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05/25/2023
Generating Synergistic Formulaic Alpha Collections via Reinforcement Learning
In the field of quantitative trading, it is common practice to transform...
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05/06/2023
Attacking Pre-trained Recommendation
Recently, a series of pioneer studies have shown the potency of pre-trai...
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03/01/2023
Synthetic Cross-accent Data Augmentation for Automatic Speech Recognition
The awareness for biased ASR datasets or models has increased notably in...
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11/23/2022
Voice-preserving Zero-shot Multiple Accent Conversion
Most people who have tried to learn a foreign language would have experi...
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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...
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06/30/2022
Customized Conversational Recommender Systems
Conversational recommender systems (CRS) aim to capture user's current i...
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05/19/2022
Personalized Prompts for Sequential Recommendation
Pre-training models have shown their power in sequential recommendation....
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05/10/2022
Selective Fairness in Recommendation via Prompts
Recommendation fairness has attracted great attention recently. In real-...
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04/20/2022
User-Centric Conversational Recommendation with Multi-Aspect User Modeling
Conversational recommender systems (CRS) aim to provide highquality reco...
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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 ...
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03/20/2022
Multi-view Multi-behavior Contrastive Learning in Recommendation
Multi-behavior recommendation (MBR) aims to jointly consider multiple be...
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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...
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01/04/2022
Multi-Representation Adaptation Network for Cross-domain Image Classification
In image classification, it is often expensive and time-consuming to acq...
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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 ...
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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...
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12/31/2021
Domain Adaptation with Category Attention Network for Deep Sentiment Analysis
Domain adaptation tasks such as cross-domain sentiment classification ai...
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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...
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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...
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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-...
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10/21/2021
Personalized Transfer of User Preferences for Cross-domain Recommendation
Cold-start problem is still a very challenging problem in recommender sy...
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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 ...
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09/01/2021
ConRPG: Paraphrase Generation using Contexts as Regularizer
A long-standing issue with paraphrase generation is how to obtain reliab...
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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...
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07/18/2021
GuideBoot: Guided Bootstrap for Deep Contextual Bandits
The exploration/exploitation (E E) dilemma lies at the core of interac...
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07/12/2021
Direct speech-to-speech translation with discrete units
We present a direct speech-to-speech translation (S2ST) model that trans...
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06/30/2021
ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin Information
Recent pretraining models in Chinese neglect two important aspects speci...
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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...
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05/11/2021
Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users
Cold-start problems are enormous challenges in practical recommender sys...
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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 ...
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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...
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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-...
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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...
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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...
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07/12/2020
Graph Factorization Machines for Cross-Domain Recommendation
Recently, graph neural networks (GNNs) have been successfully applied to...
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02/28/2020
A Survey on Knowledge Graph-Based Recommender Systems
To solve the information explosion problem and enhance user experience i...
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11/20/2019
Transfer Learning Toolkit: Primers and Benchmarks
The transfer learning toolkit wraps the codes of 17 transfer learning mo...
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11/07/2019
A Comprehensive Survey on Transfer Learning
Transfer learning aims at improving the performance of target learners o...
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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...
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10/10/2019
Learning beyond Predefined Label Space via Bayesian Nonparametric Topic Modelling
In real world machine learning applications, testing data may contain so...
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07/26/2019
Detection of Malfunctioning Smart Electricity Meter
In this paper, a method for malfunctioning smart meter detection, based ...
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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...
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05/14/2019
Atom Responding Machine for Dialog Generation
Recently, improving the relevance and diversity of dialogue system has a...
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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...
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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...
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04/21/2019
Web Based Brain Volume Calculation for Magnetic Resonance Images
Brain volume calculations are crucial in modern medical research, especi...
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11/18/2018
Policy Optimization with Model-based Explorations
Model-free reinforcement learning methods such as the Proximal Policy Op...
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08/22/2018
Hierarchical Neural Network for Extracting Knowledgeable Snippets and Documents
In this study, we focus on extracting knowledgeable snippets and annotat...
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05/19/2018
Free-rider Episode Screening via Dual Partition Model
One of the drawbacks of frequent episode mining is that overwhelmingly m...
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03/05/2018
Cross-domain novelty seeking trait mining for sequential recommendation
Transfer learning has attracted a large amount of interest and research ...
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02/12/2018