b'Yong Yu'

research

∙ 09/08/2023

CSPRD: A Financial Policy Retrieval Dataset for Chinese Stock Market

In recent years, great advances in pre-trained language models (PLMs) ha...

0 Jinyuan Wang, et al. ∙

research

∙ 08/22/2023

ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation

With large language models (LLMs) achieving remarkable breakthroughs in ...

0 Jianghao Lin, et al. ∙

research

∙ 08/03/2023

MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction

With the widespread application of personalized online services, click-t...

0 Jianghao Lin, et al. ∙

research

∙ 06/09/2023

How Can Recommender Systems Benefit from Large Language Models: A Survey

Recommender systems (RS) play important roles to match users' informatio...

0 Jianghao Lin, et al. ∙

research

∙ 05/27/2023

MADiff: Offline Multi-agent Learning with Diffusion Models

Diffusion model (DM), as a powerful generative model, recently achieved ...

0 Zhengbang Zhu, et al. ∙

research

∙ 12/15/2022

Sim-to-Real Transfer for Quadrupedal Locomotion via Terrain Transformer

Deep reinforcement learning has recently emerged as an appealing alterna...

0 Hang Lai, et al. ∙

research

∙ 12/14/2022

Cross-Channel: Scalable Off-Chain Channels Supporting Fair and Atomic Cross-Chain Operations

Cross-chain technology facilitates the interoperability among isolated b...

0 Yihao Guo, et al. ∙

research

∙ 11/07/2022

RITA: Boost Autonomous Driving Simulators with Realistic Interactive Traffic Flow

High-quality traffic flow generation is the core module in building simu...

0 Zhengbang Zhu, et al. ∙

research

∙ 10/11/2022

Understanding or Manipulation: Rethinking Online Performance Gains of Modern Recommender Systems

Recommender systems are expected to be assistants that help human users ...

0 Zhengbang Zhu, et al. ∙

research

∙ 07/26/2022

Branch Ranking for Efficient Mixed-Integer Programming via Offline Ranking-based Policy Learning

Deriving a good variable selection strategy in branch-and-bound is essen...

4 Zeren Huang, et al. ∙

research

∙ 07/09/2022

TensorIR: An Abstraction for Automatic Tensorized Program Optimization

Deploying deep learning models on various devices has become an importan...

0 Siyuan Feng, et al. ∙

research

∙ 06/17/2022

A Graph-Enhanced Click Model for Web Search

To better exploit search logs and model users' behavior patterns, numero...

0 Jianghao Lin, et al. ∙

research

∙ 03/04/2022

Plan Your Target and Learn Your Skills: Transferable State-Only Imitation Learning via Decoupled Policy Optimization

Recent progress in state-only imitation learning extends the scope of ap...

1 Minghuan Liu, et al. ∙

research

∙ 02/25/2022

Multi-View Graph Representation for Programming Language Processing: An Investigation into Algorithm Detection

Program representation, which aims at converting program source code int...

0 Ting Long, et al. ∙

research

∙ 01/27/2022

DropNAS: Grouped Operation Dropout for Differentiable Architecture Search

Neural architecture search (NAS) has shown encouraging results in automa...

0 Weijun Hong, et al. ∙

research

∙ 01/06/2022

Phrase-level Adversarial Example Generation for Neural Machine Translation

While end-to-end neural machine translation (NMT) has achieved impressiv...

0 Juncheng Wan, et al. ∙

research

∙ 11/16/2021

On Effective Scheduling of Model-based Reinforcement Learning

Model-based reinforcement learning has attracted wide attention due to i...

0 Hang Lai, et al. ∙

research

∙ 11/16/2021

QA4PRF: A Question Answering based Framework for Pseudo Relevance Feedback

Pseudo relevance feedback (PRF) automatically performs query expansion b...

0 Handong Ma, et al. ∙

research

∙ 11/09/2021

Learning Logic Rules for Document-level Relation Extraction

Document-level relation extraction aims to identify relations between en...

0 Dongyu Ru, et al. ∙

research

∙ 11/05/2021

AIM: Automatic Interaction Machine for Click-Through Rate Prediction

Feature embedding learning and feature interaction modeling are two cruc...

0 Chenxu Zhu, et al. ∙

research

∙ 10/18/2021

Context-aware Reranking with Utility Maximization for Recommendation

As a critical task for large-scale commercial recommender systems, reran...

0 Yunjia Xi, et al. ∙

research

∙ 08/16/2021

Task-wise Split Gradient Boosting Trees for Multi-center Diabetes Prediction

Diabetes prediction is an important data science application in the soci...

10 Mingcheng Chen, et al. ∙

research

∙ 08/11/2021

Retrieval Interaction Machine for Tabular Data Prediction

Prediction over tabular data is an essential task in many data science a...

0 Jiarui Qin, et al. ∙

research

∙ 05/28/2021

Learning to Select Cuts for Efficient Mixed-Integer Programming

Cutting plane methods play a significant role in modern solvers for tack...

8 Zeren Huang, et al. ∙

research

∙ 05/13/2021

MapGo: Model-Assisted Policy Optimization for Goal-Oriented Tasks

In Goal-oriented Reinforcement learning, relabeling the raw goals in pas...

0 Menghui Zhu, et al. ∙

research

∙ 04/13/2021

An Adversarial Imitation Click Model for Information Retrieval

Modern information retrieval systems, including web search, ads placemen...

0 Xinyi Dai, et al. ∙

research

∙ 03/18/2021

MARS: Markov Molecular Sampling for Multi-objective Drug Discovery

Searching for novel molecules with desired chemical properties is crucia...

16 Yutong Xie, et al. ∙

research

∙ 12/09/2020

Improving Knowledge Tracing via Pre-training Question Embeddings

Knowledge tracing (KT) defines the task of predicting whether students c...

0 Yunfei Liu, et al. ∙

research

∙ 12/07/2020

Sobolev Wasserstein GAN

Wasserstein GANs (WGANs), built upon the Kantorovich-Rubinstein (KR) dua...

10 Minkai Xu, et al. ∙

research

∙ 11/01/2020

U-rank: Utility-oriented Learning to Rank with Implicit Feedback

Learning to rank with implicit feedback is one of the most important tas...

0 Xinyi Dai, et al. ∙

research

∙ 10/21/2020

Efficient Projection-Free Algorithms for Saddle Point Problems

The Frank-Wolfe algorithm is a classic method for constrained optimizati...

0 Cheng Chen, et al. ∙

research

∙ 10/19/2020

Model-based Policy Optimization with Unsupervised Model Adaptation

Model-based reinforcement learning methods learn a dynamics model with r...

0 Jian Shen, et al. ∙

research

∙ 10/09/2020

AI Chiller: An Open IoT Cloud Based Machine Learning Framework for the Energy Saving of Building HVAC System via Big Data Analytics on the Fusion of BMS and Environmental Data

Energy saving and carbon emission reduction in buildings is one of the k...

0 Yong Yu, et al. ∙

research

∙ 09/17/2020

GeneraLight: Improving Environment Generalization of Traffic Signal Control via Meta Reinforcement Learning

The heavy traffic congestion problem has always been a concern for moder...

9 Chang Liu, et al. ∙

research

∙ 09/13/2020

GIKT: A Graph-based Interaction Model for Knowledge Tracing

With the rapid development in online education, knowledge tracing (KT) h...

20 Yang Yang, et al. ∙

research

∙ 08/18/2020

Glancing Transformer for Non-Autoregressive Neural Machine Translation

Non-autoregressive neural machine translation achieves remarkable infere...

0 Lihua Qian, et al. ∙

research

∙ 07/04/2020

Bidirectional Model-based Policy Optimization

Model-based reinforcement learning approaches leverage a forward dynamic...

8 Hang Lai, et al. ∙

research

∙ 06/18/2020

Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning

Interactive recommender system (IRS) has drawn huge attention because of...

0 Sijin Zhou, et al. ∙

research

∙ 04/17/2020

Active Sentence Learning by Adversarial Uncertainty Sampling in Discrete Space

In this paper, we focus on reducing the labeled data size for sentence l...

0 Dongyu Ru, et al. ∙

research

∙ 04/03/2020

Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip

Although Shannon theory states that it is asymptotically optimal to sepa...

0 Yuxuan Song, et al. ∙

research

∙ 03/25/2020

AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction

Learning effective feature interactions is crucial for click-through rat...

2 Bin Liu, et al. ∙

research

∙ 03/14/2020

Large-Scale Optimal Transport via Adversarial Training with Cycle-Consistency

Recent advances in large-scale optimal transport have greatly extended i...

16 Guansong Lu, et al. ∙

research

∙ 01/04/2020

Multi-Agent Interactions Modeling with Correlated Policies

In multi-agent systems, complex interacting behaviors arise due to the h...

0 Minghuan Liu, et al. ∙

research

∙ 11/21/2019

Improving Unsupervised Domain Adaptation with Variational Information Bottleneck

Domain adaptation aims to leverage the supervision signal of source doma...

0 Yuxuan Song, et al. ∙

research

∙ 11/10/2019

Sequential Recommendation with Dual Side Neighbor-based Collaborative Relation Modeling

Sequential recommendation task aims to predict user preference over item...

0 Jiarui Qin, et al. ∙

research

∙ 10/07/2019

Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matching

Improving the efficiency of dispatching orders to vehicles is a research...

0 Ming Zhou, et al. ∙

research

∙ 09/10/2019

Signal Instructed Coordination in Team Competition

Most existing models of multi-agent reinforcement learning (MARL) adopt ...

11 Liheng Chen, et al. ∙

research

∙ 09/10/2019

Signal Instructed Coordination in Cooperative Multi-agent Reinforcement Learning

In many real-world problems, a team of agents need to collaborate to max...

0 Liheng Chen, et al. ∙

research

∙ 08/15/2019

Towards Making the Most of BERT in Neural Machine Translation

GPT-2 and BERT demonstrate the effectiveness of using pre-trained langua...

0 Jiacheng Yang, et al. ∙

research

∙ 05/25/2019

Triple-to-Text: Converting RDF Triples into High-Quality Natural Languages via Optimizing an Inverse KL Divergence

Knowledge base is one of the main forms to represent information in a st...

0 Yaoming Zhu, et al. ∙

Yong Yu

Featured Co-authors