b'Qing He'

research

∙ 05/25/2023

Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning

In the field of quantitative trading, it is common practice to transform...

0 Shuo Yu, et al. ∙

research

∙ 05/06/2023

Attacking Pre-trained Recommendation

Recently, a series of pioneer studies have shown the potency of pre-trai...

0 Yiqing Wu, et al. ∙

research

∙ 03/01/2023

Synthetic Cross-accent Data Augmentation for Automatic Speech Recognition

The awareness for biased ASR datasets or models has increased notably in...

0 Philipp Klumpp, et al. ∙

research

∙ 11/23/2022

Voice-preserving Zero-shot Multiple Accent Conversion

Most people who have tried to learn a foreign language would have experi...

0 Mumin Jin, et al. ∙

research

∙ 10/28/2022

Towards zero-shot Text-based voice editing using acoustic context conditioning, utterance embeddings, and reference encoders

Text-based voice editing (TBVE) uses synthetic output from text-to-speec...

5 Jason Fong, et al. ∙

research

∙ 06/30/2022

Customized Conversational Recommender Systems

Conversational recommender systems (CRS) aim to capture user's current i...

0 Shuokai Li, et al. ∙

research

∙ 05/19/2022

Personalized Prompts for Sequential Recommendation

Pre-training models have shown their power in sequential recommendation....

1 Yiqing Wu, et al. ∙

research

∙ 05/10/2022

Selective Fairness in Recommendation via Prompts

Recommendation fairness has attracted great attention recently. In real-...

0 Yiqing Wu, et al. ∙

research

∙ 04/20/2022

User-Centric Conversational Recommendation with Multi-Aspect User Modeling

Conversational recommender systems (CRS) aim to provide highquality reco...

0 Shuokai Li, et al. ∙

research

∙ 04/06/2022

CCAT-NET: A Novel Transformer Based Semi-supervised Framework for Covid-19 Lung Lesion Segmentation

The spread of the novel coronavirus disease 2019 (COVID-19) has claimed ...

0 Mingyang Liu, et al. ∙

research

∙ 03/20/2022

Multi-view Multi-behavior Contrastive Learning in Recommendation

Multi-behavior recommendation (MBR) aims to jointly consider multiple be...

0 Yiqing Wu, et al. ∙

research

∙ 01/04/2022

Modeling Users' Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection

With the explosive growth of the e-commerce industry, detecting online t...

2 Yongchun Zhu, et al. ∙

research

∙ 01/04/2022

Multi-Representation Adaptation Network for Cross-domain Image Classification

In image classification, it is often expensive and time-consuming to acq...

0 Yongchun Zhu, et al. ∙

research

∙ 12/31/2021

Exploiting Bi-directional Global Transition Patterns and Personal Preferences for Missing POI Category Identification

Recent years have witnessed the increasing popularity of Location-based ...

0 Dongbo Xi, et al. ∙

research

∙ 12/31/2021

Neural Hierarchical Factorization Machines for User's Event Sequence Analysis

Many prediction tasks of real-world applications need to model multi-ord...

1 Dongbo Xi, et al. ∙

research

∙ 12/31/2021

Domain Adaptation with Category Attention Network for Deep Sentiment Analysis

Domain adaptation tasks such as cross-domain sentiment classification ai...

0 Dongbo Xi, et al. ∙

research

∙ 12/31/2021

Modelling of Bi-directional Spatio-Temporal Dependence and Users' Dynamic Preferences for Missing POI Check-in Identification

Human mobility data accumulated from Point-of-Interest (POI) check-ins p...

0 Dongbo Xi, et al. ∙

research

∙ 12/27/2021

Mind the Gap: Cross-Lingual Information Retrieval with Hierarchical Knowledge Enhancement

Cross-Lingual Information Retrieval (CLIR) aims to rank the documents wr...

7 Fuwei Zhang, et al. ∙

research

∙ 11/11/2021

Towards Robust Knowledge Graph Embedding via Multi-task Reinforcement Learning

Nowadays, Knowledge graphs (KGs) have been playing a pivotal role in AI-...

0 Zhao Zhang, et al. ∙

research

∙ 10/21/2021

Personalized Transfer of User Preferences for Cross-domain Recommendation

Cold-start problem is still a very challenging problem in recommender sy...

0 Yongchun Zhu, et al. ∙

research

∙ 09/10/2021

A structure preserving numerical scheme for Fokker-Planck equations of structured neural networks with learning rules

In this work, we are concerned with a Fokker-Planck equation related to ...

0 Qing He, et al. ∙

research

∙ 09/01/2021

ConRPG: Paraphrase Generation using Contexts as Regularizer

A long-standing issue with paraphrase generation is how to obtain reliab...

0 Yuxian Meng, et al. ∙

research

∙ 08/13/2021

Follow the Prophet: Accurate Online Conversion Rate Prediction in the Face of Delayed Feedback

The delayed feedback problem is one of the imperative challenges in onli...

0 Haoming Li, et al. ∙

research

∙ 07/18/2021

GuideBoot: Guided Bootstrap for Deep Contextual Bandits

The exploration/exploitation (E E) dilemma lies at the core of interac...

0 Feiyang Pan, et al. ∙

research

∙ 07/12/2021

Direct speech-to-speech translation with discrete units

We present a direct speech-to-speech translation (S2ST) model that trans...

0 Ann Lee, et al. ∙

research

∙ 06/30/2021

ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin Information

Recent pretraining models in Chinese neglect two important aspects speci...

0 Zijun Sun, et al. ∙

research

∙ 06/16/2021

AMA-GCN: Adaptive Multi-layer Aggregation Graph Convolutional Network for Disease Prediction

Recently, Graph Convolutional Networks (GCNs) have proven to be a powerf...

0 Hao Chen, et al. ∙

research

∙ 05/11/2021

Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users

Cold-start problems are enormous challenges in practical recommender sys...

0 Yongchun Zhu, et al. ∙

research

∙ 04/01/2021

Multi-rate attention architecture for fast streamable Text-to-speech spectrum modeling

Typical high quality text-to-speech (TTS) systems today use a two-stage ...

0 Qing He, et al. ∙

research

∙ 01/27/2021

Combat Data Shift in Few-shot Learning with Knowledge Graph

Many few-shot learning approaches have been designed under the meta-lear...

2 Yongchun Zhu, et al. ∙

research

∙ 11/25/2020

FBWave: Efficient and Scalable Neural Vocoders for Streaming Text-To-Speech on the Edge

Nowadays more and more applications can benefit from edge-based text-to-...

0 Bichen Wu, et al. ∙

research

∙ 10/10/2020

Trust the Model When It Is Confident: Masked Model-based Actor-Critic

It is a popular belief that model-based Reinforcement Learning (RL) is m...

11 Feiyang Pan, et al. ∙

research

∙ 08/08/2020

Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection

With the explosive growth of e-commerce, online transaction fraud has be...

0 Dongbo Xi, et al. ∙

research

∙ 07/12/2020

Graph Factorization Machines for Cross-Domain Recommendation

Recently, graph neural networks (GNNs) have been successfully applied to...

1 Dongbo Xi, et al. ∙

research

∙ 02/28/2020

A Survey on Knowledge Graph-Based Recommender Systems

To solve the information explosion problem and enhance user experience i...

0 Qingyu Guo, et al. ∙

research

∙ 11/20/2019

Transfer Learning Toolkit: Primers and Benchmarks

The transfer learning toolkit wraps the codes of 17 transfer learning mo...

0 Fuzhen Zhuang, et al. ∙

research

∙ 11/07/2019

A Comprehensive Survey on Transfer Learning

Transfer learning aims at improving the performance of target learners o...

76 Fuzhen Zhuang, et al. ∙

research

∙ 10/11/2019

Efficient and Adaptive Kernelization for Nonlinear Max-margin Multi-view Learning

Existing multi-view learning methods based on kernel function either req...

0 Changying Du, et al. ∙

research

∙ 10/10/2019

Learning beyond Predefined Label Space via Bayesian Nonparametric Topic Modelling

In real world machine learning applications, testing data may contain so...

14 Changying Du, et al. ∙

research

∙ 07/26/2019

Detection of Malfunctioning Smart Electricity Meter

In this paper, a method for malfunctioning smart meter detection, based ...

0 Ming Liu, et al. ∙

research

∙ 05/26/2019

Towards reliable and fair probabilistic predictions: field-aware calibration with neural networks

In machine learning, it is observed that probabilistic predictions somet...

0 Feiyang Pan, et al. ∙

research

∙ 05/14/2019

Atom Responding Machine for Dialog Generation

Recently, improving the relevance and diversity of dialogue system has a...

0 Ganbin Zhou, et al. ∙

research

∙ 04/25/2019

Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings

Click-through rate (CTR) prediction has been one of the most central pro...

0 Feiyang Pan, et al. ∙

research

∙ 04/21/2019

A Fast, Semi-Automatic Brain Structure Segmentation Algorithm for Magnetic Resonance Imaging

Medical image segmentation has become an essential technique in clinical...

0 Kevin Karsch, et al. ∙

research

∙ 04/21/2019

Web Based Brain Volume Calculation for Magnetic Resonance Images

Brain volume calculations are crucial in modern medical research, especi...

0 Kevin Karsch, et al. ∙

research

∙ 11/18/2018

Policy Optimization with Model-based Explorations

Model-free reinforcement learning methods such as the Proximal Policy Op...

0 Feiyang Pan, et al. ∙

research

∙ 08/22/2018

Hierarchical Neural Network for Extracting Knowledgeable Snippets and Documents

In this study, we focus on extracting knowledgeable snippets and annotat...

0 Ganbin Zhou, et al. ∙

research

∙ 05/19/2018

Free-rider Episode Screening via Dual Partition Model

One of the drawbacks of frequent episode mining is that overwhelmingly m...

0 Xiang Ao, et al. ∙

research

∙ 03/05/2018

Cross-domain novelty seeking trait mining for sequential recommendation

Transfer learning has attracted a large amount of interest and research ...

0 Fuzhen Zhuang, et al. ∙

research

∙ 02/12/2018

Policy Gradients for Contextual Bandits

We study a generalized contextual-bandits problem, where there is a stat...

0 Feiyang Pan, et al. ∙

Qing He

Featured Co-authors