Search Results for author: Ye Tian

Found 62 papers, 17 papers with code

How does BERT process disfluency?

no code implementations SIGDIAL (ACL) 2021 Ye Tian, Tim Nieradzik, Sepehr Jalali, Da-Shan Shiu

Analysis on sentence embeddings of disfluent and fluent sentence pairs reveals that the deeper the layer, the more similar their representation (exp2).

Sentence Embeddings

On semi-supervised estimation using exponential tilt mixture models

no code implementations14 Nov 2023 Ye Tian, Xinwei Zhang, Zhiqiang Tan

Consider a semi-supervised setting with a labeled dataset of binary responses and predictors and an unlabeled dataset with only the predictors.


Learning From Free-Text Human Feedback -- Collect New Datasets Or Extend Existing Ones?

1 code implementation24 Oct 2023 Dominic Petrak, Nafise Sadat Moosavi, Ye Tian, Nikolai Rozanov, Iryna Gurevych

Learning from free-text human feedback is essential for dialog systems, but annotated data is scarce and usually covers only a small fraction of error types known in conversational AI.

Chatbot Response Generation +1

Unsupervised Federated Learning: A Federated Gradient EM Algorithm for Heterogeneous Mixture Models with Robustness against Adversarial Attacks

no code implementations23 Oct 2023 Ye Tian, Haolei Weng, Yang Feng

While supervised federated learning approaches have enjoyed significant success, the domain of unsupervised federated learning remains relatively underexplored.

Federated Learning

Evolutionary Neural Architecture Search for Transformer in Knowledge Tracing

1 code implementation2 Oct 2023 Shangshang Yang, Xiaoshan Yu, Ye Tian, Xueming Yan, Haiping Ma, Xingyi Zhang

Knowledge tracing (KT) aims to trace students' knowledge states by predicting whether students answer correctly on exercises.

Stabilizing RLHF through Advantage Model and Selective Rehearsal

no code implementations18 Sep 2023 Baolin Peng, Linfeng Song, Ye Tian, Lifeng Jin, Haitao Mi, Dong Yu

Large Language Models (LLMs) have revolutionized natural language processing, yet aligning these models with human values and preferences using RLHF remains a significant challenge.

EQ-Net: Elastic Quantization Neural Networks

1 code implementation ICCV 2023 Ke Xu, Lei Han, Ye Tian, Shangshang Yang, Xingyi Zhang

In this paper, we explore a one-shot network quantization regime, named Elastic Quantization Neural Networks (EQ-Net), which aims to train a robust weight-sharing quantization supernet.


View while Moving: Efficient Video Recognition in Long-untrimmed Videos

no code implementations9 Aug 2023 Ye Tian, Mengyu Yang, Lanshan Zhang, Zhizhen Zhang, Yang Liu, Xiaohui Xie, Xirong Que, Wendong Wang

To this end, inspired by human cognition, we propose a novel recognition paradigm of "View while Moving" for efficient long-untrimmed video recognition.

Video Recognition

VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs

1 code implementation4 Aug 2023 Ling Yang, Ye Tian, Minkai Xu, Zhongyi Liu, Shenda Hong, Wei Qu, Wentao Zhang, Bin Cui, Muhan Zhang, Jure Leskovec

To address this issue, we propose to learn a new powerful graph representation space by directly labeling nodes' diverse local structures for GNN-to-MLP distillation.

Knowledge Distillation Quantization +1

Improving Social Media Popularity Prediction with Multiple Post Dependencies

no code implementations28 Jul 2023 Zhizhen Zhang, Xiaohui Xie, Mengyu Yang, Ye Tian, Yong Jiang, Yong Cui

Social Media Popularity Prediction has drawn a lot of attention because of its profound impact on many different applications, such as recommendation systems and multimedia advertising.

Recommendation Systems Social Media Popularity Prediction

Robust Fully-Asynchronous Methods for Distributed Training over General Architecture

no code implementations21 Jul 2023 Zehan Zhu, Ye Tian, Yan Huang, Jinming Xu, Shibo He

Perfect synchronization in distributed machine learning problems is inefficient and even impossible due to the existence of latency, package losses and stragglers.

Designing Novel Cognitive Diagnosis Models via Evolutionary Multi-Objective Neural Architecture Search

1 code implementation10 Jul 2023 Shangshang Yang, Haiping Ma, Cheng Zhen, Ye Tian, Limiao Zhang, Yaochu Jin, Xingyi Zhang

Then, we propose multi-objective genetic programming (MOGP) to explore the NAS task's search space by maximizing model performance and interpretability.

Neural Architecture Search

RestGPT: Connecting Large Language Models with Real-World RESTful APIs

no code implementations11 Jun 2023 YiFan Song, Weimin Xiong, Dawei Zhu, Wenhao Wu, Han Qian, Mingbo Song, Hailiang Huang, Cheng Li, Ke Wang, Rong Yao, Ye Tian, Sujian Li

To address the practical challenges of tackling complex instructions, we propose RestGPT, which exploits the power of LLMs and conducts a coarse-to-fine online planning mechanism to enhance the abilities of task decomposition and API selection.

Coordinated Frequency-Constrained Stochastic Economic Dispatch for Integrated Transmission and Distribution System via Distributed Optimization

no code implementations19 May 2023 Ye Tian, Zhengshuo Li

TPS and ADNs can deliver base point power bidirectionally and provide frequency regulation support bidirectionally, which extend the existing reserve assumption in ITD dispatch and enhance the operational security of the ITD system.

Distributed Optimization

Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness

1 code implementation31 Mar 2023 Ye Tian, Yuqi Gu, Yang Feng

With a known intrinsic dimension, we propose two algorithms that are \textit{adaptive} to the similarity structure and \textit{robust} to outlier tasks under both MTL and TL settings.

Multi-Task Learning

Joint Chance-Constrained Economic Dispatch Involving Joint Optimization of Frequency-related Inverter Control and Regulation Reserve Allocation

no code implementations7 Mar 2023 Ye Tian, Zhengshuo Li, Wenchuan Wu, Miao Fan

The issues of uncertainty and frequency security could become significantly serious in power systems with the high penetration of volatile inverter-based renewables (IBRs).

Deep Maxout Network Gaussian Process

no code implementations8 Aug 2022 Libin Liang, Ye Tian, Ge Cheng

Study of neural networks with infinite width is important for better understanding of the neural network in practical application.

Bayesian Inference

Semi-supervised Ranking for Object Image Blur Assessment

1 code implementation13 Jul 2022 Qiang Li, Zhaoliang Yao, Jingjing Wang, Ye Tian, Pengju Yang, Di Xie, ShiLiang Pu

Based on this dataset, we propose a method to obtain the blur scores only with the pairwise rank labels as supervision.

Object Recognition Retrieval

Detecting Schizophrenia with 3D Structural Brain MRI Using Deep Learning

no code implementations26 Jun 2022 Junhao Zhang, Vishwanatha M. Rao, Ye Tian, Yanting Yang, Nicolas Acosta, Zihan Wan, Pin-Yu Lee, Chloe Zhang, Lawrence S. Kegeles, Scott A. Small, Jia Guo

Our finding corroborates that schizophrenia is associated with widespread alterations in subcortical brain structure and the subcortical structural information provides prominent features in diagnostic classification.

Improving Across-Dataset Brain Tissue Segmentation Using Transformer

1 code implementation21 Jan 2022 Vishwanatha M. Rao, Zihan Wan, Soroush Arabshahi, David J. Ma, Pin-Yu Lee, Ye Tian, Xuzhe Zhang, Andrew F. Laine, Jia Guo

Transformers have demonstrated success in natural image segmentation and have recently been applied to 3D medical image segmentation tasks due to their ability to capture long-distance relationships in the input where the local receptive fields of CNNs struggle.

Image Segmentation Medical Image Segmentation +2

Neyman-Pearson Multi-class Classification via Cost-sensitive Learning

no code implementations8 Nov 2021 Ye Tian, Yang Feng

In this work, we study the multi-class NP problem by connecting it to the CS problem and propose two algorithms.

Classification Multi-class Classification

Acceleration in Distributed Optimization under Similarity

no code implementations24 Oct 2021 Ye Tian, Gesualdo Scutari, Tianyu Cao, Alexander Gasnikov

In order to reduce the number of communications to reach a solution accuracy, we proposed a {\it preconditioned, accelerated} distributed method.

Distributed Optimization

Accelerating Evolutionary Neural Architecture Search via Multi-Fidelity Evaluation

1 code implementation10 Aug 2021 Shangshang Yang, Ye Tian, Xiaoshu Xiang, Shichen Peng, Xingyi Zhang

Evolutionary neural architecture search (ENAS) has recently received increasing attention by effectively finding high-quality neural architectures, which however consumes high computational cost by training the architecture encoded by each individual for complete epochs in individual evaluation.

Neural Architecture Search

Transfer Learning under High-dimensional Generalized Linear Models

no code implementations29 May 2021 Ye Tian, Yang Feng

In this work, we study the transfer learning problem under high-dimensional generalized linear models (GLMs), which aim to improve the fit on target data by borrowing information from useful source data.

Transfer Learning Vocal Bursts Intensity Prediction

Principled Design of Translation, Scale, and Rotation Invariant Variation Operators for Metaheuristics

no code implementations22 May 2021 Ye Tian, Xingyi Zhang, Cheng He, Kay Chen Tan, Yaochu Jin

In the past three decades, a large number of metaheuristics have been proposed and shown high performance in solving complex optimization problems.


Towards a Universal NLG for Dialogue Systems and Simulators with Future Bridging

no code implementations21 May 2021 Philipp Ennen, Yen-Ting Lin, Ali Girayhan Ozbay, Ferdinando Insalata, Maolin Li, Ye Tian, Sepehr Jalali, Da-Shan Shiu

In light of the recent success of data-driven approaches, we propose the novel future bridging NLG (FBNLG) concept for dialogue systems and simulators.

Text Generation

AppealNet: An Efficient and Highly-Accurate Edge/Cloud Collaborative Architecture for DNN Inference

no code implementations10 May 2021 Min Li, Yu Li, Ye Tian, Li Jiang, Qiang Xu

This paper presents AppealNet, a novel edge/cloud collaborative architecture that runs deep learning (DL) tasks more efficiently than state-of-the-art solutions.

Image Classification

Evaluating the Effect of Longitudinal Dose and INR Data on Maintenance Warfarin Dose Predictions

no code implementations6 May 2021 Anish Karpurapu, Adam Krekorian, Ye Tian, Leslie M. Collins, Ravi Karra, Aaron Franklin, Boyla O. Mainsah

Since a sequence of prior doses and INR better capture the variability in individual warfarin response, we hypothesized that longitudinal dose response data will improve maintenance dose predictions.

RaSE: A Variable Screening Framework via Random Subspace Ensembles

1 code implementation7 Feb 2021 Ye Tian, Yang Feng

Variable screening methods have been shown to be effective in dimension reduction under the ultra-high dimensional setting.

Dimensionality Reduction

Imaging vibrations of locally gated, electromechanical few layer graphene resonators with a moving vacuum enclosure

no code implementations4 Jan 2021 Heng Lu, Chen Yang, Ye Tian, Jun Lu, Fanqi Xu, FengNan Chen, Yan Ying, Kevin G. Schädler, Chinhua Wang, Frank H. L. Koppens, Antoine Reserbat-Plantey, Joel Moser

With it we characterize the lowest frequency mode of a FLG resonator by measuring its frequency response as a function of position on the membrane.

Mesoscale and Nanoscale Physics

A Multilayer Correlated Topic Model

no code implementations2 Jan 2021 Ye Tian

We proposed a novel multilayer correlated topic model (MCTM) to analyze how the main ideas inherit and vary between a document and its different segments, which helps understand an article's structure.

Model agnostic meta-learning on trees

no code implementations1 Jan 2021 Jezabel Garcia, Federica Freddi, Jamie McGowan, Tim Nieradzik, Da-Shan Shiu, Ye Tian, Alberto Bernacchia

In meta-learning, the knowledge learned from previous tasks is transferred to new ones, but this transfer only works if tasks are related, and sharing information between unrelated tasks might hurt performance.


DeepDyve: Dynamic Verification for Deep Neural Networks

no code implementations21 Sep 2020 Yu Li, Min Li, Bo Luo, Ye Tian, Qiang Xu

The key to enabling such lightweight checking is that the smaller neural network only needs to produce approximate results for the initial task without sacrificing fault coverage much.

Autonomous Driving

AMRNet: Chips Augmentation in Aerial Images Object Detection

no code implementations15 Sep 2020 Zhiwei Wei, Chenzhen Duan, Xinghao Song, Ye Tian, Hongpeng Wang

Specifically, we propose a scale adaptive module, which dynamically adjusts chip size to balance object scale, narrowing scale variation in training.

object-detection Object Detection In Aerial Images

Temporal Self-Ensembling Teacher for Semi-Supervised Object Detection

1 code implementation13 Jul 2020 Cong Chen, Shouyang Dong, Ye Tian, Kunlin Cao, Li Liu, Yuanhao Guo

(1) The teacher model serves a dual role as a teacher and a student, such that the teacher predictions on unlabeled images may be very close to those of student, which limits the upper-bound of the student.

Knowledge Distillation object-detection +4

RaSE: Random Subspace Ensemble Classification

no code implementations16 Jun 2020 Ye Tian, Yang Feng

In addition, we show that in a high-dimensional framework, the number of random subspaces needs to be very large to guarantee that a subspace covering signals is selected.

Classification General Classification

Downstream Model Design of Pre-trained Language Model for Relation Extraction Task

1 code implementation8 Apr 2020 Cheng Li, Ye Tian

We believe that PLMs can also be used to solve the relation extraction problem, but it is necessary to establish a specially designed downstream task model or even loss function for dealing with complicated relations.

Language Modelling Relation Extraction

Accelerated Primal-Dual Algorithms for Distributed Smooth Convex Optimization over Networks

1 code implementation23 Oct 2019 Jinming Xu, Ye Tian, Ying Sun, Gesualdo Scutari

This paper proposes a novel family of primal-dual-based distributed algorithms for smooth, convex, multi-agent optimization over networks that uses only gradient information and gossip communications.

Distributed Optimization

Computer-aided Detection of Squamous Carcinoma of the Cervix in Whole Slide Images

no code implementations27 May 2019 Ye Tian, Li Yang, Wei Wang, Jing Zhang, Qing Tang, Mili Ji, Yang Yu, Yu Li, Hong Yang, Airong Qian

Traditionally, the most indispensable diagnosis of cervix squamous carcinoma is histopathological assessment which is achieved under microscope by pathologist.

whole slide images

Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

2 code implementations21 Feb 2019 Jonathan Shen, Patrick Nguyen, Yonghui Wu, Zhifeng Chen, Mia X. Chen, Ye Jia, Anjuli Kannan, Tara Sainath, Yuan Cao, Chung-Cheng Chiu, Yanzhang He, Jan Chorowski, Smit Hinsu, Stella Laurenzo, James Qin, Orhan Firat, Wolfgang Macherey, Suyog Gupta, Ankur Bapna, Shuyuan Zhang, Ruoming Pang, Ron J. Weiss, Rohit Prabhavalkar, Qiao Liang, Benoit Jacob, Bowen Liang, HyoukJoong Lee, Ciprian Chelba, Sébastien Jean, Bo Li, Melvin Johnson, Rohan Anil, Rajat Tibrewal, Xiaobing Liu, Akiko Eriguchi, Navdeep Jaitly, Naveen Ari, Colin Cherry, Parisa Haghani, Otavio Good, Youlong Cheng, Raziel Alvarez, Isaac Caswell, Wei-Ning Hsu, Zongheng Yang, Kuan-Chieh Wang, Ekaterina Gonina, Katrin Tomanek, Ben Vanik, Zelin Wu, Llion Jones, Mike Schuster, Yanping Huang, Dehao Chen, Kazuki Irie, George Foster, John Richardson, Klaus Macherey, Antoine Bruguier, Heiga Zen, Colin Raffel, Shankar Kumar, Kanishka Rao, David Rybach, Matthew Murray, Vijayaditya Peddinti, Maxim Krikun, Michiel A. U. Bacchiani, Thomas B. Jablin, Rob Suderman, Ian Williams, Benjamin Lee, Deepti Bhatia, Justin Carlson, Semih Yavuz, Yu Zhang, Ian McGraw, Max Galkin, Qi Ge, Golan Pundak, Chad Whipkey, Todd Wang, Uri Alon, Dmitry Lepikhin, Ye Tian, Sara Sabour, William Chan, Shubham Toshniwal, Baohua Liao, Michael Nirschl, Pat Rondon

Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models.

Sequence-To-Sequence Speech Recognition

THORS: An Efficient Approach for Making Classifiers Cost-sensitive

no code implementations7 Nov 2018 Ye Tian, Weiping Zhang

In this paper, we propose an effective THresholding method based on ORder Statistic, called THORS, to convert an arbitrary scoring-type classifier, which can induce a continuous cumulative distribution function of the score, into a cost-sensitive one.

General Classification

Treat the system like a human student: Automatic naturalness evaluation of generated text without reference texts

no code implementations WS 2018 Isabel Groves, Ye Tian, Ioannis Douratsos

The current most popular method for automatic Natural Language Generation (NLG) evaluation is comparing generated text with human-written reference sentences using a metrics system, which has drawbacks around reliability and scalability.

Image Captioning Machine Translation +2

Aggression Identification and Multi Lingual Word Embeddings

no code implementations COLING 2018 Thiago Galery, Efstathios Charitos, Ye Tian

The system presented here took part in the 2018 Trolling, Aggression and Cyberbullying shared task (Forest and Trees team) and uses a Gated Recurrent Neural Network architecture (Cho et al., 2014) in an attempt to assess whether combining pre-trained English and Hindi fastText (Mikolov et al., 2018) word embeddings as a representation of the sequence input would improve classification performance.

Aggression Identification Multi-Label Text Classification +2

ClusterNet: 3D Instance Segmentation in RGB-D Images

no code implementations24 Jul 2018 Lin Shao, Ye Tian, Jeannette Bohg

We show that our method generalizes well on real-world data achieving visually better segmentation results.

3D Instance Segmentation Clustering +3

Resisting Large Data Variations via Introspective Transformation Network

no code implementations16 May 2018 Yunhan Zhao, Ye Tian, Charless Fowlkes, Wei Shen, Alan Yuille

Experimental results verify that our approach significantly improves the ability of deep networks to resist large variations between training and testing data and achieves classification accuracy improvements on several benchmark datasets, including MNIST, affNIST, SVHN, CIFAR-10 and miniImageNet.

Data Augmentation Few-Shot Learning

Facebook sentiment: Reactions and Emojis

no code implementations WS 2017 Ye Tian, Thiago Galery, Giulio Dulcinati, Emilia Molimpakis, Chao Sun

FB reactions (e. g. {``}Love{''} and {``}Angry{''}) indicate the readers{'} overall sentiment, against which we can investigate the types of emojis used the comments under different reaction profiles.

PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization

no code implementations4 Jan 2017 Ye Tian, Ran Cheng, Xingyi Zhang, Yaochu Jin

To address these issues, we have developed a MATLAB platform for evolutionary multi-objective optimization in this paper, called PlatEMO, which includes more than 50 multi-objective evolutionary algorithms and more than 100 multi-objective test problems, along with several widely used performance indicators.

Evolutionary Algorithms Multiobjective Optimization +1

DUEL: A Multi-lingual Multimodal Dialogue Corpus for Disfluency, Exclamations and Laughter

no code implementations LREC 2016 Julian Hough, Ye Tian, Laura de Ruiter, Simon Betz, Spyros Kousidis, David Schlangen, Jonathan Ginzburg

We present the DUEL corpus, consisting of 24 hours of natural, face-to-face, loosely task-directed dialogue in German, French and Mandarin Chinese.

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