erxin Yu, Wenjuan Han, Yuan Tian, Yi Chang

Distantly Supervised Relation Extraction (DSRE) has proven to be effective to find relational facts from texts, but it still suffers from two main problems: the wrong labeling problem and the long-tail problem.

Classification Relation Extraction

PolicyQA: A Reading Comprehension Dataset for Privacy Policies

1 code implementation Findings of the Association for Computational Linguistics 2020 Wasi Uddin Ahmad, Jianfeng Chi, Yuan Tian, Kai-Wei Chang

Prior studies in this domain frame the QA task as retrieving the most relevant text segment or a list of sentences from the policy document given a question.

Question Answering Reading Comprehension

Dual-path CNN with Max Gated block for Text-Based Person Re-identification

1 code implementation20 Sep 2020 Tinghuai Ma, Mingming Yang, Huan Rong, Yurong Qian, Yuan Tian, NajlaAl-Nabhan

With that in mind, a novel Dual-path CNN with Max Gated block (DCMG) is proposed to extract discriminative word embeddings and make visual-textual association concern more on remarkable features of both modalities.

Association Language Modelling +2

Object Detection in the Context of Mobile Augmented Reality

no code implementations15 Aug 2020 Xiang Li, Yuan Tian, Fuyao Zhang, Shuxue Quan, Yi Xu

Ordinary object detection approaches process information from the images only, and they are oblivious to the camera pose with regard to the environment and the scale of the environment.

object-detection Real-Time Object Detection

Perceptron Synthesis Network: Rethinking the Action Scale Variances in Videos

no code implementations22 Jul 2020 Yuan Tian, Guangtao Zhai, Zhiyong Gao

More specifically, an \textit{action perceptron synthesizer} is proposed to generate the kernels from a bag of fixed-size kernels that are interacted by dense routing paths.

Action Recognition Temporal Action Localization +1

Off-Policy Reinforcement Learning for Efficient and Effective GAN Architecture Search

1 code implementation ECCV 2020 Yuan Tian, Qin Wang, Zhiwu Huang, Wen Li, Dengxin Dai, Minghao Yang, Jun Wang, Olga Fink

In this paper, we introduce a new reinforcement learning (RL) based neural architecture search (NAS) methodology for effective and efficient generative adversarial network (GAN) architecture search.

Image Generation Neural Architecture Search +2

Model-Targeted Poisoning Attacks with Provable Convergence

1 code implementation30 Jun 2020 Fnu Suya, Saeed Mahloujifar, Anshuman Suri, David Evans, Yuan Tian

Our attack is the first model-targeted poisoning attack that provides provable convergence for convex models, and in our experiments, it either exceeds or matches state-of-the-art attacks in terms of attack success rate and distance to the target model.

Real-Time Model Calibration with Deep Reinforcement Learning

no code implementations7 Jun 2020 Yuan Tian, Manuel Arias Chao, Chetan Kulkarni, Kai Goebel, Olga Fink

The dynamic, real-time, and accurate inference of model parameters from empirical data is of great importance in many scientific and engineering disciplines that use computational models (such as a digital twin) for the analysis and prediction of complex physical processes.

reinforcement-learning Reinforcement Learning (RL)

GraphLIME: Local Interpretable Model Explanations for Graph Neural Networks

2 code implementations17 Jan 2020 Qiang Huang, Makoto Yamada, Yuan Tian, Dinesh Singh, Dawei Yin, Yi Chang

In this paper, we propose GraphLIME, a local interpretable model explanation for graphs using the Hilbert-Schmidt Independence Criterion (HSIC) Lasso, which is a nonlinear feature selection method.

$H_\infty$ Model-free Reinforcement Learning with Robust Stability Guarantee

1 code implementation7 Nov 2019 Minghao Han, Yuan Tian, Lixian Zhang, Jun Wang, Wei Pan

In this paper, we introduce and extend the idea of robust stability and $H_\infty$ control to design policies with both stability and robustness guarantee.

Autonomous Driving reinforcement-learning +2

Convex Reconstruction of Structured Matrix Signals from Linear Measurements (I): Theoretical Results

no code implementations19 Oct 2019 Yuan Tian

The first part is about conditions for stability and robustness in signal reconstruction via solving the convex programming from noise-free or noisy measurements. We establish uniform sufficient conditions which are very close to necessary conditions and non-uniform conditions are also discussed.

Compressive Sensing

Model-free Learning Control of Nonlinear Stochastic Systems with Stability Guarantee

no code implementations25 Sep 2019 Minghao Han, Yuan Tian, Lixian Zhang, Jun Wang, Wei Pan

Reinforcement learning (RL) offers a principled way to achieve the optimal cumulative performance index in discrete-time nonlinear stochastic systems, which are modeled as Markov decision processes.

Continuous Control Reinforcement Learning (RL)

Adversarial Privacy Preservation under Attribute Inference Attack

no code implementations25 Sep 2019 Han Zhao, Jianfeng Chi, Yuan Tian, Geoffrey J. Gordon

With the prevalence of machine learning services, crowdsourced data containing sensitive information poses substantial privacy challenges.

Inference Attack Representation Learning

Variational Constrained Reinforcement Learning with Application to Planning at Roundabout

no code implementations25 Sep 2019 Yuan Tian, Minghao Han, Lixian Zhang, Wulong Liu, Jun Wang, Wei Pan

In this paper, we combine variational learning and constrained reinforcement learning to simultaneously learn a Conditional Representation Model (CRM) to encode the states into safe and unsafe distributions respectively as well as to learn the corresponding safe policy.

Autonomous Driving reinforcement-learning +1

Jointly Modeling Hierarchical and Horizontal Features for Relational Triple Extraction

no code implementations23 Aug 2019 Zhepei Wei, Yantao Jia, Yuan Tian, Mohammad Javad Hosseini, Sujian Li, Mark Steedman, Yi Chang

In this work, we first introduce the hierarchical dependency and horizontal commonality between the two levels, and then propose an entity-enhanced dual tagging framework that enables the triple extraction (TE) task to utilize such interactions with self-learned entity features through an auxiliary entity extraction (EE) task, without breaking the joint decoding of relational triples.

Entity Extraction using GAN graph construction +2

Hybrid Batch Attacks: Finding Black-box Adversarial Examples with Limited Queries

1 code implementation19 Aug 2019 Fnu Suya, Jianfeng Chi, David Evans, Yuan Tian

In a black-box setting, the adversary only has API access to the target model and each query is expensive.

Cryptography and Security

PatchNet: A Tool for Deep Patch Classification

1 code implementation16 Feb 2019 Thong Hoang, Julia Lawall, Richard J. Oentaryo, Yuan Tian, David Lo

This work proposes PatchNet, an automated tool based on hierarchical deep learning for classifying patches by extracting features from commit messages and code changes.

Classification General Classification

Privacy Partitioning: Protecting User Data During the Deep Learning Inference Phase

no code implementations7 Dec 2018 Jianfeng Chi, Emmanuel Owusu, Xuwang Yin, Tong Yu, William Chan, Patrick Tague, Yuan Tian

We present a practical method for protecting data during the inference phase of deep learning based on bipartite topology threat modeling and an interactive adversarial deep network construction.

BIG-bench Machine Learning Face Identification +1

Understanding and Mitigating the Security Risks of Voice-Controlled Third-Party Skills on Amazon Alexa and Google Home

no code implementations3 May 2018 Nan Zhang, Xianghang Mi, Xuan Feng, Xiao-Feng Wang, Yuan Tian, Feng Qian

The significance of our findings have already been acknowledged by Amazon and Google, and further evidenced by the risky skills discovered on Alexa and Google markets by the new detection systems we built.

Cryptography and Security

Query-limited Black-box Attacks to Classifiers

1 code implementation23 Dec 2017 Fnu Suya, Yuan Tian, David Evans, Paolo Papotti

Specifically, we consider the problem of attacking machine learning classifiers subject to a budget of feature modification cost while minimizing the number of queries, where each query returns only a class and confidence score.

BIG-bench Machine Learning

WebAPIRec: Recommending Web APIs to Software Projects via Personalized Ranking

no code implementations1 May 2017 Ferdian Thung, Richard J. Oentaryo, David Lo, Yuan Tian

In this light, we propose a new, automated approach called WebAPIRec that takes as input a project profile and outputs a ranked list of {web} APIs that can be used to implement the project.

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