Search Results for author: Wei Dai

Found 60 papers, 21 papers with code

SoccerNet 2023 Challenges Results

1 code implementation12 Sep 2023 Anthony Cioppa, Silvio Giancola, Vladimir Somers, Floriane Magera, Xin Zhou, Hassan Mkhallati, Adrien Deliège, Jan Held, Carlos Hinojosa, Amir M. Mansourian, Pierre Miralles, Olivier Barnich, Christophe De Vleeschouwer, Alexandre Alahi, Bernard Ghanem, Marc Van Droogenbroeck, Abdullah Kamal, Adrien Maglo, Albert Clapés, Amr Abdelaziz, Artur Xarles, Astrid Orcesi, Atom Scott, Bin Liu, Byoungkwon Lim, Chen Chen, Fabian Deuser, Feng Yan, Fufu Yu, Gal Shitrit, Guanshuo Wang, Gyusik Choi, Hankyul Kim, Hao Guo, Hasby Fahrudin, Hidenari Koguchi, Håkan Ardö, Ibrahim Salah, Ido Yerushalmy, Iftikar Muhammad, Ikuma Uchida, Ishay Be'ery, Jaonary Rabarisoa, Jeongae Lee, Jiajun Fu, Jianqin Yin, Jinghang Xu, Jongho Nang, Julien Denize, Junjie Li, Junpei Zhang, Juntae Kim, Kamil Synowiec, Kenji Kobayashi, Kexin Zhang, Konrad Habel, Kota Nakajima, Licheng Jiao, Lin Ma, Lizhi Wang, Luping Wang, Menglong Li, Mengying Zhou, Mohamed Nasr, Mohamed Abdelwahed, Mykola Liashuha, Nikolay Falaleev, Norbert Oswald, Qiong Jia, Quoc-Cuong Pham, Ran Song, Romain Hérault, Rui Peng, Ruilong Chen, Ruixuan Liu, Ruslan Baikulov, Ryuto Fukushima, Sergio Escalera, Seungcheon Lee, Shimin Chen, Shouhong Ding, Taiga Someya, Thomas B. Moeslund, Tianjiao Li, Wei Shen, Wei zhang, Wei Li, Wei Dai, Weixin Luo, Wending Zhao, Wenjie Zhang, Xinquan Yang, Yanbiao Ma, Yeeun Joo, Yingsen Zeng, Yiyang Gan, Yongqiang Zhu, Yujie Zhong, Zheng Ruan, Zhiheng Li, Zhijian Huang, Ziyu Meng

More information on the tasks, challenges, and leaderboards are available on https://www. soccer-net. org.

Action Spotting Camera Calibration +3

Constructive Incremental Learning for Fault Diagnosis of Rolling Bearings with Ensemble Domain Adaptation

no code implementations29 Aug 2023 Jiang Liu, Wei Dai

Given the prevalence of rolling bearing fault diagnosis as a practical issue across various working conditions, the limited availability of samples compounds the challenge.

Domain Adaptation Ensemble Learning +1

DPAN: Dynamic Preference-based and Attribute-aware Network for Relevant Recommendations

1 code implementation21 Aug 2023 Wei Dai, Yingmin Su, Xiaofeng Pan

In e-commerce platforms, the relevant recommendation is a unique scenario providing related items for a trigger item that users are interested in.

FinEval: A Chinese Financial Domain Knowledge Evaluation Benchmark for Large Language Models

1 code implementation19 Aug 2023 Liwen Zhang, Weige Cai, Zhaowei Liu, Zhi Yang, Wei Dai, Yujie Liao, Qianru Qin, Yifei Li, Xingyu Liu, Zhiqiang Liu, Zhoufan Zhu, Anbo Wu, Xin Guo, Yun Chen

Our work offers a more comprehensive financial knowledge evaluation benchmark, utilizing data of mock exams and covering a wide range of evaluated LLMs.


Cloud Ensemble Learning for Fault Diagnosis of Rolling Bearings with Stochastic Configuration Networks

no code implementations2 Jul 2023 Wei Dai, Jiang Liu, Lanhao Wang

Concretely, a cloud feature extraction method is first developed by using a backward cloud generator of normal cloud model to mine the uncertainty of fault information.

Ensemble Learning

An Interpretable Constructive Algorithm for Incremental Random Weight Neural Networks and Its Application

no code implementations1 Jul 2023 Jing Nan, Wei Dai, Guan Yuan, Ping Zhou

However, a significant drawback of IRWNNs is that the elationship between the hidden parameters (node)and the residual error (model performance) is difficult to be interpreted.

A Mask Free Neural Network for Monaural Speech Enhancement

1 code implementation7 Jun 2023 Liang Liu, Haixin Guan, Jinlong Ma, Wei Dai, Guangyong Wang, Shaowei Ding

In speech enhancement, the lack of clear structural characteristics in the target speech phase requires the use of conservative and cumbersome network frameworks.

Speech Enhancement

Transformer-Based Hierarchical Clustering for Brain Network Analysis

1 code implementation6 May 2023 Wei Dai, Hejie Cui, Xuan Kan, Ying Guo, Sanne van Rooij, Carl Yang

Brain networks, graphical models such as those constructed from MRI, have been widely used in pathological prediction and analysis of brain functions.


Explainable Semantic Medical Image Segmentation with Style

no code implementations10 Mar 2023 Wei Dai, Siyu Liu, Craig B. Engstrom, Shekhar S. Chandra

The discriminator is generalised to small domain shifts as much as permissible by the training data, and the generator automatically diversifies the training samples using a manifold of input features learnt during segmentation.

Image Segmentation Medical Image Segmentation +1

TrojanPuzzle: Covertly Poisoning Code-Suggestion Models

1 code implementation6 Jan 2023 Hojjat Aghakhani, Wei Dai, Andre Manoel, Xavier Fernandes, Anant Kharkar, Christopher Kruegel, Giovanni Vigna, David Evans, Ben Zorn, Robert Sim

To achieve this, prior poisoning attacks explicitly inject the insecure code payload into the training data, making the poisoning data detectable by static analysis tools that can remove such malicious data from the training set.

Data Poisoning

Discovering Limitations of Image Quality Assessments with Noised Deep Learning Image Sets

no code implementations19 Oct 2022 Wei Dai, Daniel Berleant

After quantitatively analyzing experimental results, we report the limitations of the two IQAs with these noised CIFAR-10 and MNIST image sets.

Image Quality Assessment object-detection +1

Brain Network Transformer

1 code implementation13 Oct 2022 Xuan Kan, Wei Dai, Hejie Cui, Zilong Zhang, Ying Guo, Carl Yang

Human brains are commonly modeled as networks of Regions of Interest (ROIs) and their connections for the understanding of brain functions and mental disorders.


Multimodal Brain Disease Classification with Functional Interaction Learning from Single fMRI Volume

no code implementations5 Aug 2022 Wei Dai, Ziyao Zhang, Lixia Tian, Shengyuan Yu, Shuhui Wang, Zhao Dong, Hairong Zheng

The low representation ability of FC leads to poor performance in clinical practice, especially when dealing with multimodal medical data involving multiple types of visual signals and textual records for brain diseases.

Time Series Analysis

Combing for Credentials: Active Pattern Extraction from Smart Reply

no code implementations14 Jul 2022 Bargav Jayaraman, Esha Ghosh, Melissa Chase, Sambuddha Roy, Wei Dai, David Evans

We show experimentally that it is possible for an adversary to extract sensitive user information present in the training data, even in realistic settings where all interactions with the model must go through a front-end that limits the types of queries.

Language Modelling

Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis

1 code implementation30 Jun 2022 Hejie Cui, Wei Dai, Yanqiao Zhu, Xiaoxiao Li, Lifang He, Carl Yang

Mapping the connections of the human brain as a network is one of the most pervasive paradigms in neuroscience.

Disease Prediction

Orthogonal Stochastic Configuration Networks with Adaptive Construction Parameter for Data Analytics

no code implementations26 May 2022 Wei Dai, Chuanfeng Ning, Shiyu Pei, Song Zhu, Xuesong Wang

As a randomized learner model, SCNs are remarkable that the random weights and biases are assigned employing a supervisory mechanism to ensure universal approximation and fast learning.

Deeply Supervised Skin Lesions Diagnosis with Stage and Branch Attention

2 code implementations9 May 2022 Wei Dai, Rui Liu, Tianyi Wu, Min Wang, Jianqin Yin, Jun Liu

Visual features of skin lesions vary significantly because the images are collected from patients with different lesion colours and morphologies by using dissimilar imaging equipment.

Digging into Primary Financial Market: Challenges and Opportunities of Adopting Blockchain

no code implementations20 Apr 2022 Ji Liu, Zheng Xu, Yanmei Zhang, Wei Dai, Hao Wu, Shiping Chen

Since the emergence of blockchain technology, its application in the financial market has always been an area of focus and exploration by all parties.

A New Learning Paradigm for Stochastic Configuration Network: SCN+

no code implementations11 Mar 2022 Yanshuang Ao, Xinyu Zhou, Wei Dai

This novel algorithm can leverage privileged information into SCN in the training stage, which provides a new method to train SCN.

Incremental Learning

Benchmarking Robustness of Deep Learning Classifiers Using Two-Factor Perturbation

no code implementations2 Mar 2022 Wei Dai, Daniel Berleant

We created comprehensive 69 benchmarking image sets, including a clean set, sets with single factor perturbations, and sets with two-factor perturbation conditions.

Benchmarking Vocal Bursts Valence Prediction

Dictionary Learning Using Rank-One Atomic Decomposition (ROAD)

no code implementations25 Oct 2021 Cheng Cheng, Wei Dai

Dictionary learning aims at seeking a dictionary under which the training data can be sparsely represented.

Dictionary Learning

Dictionary Learning with Convex Update (ROMD)

no code implementations13 Oct 2021 Cheng Cheng, Wei Dai

Typical methods for dictionary update focuses on refining both dictionary atoms and their corresponding sparse coefficients by using the sparsity patterns obtained from sparse coding stage, and hence it is a non-convex bilinear inverse problem.

Dictionary Learning

Short-and-Sparse Deconvolution Via Rank-One Constrained Optimization (ROCO)

no code implementations5 Oct 2021 Cheng Cheng, Wei Dai

In the literature, formulations of blind deconvolution is either a convex programming via a matrix lifting of convolution, or a bilinear Lasso.

CAN3D: Fast 3D Medical Image Segmentation via Compact Context Aggregation

no code implementations12 Sep 2021 Wei Dai, Boyeong Woo, Siyu Liu, Matthew Marques, Craig B. Engstrom, Peter B. Greer, Stuart Crozier, Jason A. Dowling, Shekhar S. Chandra

Direct automatic segmentation of objects from 3D medical imaging, such as magnetic resonance (MR) imaging, is challenging as it often involves accurately identifying a number of individual objects with complex geometries within a large volume under investigation.

Image Segmentation Medical Image Segmentation +1

Conflict-Free Four-Dimensional Path Planning for Urban Air Mobility Considering Airspace Occupations

no code implementations27 Jul 2021 Wei Dai, Bizhao Pang, Kin Huat Low

This paper aims at tackling conflict-free path planning problem for UAM operation with a consideration of four-dimensional airspace management.


BrainNNExplainer: An Interpretable Graph Neural Network Framework for Brain Network based Disease Analysis

1 code implementation11 Jul 2021 Hejie Cui, Wei Dai, Yanqiao Zhu, Xiaoxiao Li, Lifang He, Carl Yang

Interpretable brain network models for disease prediction are of great value for the advancement of neuroscience.

Disease Prediction

Price change prediction of ultra high frequency financial data based on temporal convolutional network

no code implementations1 Jul 2021 Wei Dai, Yuan An, Wen Long

Through in-depth analysis of ultra high frequency (UHF) stock price change data, more reasonable discrete dynamic distribution models are constructed in this paper.

Deep Kernel Gaussian Process Based Financial Market Predictions

no code implementations26 May 2021 Yong Shi, Wei Dai, Wen Long, Bo Li

However, the deep kernel Gaussian Process has not been applied to forecast the conditional returns and volatility in financial market to the best of our knowledge.

VMAF And Variants: Towards A Unified VQA

no code implementations13 Mar 2021 Pankaj Topiwala, Wei Dai, Jiangfeng Pian, Katalina Biondi, Arvind Krovvidi

We investigate variants of the popular VMAF video quality assessment algorithm for the FR case, using both support vector regression and feedforward neural networks.

feature selection regression +2

Benchmarking Robustness of Deep Learning Classifiers Using Two-Factor Perturbation

2 code implementations2 Mar 2021 Wei Dai, Daniel Berleant

Also, we introduce a new four-quadrant statistical visualization tool, including minimum accuracy, maximum accuracy, mean accuracy, and coefficient of variation, for benchmarking robustness of DL classifiers.

Benchmarking Vocal Bursts Valence Prediction

Improved ACD-based financial trade durations prediction leveraging LSTM networks and Attention Mechanism

no code implementations7 Jan 2021 Yong Shi, Wei Dai, Wen Long, Bo Li

In the input sequence, the temporal positions which are more important for predicting the next duration can be efficiently highlighted via the added attention mechanism layer.

Where is the Model Looking At?--Concentrate and Explain the Network Attention

no code implementations29 Sep 2020 Wenjia Xu, Jiuniu Wang, Yang Wang, Guangluan Xu, Wei Dai, Yirong Wu

We generate attribute-based textual explanations for the network and ground the attributes on the image to show visual explanations.

Image Classification Multi-Task Learning

Generalisable 3D Fabric Architecture for Streamlined Universal Multi-Dataset Medical Image Segmentation

1 code implementation28 Jun 2020 Siyu Liu, Wei Dai, Craig Engstrom, Jurgen Fripp, Stuart Crozier, Jason A. Dowling, Shekhar S. Chandra

However, medical image datasets have diverse-sized images and features, and developing a model simultaneously for multiple datasets is challenging.

Anatomy Image Segmentation +3

Learning Optimal Tree Models Under Beam Search

1 code implementation ICML 2020 Jingwei Zhuo, Ziru Xu, Wei Dai, Han Zhu, Han Li, Jian Xu, Kun Gai

Retrieving relevant targets from an extremely large target set under computational limits is a common challenge for information retrieval and recommendation systems.

Information Retrieval Recommendation Systems +1

EVA: An Encrypted Vector Arithmetic Language and Compiler for Efficient Homomorphic Computation

4 code implementations27 Dec 2019 Roshan Dathathri, Blagovesta Kostova, Olli Saarikivi, Wei Dai, Kim Laine, Madanlal Musuvathi

We believe that EVA would enable a wider adoption of FHE by making it easier to develop FHE applications and domain-specific FHE compilers.

HEAX: An Architecture for Computing on Encrypted Data

no code implementations20 Sep 2019 M. Sadegh Riazi, Kim Laine, Blake Pelton, Wei Dai

Building on top of NTT engine, we design a novel architecture for computation on homomorphically encrypted data.

Cloud Computing

Charge-Based Prison Term Prediction with Deep Gating Network

no code implementations IJCNLP 2019 Huajie Chen, Deng Cai, Wei Dai, Zehui Dai, Yadong Ding

Judgment prediction for legal cases has attracted much research efforts for its practice use, of which the ultimate goal is prison term prediction.

feature selection

Benchmarking Contemporary Deep Learning Hardware and Frameworks:A Survey of Qualitative Metrics

1 code implementation5 Jul 2019 Wei Dai, Daniel Berleant

This paper surveys benchmarking principles, machine learning devices including GPUs, FPGAs, and ASICs, and deep learning software frameworks.

Benchmarking BIG-bench Machine Learning

Dictionary Learning with BLOTLESS Update

1 code implementation24 Jun 2019 Qi Yu, Wei Dai, Zoran Cvetkovic, Jubo Zhu

BLOTLESS updates a block of dictionary elements and the corresponding sparse coefficients simultaneously.

Dictionary Learning

Improving Data Quality through Deep Learning and Statistical Models

no code implementations16 Oct 2018 Wei Dai, Kenji Yoshigoe, William Parsley

Traditional data quality control methods are based on users experience or previously established business rules, and this limits performance in addition to being a very time consuming process with lower than desirable accuracy.

Toward Understanding the Impact of Staleness in Distributed Machine Learning

no code implementations ICLR 2019 Wei Dai, Yi Zhou, Nanqing Dong, Hao Zhang, Eric P. Xing

Many distributed machine learning (ML) systems adopt the non-synchronous execution in order to alleviate the network communication bottleneck, resulting in stale parameters that do not reflect the latest updates.

BIG-bench Machine Learning

Reinforced Auto-Zoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Whole-slide Images

no code implementations29 Jul 2018 Nanqing Dong, Michael Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric P. Xing

Motivated by the zoom-in operation of a pathologist using a digital microscope, RAZN learns a policy network to decide whether zooming is required in a given region of interest.

whole slide images

Cavs: A Vertex-centric Programming Interface for Dynamic Neural Networks

no code implementations11 Dec 2017 Hao Zhang, Shizhen Xu, Graham Neubig, Wei Dai, Qirong Ho, Guangwen Yang, Eric P. Xing

Recent deep learning (DL) models have moved beyond static network architectures to dynamic ones, handling data where the network structure changes every example, such as sequences of variable lengths, trees, and graphs.

graph construction Management +1

Dual Motion GAN for Future-Flow Embedded Video Prediction

no code implementations ICCV 2017 Xiaodan Liang, Lisa Lee, Wei Dai, Eric P. Xing

To make both synthesized future frames and flows indistinguishable from reality, a dual adversarial training method is proposed to ensure that the future-flow prediction is able to help infer realistic future-frames, while the future-frame prediction in turn leads to realistic optical flows.

Representation Learning Video Prediction

Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters

no code implementations11 Jun 2017 Hao Zhang, Zeyu Zheng, Shizhen Xu, Wei Dai, Qirong Ho, Xiaodan Liang, Zhiting Hu, Jinliang Wei, Pengtao Xie, Eric P. Xing

We show that Poseidon enables Caffe and TensorFlow to achieve 15. 5x speed-up on 16 single-GPU machines, even with limited bandwidth (10GbE) and the challenging VGG19-22K network for image classification.

Image Classification

SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays

no code implementations26 Mar 2017 Wei Dai, Joseph Doyle, Xiaodan Liang, Hao Zhang, Nanqing Dong, Yuan Li, Eric P. Xing

Through this adversarial process the critic network learns the higher order structures and guides the segmentation model to achieve realistic segmentation outcomes.

Organ Segmentation

A Comparison of deep learning methods for environmental sound

1 code implementation20 Mar 2017 Juncheng Li, Wei Dai, Florian Metze, Shuhui Qu, Samarjit Das

On these features, we apply five models: Gaussian Mixture Model (GMM), Deep Neural Network (DNN), Recurrent Neural Network (RNN), Convolutional Deep Neural Net- work (CNN) and i-vector.


Learning Filter Banks Using Deep Learning For Acoustic Signals

no code implementations29 Nov 2016 Shuhui Qu, Juncheng Li, Wei Dai, Samarjit Das

Based on the procedure of log Mel-filter banks, we design a filter bank learning layer.

Very Deep Convolutional Neural Networks for Raw Waveforms

8 code implementations1 Oct 2016 Wei Dai, Chia Dai, Shuhui Qu, Juncheng Li, Samarjit Das

Our CNNs, with up to 34 weight layers, are efficient to optimize over very long sequences (e. g., vector of size 32000), necessary for processing acoustic waveforms.

Representation Learning

Strategies and Principles of Distributed Machine Learning on Big Data

no code implementations31 Dec 2015 Eric P. Xing, Qirong Ho, Pengtao Xie, Wei Dai

Taking the view that Big ML systems can benefit greatly from ML-rooted statistical and algorithmic insights --- and that ML researchers should therefore not shy away from such systems design --- we discuss a series of principles and strategies distilled from our recent efforts on industrial-scale ML solutions.

BIG-bench Machine Learning

LightLDA: Big Topic Models on Modest Compute Clusters

1 code implementation4 Dec 2014 Jinhui Yuan, Fei Gao, Qirong Ho, Wei Dai, Jinliang Wei, Xun Zheng, Eric P. Xing, Tie-Yan Liu, Wei-Ying Ma

When building large-scale machine learning (ML) programs, such as big topic models or deep neural nets, one usually assumes such tasks can only be attempted with industrial-sized clusters with thousands of nodes, which are out of reach for most practitioners or academic researchers.

Topic Models

High-Performance Distributed ML at Scale through Parameter Server Consistency Models

no code implementations29 Oct 2014 Wei Dai, Abhimanu Kumar, Jinliang Wei, Qirong Ho, Garth Gibson, Eric P. Xing

As Machine Learning (ML) applications increase in data size and model complexity, practitioners turn to distributed clusters to satisfy the increased computational and memory demands.

Vocal Bursts Intensity Prediction

Parallel and Distributed Block-Coordinate Frank-Wolfe Algorithms

no code implementations22 Sep 2014 Yu-Xiang Wang, Veeranjaneyulu Sadhanala, Wei Dai, Willie Neiswanger, Suvrit Sra, Eric P. Xing

We develop parallel and distributed Frank-Wolfe algorithms; the former on shared memory machines with mini-batching, and the latter in a delayed update framework.

Petuum: A New Platform for Distributed Machine Learning on Big Data

no code implementations30 Dec 2013 Eric P. Xing, Qirong Ho, Wei Dai, Jin Kyu Kim, Jinliang Wei, Seunghak Lee, Xun Zheng, Pengtao Xie, Abhimanu Kumar, Yao-Liang Yu

What is a systematic way to efficiently apply a wide spectrum of advanced ML programs to industrial scale problems, using Big Models (up to 100s of billions of parameters) on Big Data (up to terabytes or petabytes)?

BIG-bench Machine Learning Scheduling

Consistent Bounded-Asynchronous Parameter Servers for Distributed ML

no code implementations30 Dec 2013 Jinliang Wei, Wei Dai, Abhimanu Kumar, Xun Zheng, Qirong Ho, Eric P. Xing

Many ML algorithms fall into the category of \emph{iterative convergent algorithms} which start from a randomly chosen initial point and converge to optima by repeating iteratively a set of procedures.

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