Search Results for author: Han Zhu

Found 23 papers, 10 papers with code

Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: Report

2 code implementations7 Nov 2022 Andrey Ignatov, Radu Timofte, Maurizio Denna, Abdel Younes, Ganzorig Gankhuyag, Jingang Huh, Myeong Kyun Kim, Kihwan Yoon, Hyeon-Cheol Moon, Seungho Lee, Yoonsik Choe, Jinwoo Jeong, Sungjei Kim, Maciej Smyl, Tomasz Latkowski, Pawel Kubik, Michal Sokolski, Yujie Ma, Jiahao Chao, Zhou Zhou, Hongfan Gao, Zhengfeng Yang, Zhenbing Zeng, Zhengyang Zhuge, Chenghua Li, Dan Zhu, Mengdi Sun, Ran Duan, Yan Gao, Lingshun Kong, Long Sun, Xiang Li, Xingdong Zhang, Jiawei Zhang, Yaqi Wu, Jinshan Pan, Gaocheng Yu, Jin Zhang, Feng Zhang, Zhe Ma, Hongbin Wang, Hojin Cho, Steve Kim, Huaen Li, Yanbo Ma, Ziwei Luo, Youwei Li, Lei Yu, Zhihong Wen, Qi Wu, Haoqiang Fan, Shuaicheng Liu, Lize Zhang, Zhikai Zong, Jeremy Kwon, Junxi Zhang, Mengyuan Li, Nianxiang Fu, Guanchen Ding, Han Zhu, Zhenzhong Chen, Gen Li, Yuanfan Zhang, Lei Sun, Dafeng Zhang, Neo Yang, Fitz Liu, Jerry Zhao, Mustafa Ayazoglu, Bahri Batuhan Bilecen, Shota Hirose, Kasidis Arunruangsirilert, Luo Ao, Ho Chun Leung, Andrew Wei, Jie Liu, Qiang Liu, Dahai Yu, Ao Li, Lei Luo, Ce Zhu, Seongmin Hong, Dongwon Park, Joonhee Lee, Byeong Hyun Lee, Seunggyu Lee, Se Young Chun, Ruiyuan He, Xuhao Jiang, Haihang Ruan, Xinjian Zhang, Jing Liu, Garas Gendy, Nabil Sabor, Jingchao Hou, Guanghui He

While numerous solutions have been proposed for this problem in the past, they are usually not compatible with low-power mobile NPUs having many computational and memory constraints.

Image Super-Resolution

Learning Knowledge Representation with Meta Knowledge Distillation for Single Image Super-Resolution

no code implementations18 Jul 2022 Han Zhu, Zhenzhong Chen, Shan Liu

In addition, the KRNets are optimized in a meta-learning manner to ensure the knowledge transferring and the student learning are beneficial to improving the reconstructed quality of the student.

Image Super-Resolution Knowledge Distillation +1

Adaptive Domain Interest Network for Multi-domain Recommendation

no code implementations20 Jun 2022 Yuchen Jiang, Qi Li, Han Zhu, Jinbei Yu, Jin Li, Ziru Xu, Huihui Dong, Bo Zheng

Industrial recommender systems usually hold data from multiple business scenarios and are expected to provide recommendation services for these scenarios simultaneously.

Domain Adaptation Recommendation Systems +1

Boosting Cross-Domain Speech Recognition with Self-Supervision

no code implementations20 Jun 2022 Han Zhu, Gaofeng Cheng, Jindong Wang, Wenxin Hou, Pengyuan Zhang, Yonghong Yan

The cross-domain performance of automatic speech recognition (ASR) could be severely hampered due to the mismatch between training and testing distributions.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +4

WSLRec: Weakly Supervised Learning for Neural Sequential Recommendation Models

no code implementations28 Feb 2022 Jingwei Zhuo, Bin Liu, Xiang Li, Han Zhu, Xiaoqiang Zhu

Motivated by the observation that model-free methods like behavioral retargeting (BR) and item-based collaborative filtering (ItemCF) hit different parts of the user-item relevance compared to neural sequential recommendation models, we propose a novel model-agnostic training approach called WSLRec, which adopts a three-stage framework: pre-training, top-$k$ mining, and fine-tuning.

Collaborative Filtering Sequential Recommendation +1

MBCT: Tree-Based Feature-Aware Binning for Individual Uncertainty Calibration

1 code implementation9 Feb 2022 Siguang Huang, Yunli Wang, Lili Mou, Huayue Zhang, Han Zhu, Chuan Yu, Bo Zheng

In previous work, researchers have developed several calibration methods to post-process the outputs of a predictor to obtain calibrated values, such as binning and scaling methods.

Medical Diagnosis

Optical Flow Reusing for High-Efficiency Space-Time Video Super Resolution

no code implementations13 Oct 2021 Yuantong Zhang, Huairui Wang, Han Zhu, Zhenzhong Chen

In this paper, we consider the task of space-time video super-resolution (ST-VSR), which can increase the spatial resolution and frame rate for a given video simultaneously.

Optical Flow Estimation Space-time Video Super-resolution +2

Wav2vec-S: Semi-Supervised Pre-Training for Low-Resource ASR

no code implementations9 Oct 2021 Han Zhu, Li Wang, Jindong Wang, Gaofeng Cheng, Pengyuan Zhang, Yonghong Yan

In this work, in order to build a better pre-trained model for low-resource ASR, we propose a pre-training approach called wav2vec-S, where we use task-specific semi-supervised pre-training to refine the self-supervised pre-trained model for the ASR task thus more effectively utilize the capacity of the pre-trained model to generate task-specific representations for ASR.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Context-aware Tree-based Deep Model for Recommender Systems

no code implementations22 Sep 2021 Daqing Chang, Jintao Liu, Ziru Xu, Han Li, Han Zhu, Xiaoqiang Zhu

Vertically, a parent fusion layer is designed in M to transmit the user preference representation in higher levels of T to the current level, grasping the essence that tree-based methods are generating the candidate set from coarse to detail during the beam search retrieval.

Recommendation Systems Retrieval

Exploiting Adapters for Cross-lingual Low-resource Speech Recognition

2 code implementations18 May 2021 Wenxin Hou, Han Zhu, Yidong Wang, Jindong Wang, Tao Qin, Renjun Xu, Takahiro Shinozaki

Based on our previous MetaAdapter that implicitly leverages adapters, we propose a novel algorithms called SimAdapter for explicitly learning knowledge from adapters.

Cross-Lingual ASR General Knowledge +3

Truncation-Free Matching System for Display Advertising at Alibaba

no code implementations18 Feb 2021 Jin Li, Jie Liu, Shangzhou Li, Yao Xu, Ran Cao, Qi Li, Biye Jiang, Guan Wang, Han Zhu, Kun Gai, Xiaoqiang Zhu

When receiving a user request, matching system (i) finds the crowds that the user belongs to; (ii) retrieves all ads that have targeted those crowds.


Multi-Accent Adaptation based on Gate Mechanism

no code implementations5 Nov 2020 Han Zhu, Li Wang, Pengyuan Zhang, Yonghong Yan

To jointly train the acoustic model and the accent classifier, we propose the multi-task learning with gate mechanism (MTL-G).

Multi-Task Learning speech-recognition +1

Domain Adaptation Using Class Similarity for Robust Speech Recognition

1 code implementation5 Nov 2020 Han Zhu, Jiangjiang Zhao, Yuling Ren, Li Wang, Pengyuan Zhang

Then, for each class, probabilities of this class are used to compute a mean vector, which we refer to as mean soft labels.

Domain Adaptation Robust Speech Recognition +1

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

A Survey of Optimization Methods from a Machine Learning Perspective

no code implementations17 Jun 2019 Shiliang Sun, Zehui Cao, Han Zhu, Jing Zhao

Machine learning develops rapidly, which has made many theoretical breakthroughs and is widely applied in various fields.

BIG-bench Machine Learning

Learning Tree-based Deep Model for Recommender Systems

4 code implementations8 Jan 2018 Han Zhu, Xiang Li, Pengye Zhang, Guozheng Li, Jie He, Han Li, Kun Gai

In systems with large corpus, however, the calculation cost for the learnt model to predict all user-item preferences is tremendous, which makes full corpus retrieval extremely difficult.

Recommendation Systems Retrieval

Deep Interest Network for Click-Through Rate Prediction

16 code implementations21 Jun 2017 Guorui Zhou, Chengru Song, Xiaoqiang Zhu, Ying Fan, Han Zhu, Xiao Ma, Yanghui Yan, Junqi Jin, Han Li, Kun Gai

In this way, user features are compressed into a fixed-length representation vector, in regardless of what candidate ads are.

Click-Through Rate Prediction

Optimized Cost per Click in Taobao Display Advertising

no code implementations27 Feb 2017 Han Zhu, Junqi Jin, Chang Tan, Fei Pan, Yifan Zeng, Han Li, Kun Gai

Moreover, the platform has to be responsible for the business revenue and user experience.

Deep Transfer Learning with Joint Adaptation Networks

4 code implementations ICML 2017 Mingsheng Long, Han Zhu, Jian-Min Wang, Michael. I. Jordan

Deep networks have been successfully applied to learn transferable features for adapting models from a source domain to a different target domain.

Multi-Source Unsupervised Domain Adaptation Transfer Learning

Unsupervised Domain Adaptation with Residual Transfer Networks

2 code implementations NeurIPS 2016 Mingsheng Long, Han Zhu, Jian-Min Wang, Michael. I. Jordan

In this paper, we propose a new approach to domain adaptation in deep networks that can jointly learn adaptive classifiers and transferable features from labeled data in the source domain and unlabeled data in the target domain.

Unsupervised Domain Adaptation

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