Search Results for author: Wei Chu

Found 37 papers, 12 papers with code

Variational Connectionist Temporal Classification

no code implementations ECCV 2020 Linlin Chao, Jingdong Chen, Wei Chu

However, CTC tends to output spiky distributions since it prefers to output blank symbol most of the time.

Classification General Classification +2

ESCM$^2$: Entire Space Counterfactual Multi-Task Model for Post-Click Conversion Rate Estimation

no code implementations3 Apr 2022 Hao Wang, Tai-Wei Chang, Tianqiao Liu, Jianmin Huang, Zhichao Chen, Chao Yu, Ruopeng Li, Wei Chu

In this paper, we theoretically demonstrate that ESMM suffers from the following two problems: (1) Inherent Estimation Bias (IEB), where the estimated CVR of ESMM is inherently higher than the ground truth; (2) Potential Independence Priority (PIP) for CTCVR estimation, where there is a risk that the ESMM overlooks the causality from click to conversion.

Recommendation Systems Selection bias

Training Protocol Matters: Towards Accurate Scene Text Recognition via Training Protocol Searching

2 code implementations13 Mar 2022 Xiaojie Chu, Yongtao Wang, Chunhua Shen, Jingdong Chen, Wei Chu

The development of scene text recognition (STR) in the era of deep learning has been mainly focused on novel architectures of STR models.

Scene Text Recognition

CBNetV2: A Composite Backbone Network Architecture for Object Detection

3 code implementations1 Jul 2021 TingTing Liang, Xiaojie Chu, Yudong Liu, Yongtao Wang, Zhi Tang, Wei Chu, Jingdong Chen, Haibin Ling

With multi-scale testing, we push the current best single model result to a new record of 60. 1% box AP and 52. 3% mask AP without using extra training data.

Instance Segmentation Object Detection

Discrimination-Aware Mechanism for Fine-Grained Representation Learning

no code implementations CVPR 2021 Furong Xu, Meng Wang, Wei zhang, Yuan Cheng, Wei Chu

Therefore, there is a need for a training mechanism that enforces the discriminativeness of all the elements in the feature to capture more the subtle visual cues.

Representation Learning

LPSNet: A Lightweight Solution for Fast Panoptic Segmentation

no code implementations CVPR 2021 Weixiang Hong, Qingpei Guo, Wei zhang, Jingdong Chen, Wei Chu

Panoptic segmentation is a challenging task aiming to simultaneously segment objects (things) at instance level and background contents (stuff) at semantic level.

Instance Segmentation Panoptic Segmentation

An Improved Single Step Non-autoregressive Transformer for Automatic Speech Recognition

no code implementations18 Jun 2021 Ruchao Fan, Wei Chu, Peng Chang, Jing Xiao, Abeer Alwan

For the analyses, we plot attention weight distributions in the decoders to visualize the relationships between token-level acoustic embeddings.

Automatic Speech Recognition Word Embeddings

CMUA-Watermark: A Cross-Model Universal Adversarial Watermark for Combating Deepfakes

1 code implementation23 May 2021 Hao Huang, Yongtao Wang, Zhaoyu Chen, Yuze Zhang, Yuheng Li, Zhi Tang, Wei Chu, Jingdong Chen, Weisi Lin, Kai-Kuang Ma

Then, we design a two-level perturbation fusion strategy to alleviate the conflict between the adversarial watermarks generated by different facial images and models.

Adversarial Attack Face Swapping

PairRE: Knowledge Graph Embeddings via Paired Relation Vectors

1 code implementation ACL 2021 Linlin Chao, Jianshan He, Taifeng Wang, Wei Chu

Distance based knowledge graph embedding methods show promising results on link prediction task, on which two topics have been widely studied: one is the ability to handle complex relations, such as N-to-1, 1-to-N and N-to-N, the other is to encode various relation patterns, such as symmetry/antisymmetry.

Knowledge Graph Embedding Knowledge Graph Embeddings +1

CASS-NAT: CTC Alignment-based Single Step Non-autoregressive Transformer for Speech Recognition

no code implementations28 Oct 2020 Ruchao Fan, Wei Chu, Peng Chang, Jing Xiao

The information are used to extract acoustic representation for each token in parallel, referred to as token-level acoustic embedding which substitutes the word embedding in autoregressive transformer (AT) to achieve parallel generation in decoder.

Speech Recognition

Question Directed Graph Attention Network for Numerical Reasoning over Text

no code implementations EMNLP 2020 Kunlong Chen, Weidi Xu, Xingyi Cheng, Zou Xiaochuan, Yuyu Zhang, Le Song, Taifeng Wang, Yuan Qi, Wei Chu

Numerical reasoning over texts, such as addition, subtraction, sorting and counting, is a challenging machine reading comprehension task, since it requires both natural language understanding and arithmetic computation.

Graph Attention Machine Reading Comprehension +2

Generating Informative Conversational Response using Recurrent Knowledge-Interaction and Knowledge-Copy

no code implementations ACL 2020 Xiexiong Lin, Weiyu Jian, Jianshan He, Taifeng Wang, Wei Chu

Experiments demonstrate that our model with fewer parameters yields significant improvements over competitive baselines on two datasets Wizard-of-Wikipedia(average Bleu +87{\%}; abs.

Riemannian Proximal Policy Optimization

no code implementations19 May 2020 Shijun Wang, Baocheng Zhu, Chen Li, Mingzhe Wu, James Zhang, Wei Chu, Yuan Qi

In this paper, We propose a general Riemannian proximal optimization algorithm with guaranteed convergence to solve Markov decision process (MDP) problems.

SpellGCN: Incorporating Phonological and Visual Similarities into Language Models for Chinese Spelling Check

1 code implementation ACL 2020 Xingyi Cheng, Weidi Xu, Kunlong Chen, Shaohua Jiang, Feng Wang, Taifeng Wang, Wei Chu, Yuan Qi

This paper proposes to incorporate phonological and visual similarity knowledge into language models for CSC via a specialized graph convolutional network (SpellGCN).

Variational Policy Propagation for Multi-agent Reinforcement Learning

no code implementations19 Apr 2020 Chao Qu, Hui Li, Chang Liu, Junwu Xiong, James Zhang, Wei Chu, Weiqiang Wang, Yuan Qi, Le Song

We propose a \emph{collaborative} multi-agent reinforcement learning algorithm named variational policy propagation (VPP) to learn a \emph{joint} policy through the interactions over agents.

Multi-agent Reinforcement Learning reinforcement-learning +1

Symmetric Regularization based BERT for Pair-wise Semantic Reasoning

1 code implementation8 Sep 2019 Weidi Xu, Xingyi Cheng, Kunlong Chen, Wei Wang, Bin Bi, Ming Yan, Chen Wu, Luo Si, Wei Chu, Taifeng Wang

To remedy this, we propose to augment the NSP task to a 3-class categorization task, which includes a category for previous sentence prediction (PSP).

Machine Reading Comprehension Natural Language Inference +1

BERT-Based Multi-Head Selection for Joint Entity-Relation Extraction

1 code implementation16 Aug 2019 Weipeng Huang, Xingyi Cheng, Taifeng Wang, Wei Chu

Combining these three contributions, we enhance the information extracting ability of the multi-head selection model and achieve F1-score 0. 876 on testset-1 with a single model.

Relation Extraction

Singing voice conversion with non-parallel data

no code implementations11 Mar 2019 Xin Chen, Wei Chu, Jinxi Guo, Ning Xu

F0 and aperiodic are obtained through the original singing voice, and used with acoustic features to reconstruct the target singing voice through a vocoder.

Automatic Speech Recognition Voice Conversion

Toward Fast and Accurate Neural Chinese Word Segmentation with Multi-Criteria Learning

no code implementations11 Mar 2019 Weipeng Huang, Xingyi Cheng, Kunlong Chen, Taifeng Wang, Wei Chu

The ambiguous annotation criteria lead to divergence of Chinese Word Segmentation (CWS) datasets in various granularities.

Chinese Word Segmentation Quantization

BandNet: A Neural Network-based, Multi-Instrument Beatles-Style MIDI Music Composition Machine

no code implementations18 Dec 2018 Yichao Zhou, Wei Chu, Sam Young, Xin Chen

In the learning stage, a sequence of stylistically uniform, multiple-channel music samples was modeled by a RNN.

Reinforcement Learning for Uplift Modeling

1 code implementation26 Nov 2018 Chenchen Li, Xiang Yan, Xiaotie Deng, Yuan Qi, Wei Chu, Le Song, Junlong Qiao, Jianshan He, Junwu Xiong

Uplift modeling aims to directly model the incremental impact of a treatment on an individual response.

reinforcement-learning

A Novel Integrated Framework for Learning both Text Detection and Recognition

no code implementations21 Nov 2018 Wanchen Sui, Qing Zhang, Jun Yang, Wei Chu

In this paper, we propose a novel integrated framework for learning both text detection and recognition.

Variational Semi-supervised Aspect-term Sentiment Analysis via Transformer

no code implementations CONLL 2019 Xingyi Cheng, Weidi Xu, Taifeng Wang, Wei Chu

By disentangling the latent representation into the aspect-specific sentiment and the lexical context, our method induces the underlying sentiment prediction for the unlabeled data, which then benefits the ATSA classifier.

Aspect-Based Sentiment Analysis Natural Language Understanding +1

Latent Dirichlet Allocation for Internet Price War

no code implementations23 Aug 2018 Chenchen Li, Xiang Yan, Xiaotie Deng, Yuan Qi, Wei Chu, Le Song, Junlong Qiao, Jianshan He, Junwu Xiong

Then we develop a variant of Latent Dirichlet Allocation (LDA) to infer latent variables under the current market environment, which represents the preferences of customers and strategies of competitors.

Hybrid CTC-Attention based End-to-End Speech Recognition using Subword Units

no code implementations13 Jul 2018 Zhangyu Xiao, Zhijian Ou, Wei Chu, Hui Lin

In this paper, we present an end-to-end automatic speech recognition system, which successfully employs subword units in a hybrid CTC-Attention based system.

Automatic Speech Recognition

Modelling Domain Relationships for Transfer Learning on Retrieval-based Question Answering Systems in E-commerce

1 code implementation23 Nov 2017 Jianfei Yu, Minghui Qiu, Jing Jiang, Jun Huang, Shuangyong Song, Wei Chu, Haiqing Chen

In this paper, we study transfer learning for the PI and NLI problems, aiming to propose a general framework, which can effectively and efficiently adapt the shared knowledge learned from a resource-rich source domain to a resource- poor target domain.

Chatbot Natural Language Inference +3

AliMe Chat: A Sequence to Sequence and Rerank based Chatbot Engine

no code implementations ACL 2017 Minghui Qiu, Feng-Lin Li, Siyu Wang, Xing Gao, Yan Chen, Weipeng Zhao, Haiqing Chen, Jun Huang, Wei Chu

We propose AliMe Chat, an open-domain chatbot engine that integrates the joint results of Information Retrieval (IR) and Sequence to Sequence (Seq2Seq) based generation models.

Chatbot Information Retrieval

Speaker Cluster-Based Speaker Adaptive Training for Deep Neural Network Acoustic Modeling

no code implementations20 Apr 2016 Wei Chu, Ruxin Chen

The previously trained DNN of the matched speaker cluster is used for decoding utterances of the test speaker.

Speech Recognition

Unbiased Offline Evaluation of Contextual-bandit-based News Article Recommendation Algorithms

4 code implementations31 Mar 2010 Lihong Li, Wei Chu, John Langford, Xuanhui Wang

\emph{Offline} evaluation of the effectiveness of new algorithms in these applications is critical for protecting online user experiences but very challenging due to their "partial-label" nature.

News Recommendation Recommendation Systems

A Contextual-Bandit Approach to Personalized News Article Recommendation

11 code implementations28 Feb 2010 Lihong Li, Wei Chu, John Langford, Robert E. Schapire

In this work, we model personalized recommendation of news articles as a contextual bandit problem, a principled approach in which a learning algorithm sequentially selects articles to serve users based on contextual information about the users and articles, while simultaneously adapting its article-selection strategy based on user-click feedback to maximize total user clicks.

Collaborative Filtering Learning Theory

Gaussian Process Models for Link Analysis and Transfer Learning

no code implementations NeurIPS 2007 Kai Yu, Wei Chu

In this paper we develop a Gaussian process (GP) framework to model a collection of reciprocal random variables defined on the \emph{edges} of a network.

Link Prediction Transfer Learning

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