Search Results for author: Zhen Qin

Found 31 papers, 9 papers with code

Towards Disentangling Relevance and Bias in Unbiased Learning to Rank

no code implementations28 Dec 2022 Yunan Zhang, Le Yan, Zhen Qin, Honglei Zhuang, Jiaming Shen, Xuanhui Wang, Michael Bendersky, Marc Najork

We give both theoretical analysis and empirical results to show the negative effects on relevance tower due to such a correlation.


Learning List-Level Domain-Invariant Representations for Ranking

no code implementations21 Dec 2022 Ruicheng Xian, Honglei Zhuang, Zhen Qin, Hamed Zamani, Jing Lu, Ji Ma, Kai Hui, Han Zhao, Xuanhui Wang, Michael Bendersky

Domain adaptation aims to transfer the knowledge acquired by models trained on (data-rich) source domains to (low-resource) target domains, for which a popular method is invariant representation learning.

Representation Learning Unsupervised Domain Adaptation

Adaptive Combination of Proportionate Recursive Maximum Correntropy Criterion Algorithms and its Performance Analysis

no code implementations22 Oct 2022 Zhen Qin, Jun Tao, Le Yang, Yili Xia, Ming Jiang

The sparse adaptive algorithms under maximum correntropy criterion (MCC) have been developed and available for practical use due to their robustness against outliers (or impulsive noises).

The Devil in Linear Transformer

1 code implementation19 Oct 2022 Zhen Qin, Xiaodong Han, Weixuan Sun, Dongxu Li, Lingpeng Kong, Nick Barnes, Yiran Zhong

In this paper, we examine existing kernel-based linear transformers and identify two key issues that lead to such performance gaps: 1) unbounded gradients in the attention computation adversely impact the convergence of linear transformer models; 2) attention dilution which trivially distributes attention scores over long sequences while neglecting neighbouring structures.

Language Modelling Text Classification

Linear Video Transformer with Feature Fixation

no code implementations15 Oct 2022 Kaiyue Lu, Zexiang Liu, Jianyuan Wang, Weixuan Sun, Zhen Qin, Dong Li, Xuyang Shen, Hui Deng, Xiaodong Han, Yuchao Dai, Yiran Zhong

Therefore, we propose a feature fixation module to reweight the feature importance of the query and key before computing linear attention.

Association Feature Importance +1

RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses

no code implementations12 Oct 2022 Honglei Zhuang, Zhen Qin, Rolf Jagerman, Kai Hui, Ji Ma, Jing Lu, Jianmo Ni, Xuanhui Wang, Michael Bendersky

Recently, substantial progress has been made in text ranking based on pretrained language models such as BERT.

A Validation Approach to Over-parameterized Matrix and Image Recovery

no code implementations21 Sep 2022 Lijun Ding, Zhen Qin, Liwei Jiang, Jinxin Zhou, Zhihui Zhu

In this paper, we study the problem of recovering a low-rank matrix from a number of noisy random linear measurements.

Image Restoration

Neural Architecture Search on Efficient Transformers and Beyond

no code implementations28 Jul 2022 Zexiang Liu, Dong Li, Kaiyue Lu, Zhen Qin, Weixuan Sun, Jiacheng Xu, Yiran Zhong

To address this issue, we propose a new framework to find optimal architectures for efficient Transformers with the neural architecture search (NAS) technique.

Image Classification Machine Translation +1

Error Analysis of Tensor-Train Cross Approximation

no code implementations9 Jul 2022 Zhen Qin, Alexander Lidiak, Zhexuan Gong, Gongguo Tang, Michael B. Wakin, Zhihui Zhu

Tensor train decomposition is widely used in machine learning and quantum physics due to its concise representation of high-dimensional tensors, overcoming the curse of dimensionality.

Vicinity Vision Transformer

1 code implementation21 Jun 2022 Weixuan Sun, Zhen Qin, Hui Deng, Jianyuan Wang, Yi Zhang, Kaihao Zhang, Nick Barnes, Stan Birchfield, Lingpeng Kong, Yiran Zhong

Based on this observation, we present a Vicinity Attention that introduces a locality bias to vision transformers with linear complexity.

Image Classification

cosFormer: Rethinking Softmax in Attention

2 code implementations ICLR 2022 Zhen Qin, Weixuan Sun, Hui Deng, Dongxu Li, Yunshen Wei, Baohong Lv, Junjie Yan, Lingpeng Kong, Yiran Zhong

As one of its core components, the softmax attention helps to capture long-range dependencies yet prohibits its scale-up due to the quadratic space and time complexity to the sequence length.

Language Modelling

Transformer Memory as a Differentiable Search Index

1 code implementation14 Feb 2022 Yi Tay, Vinh Q. Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri, Harsh Mehta, Zhen Qin, Kai Hui, Zhe Zhao, Jai Gupta, Tal Schuster, William W. Cohen, Donald Metzler

In this paper, we demonstrate that information retrieval can be accomplished with a single Transformer, in which all information about the corpus is encoded in the parameters of the model.

Information Retrieval Retrieval

Rank4Class: A Ranking Formulation for Multiclass Classification

no code implementations17 Dec 2021 Nan Wang, Zhen Qin, Le Yan, Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Marc Najork

Multiclass classification (MCC) is a fundamental machine learning problem of classifying each instance into one of a predefined set of classes.

Classification Image Classification +4

Improving Neural Ranking via Lossless Knowledge Distillation

no code implementations30 Sep 2021 Zhen Qin, Le Yan, Yi Tay, Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Marc Najork

We explore a novel perspective of knowledge distillation (KD) for learning to rank (LTR), and introduce Self-Distilled neural Rankers (SDR), where student rankers are parameterized identically to their teachers.

Knowledge Distillation Learning-To-Rank

Rank4Class: Examining Multiclass Classification through the Lens of Learning to Rank

no code implementations29 Sep 2021 Nan Wang, Zhen Qin, Le Yan, Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Marc Najork

We further demonstrate that the most popular MCC architecture in deep learning can be mathematically formulated as a LTR pipeline equivalently, with a specific set of choices in terms of ranking model architecture and loss function.

Image Classification Information Retrieval +4

Are Pretrained Convolutions Better than Pretrained Transformers?

1 code implementation ACL 2021 Yi Tay, Mostafa Dehghani, Jai Prakash Gupta, Vamsi Aribandi, Dara Bahri, Zhen Qin, Donald Metzler

In the context of language models, are convolutional models competitive to Transformers when pre-trained?

Are Pre-trained Convolutions Better than Pre-trained Transformers?

1 code implementation7 May 2021 Yi Tay, Mostafa Dehghani, Jai Gupta, Dara Bahri, Vamsi Aribandi, Zhen Qin, Donald Metzler

In the context of language models, are convolutional models competitive to Transformers when pre-trained?

OmniNet: Omnidirectional Representations from Transformers

1 code implementation1 Mar 2021 Yi Tay, Mostafa Dehghani, Vamsi Aribandi, Jai Gupta, Philip Pham, Zhen Qin, Dara Bahri, Da-Cheng Juan, Donald Metzler

In OmniNet, instead of maintaining a strictly horizontal receptive field, each token is allowed to attend to all tokens in the entire network.

Few-Shot Learning Language Modelling +2

Neural Rankers are hitherto Outperformed by Gradient Boosted Decision Trees

no code implementations ICLR 2021 Zhen Qin, Le Yan, Honglei Zhuang, Yi Tay, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, Marc Najork

We first validate this concern by showing that most recent neural LTR models are, by a large margin, inferior to the best publicly available Gradient Boosted Decision Trees (GBDT) in terms of their reported ranking accuracy on benchmark datasets.


DeepKeyGen: A Deep Learning-based Stream Cipher Generator for Medical Image Encryption and Decryption

no code implementations21 Dec 2020 Yi Ding, Fuyuan Tan, Zhen Qin, Mingsheng Cao, Kim-Kwang Raymond Choo, Zhiguang Qin

In this paper, a novel deep learning-based key generation network (DeepKeyGen) is proposed as a stream cipher generator to generate the private key, which can then be used for encrypting and decrypting of medical images.

Do RNN and LSTM have Long Memory?

1 code implementation ICML 2020 Jingyu Zhao, Feiqing Huang, Jia Lv, Yanjie Duan, Zhen Qin, Guodong Li, Guangjian Tian

The LSTM network was proposed to overcome the difficulty in learning long-term dependence, and has made significant advancements in applications.

Non-Clicks Mean Irrelevant? Propensity Ratio Scoring As a Correction

no code implementations18 May 2020 Nan Wang, Zhen Qin, Xuanhui Wang, Hongning Wang

Recent advances in unbiased learning to rank (LTR) count on Inverse Propensity Scoring (IPS) to eliminate bias in implicit feedback.


Multi-Task Learning for Email Search Ranking with Auxiliary Query Clustering

no code implementations15 Sep 2018 Jiaming Shen, Maryam Karimzadehgan, Michael Bendersky, Zhen Qin, Donald Metzler

In this paper, we study how to obtain query type in an unsupervised fashion and how to incorporate this information into query-dependent ranking models.

Multi-Task Learning

An Online Learned Elementary Grouping Model for Multi-target Tracking

no code implementations CVPR 2014 Xiaojing Chen, Zhen Qin, Le An, Bir Bhanu

We introduce an online approach to learn possible elementary groups (groups that contain only two targets) for inferring high level context that can be used to improve multi-target tracking in a data-association based framework.


Efficient Online Bootstrapping for Large Scale Learning

no code implementations18 Dec 2013 Zhen Qin, Vaclav Petricek, Nikos Karampatziakis, Lihong Li, John Langford

Bootstrapping is a useful technique for estimating the uncertainty of a predictor, for example, confidence intervals for prediction.

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