Qingyun Wu | DeepAI

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Featured Co-authors

Wei Chen
332 publications
Yue Wang
263 publications
Tat-Seng Chua
173 publications
Xiangnan He
124 publications
Shuai Li
104 publications
Yu Wu
98 publications
Mengdi Wang
91 publications
Yin Tat Lee
64 publications
Peng Jiang
59 publications
John Langford
58 publications
Hongning Wang
55 publications

∙ 08/16/2023

AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework

This technical report presents AutoGen, a new framework that enables dev...

0 Qingyun Wu, et al. ∙

∙ 06/13/2023

Multi-Fidelity Multi-Armed Bandits Revisited

We study the multi-fidelity multi-armed bandit (MF-MAB), an extension of...

7 Xuchuang Wang, et al. ∙

∙ 06/13/2023

Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective

Off-policy Learning to Rank (LTR) aims to optimize a ranker from data co...

7 Zeyu Zhang, et al. ∙

∙ 06/02/2023

An Empirical Study on Challenging Math Problem Solving with GPT-4

Employing Large Language Models (LLMs) to address mathematical problems ...

0 Yiran Wu, et al. ∙

∙ 05/28/2023

HyperTime: Hyperparameter Optimization for Combating Temporal Distribution Shifts

In this work, we propose a hyperparameter optimization method named Hype...

0 Shaokun Zhang, et al. ∙

∙ 06/29/2022

Provably Efficient Reinforcement Learning for Online Adaptive Influence Maximization

Online influence maximization aims to maximize the influence spread of a...

3 Kaixuan Huang, et al. ∙

∙ 11/11/2021

Fair AutoML

We present an end-to-end automated machine learning system to find machi...

10 Qingyun Wu, et al. ∙

∙ 06/09/2021

ChaCha for Online AutoML

We propose the ChaCha (Champion-Challengers) algorithm for making an onl...

0 Qingyun Wu, et al. ∙

∙ 04/14/2021

When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution

Collaborative bandit learning, i.e., bandit algorithms that utilize coll...

5 Chuanhao Li, et al. ∙

∙ 09/05/2020

Unifying Clustered and Non-stationary Bandits

Non-stationary bandits and online clustering of bandits lift the restric...

4 Chuanhao Li, et al. ∙

∙ 07/16/2020

Fast Distributed Bandits for Online Recommendation Systems

Contextual bandit algorithms are commonly used in recommender systems, w...

0 Kanak Mahadik, et al. ∙

∙ 05/23/2020

Seamlessly Unifying Attributes and Items: Conversational Recommendation for Cold-Start Users

Static recommendation methods like collaborative filtering suffer from t...

0 Shijun Li, et al. ∙

∙ 05/04/2020

Cost Effective Optimization for Cost-related Hyperparameters

The increasing demand for democratizing machine learning algorithms for ...

2 Qingyun Wu, et al. ∙

∙ 02/21/2020

Estimation-Action-Reflection: Towards Deep Interaction Between Conversational and Recommender Systems

Recommender systems are embracing conversational technologies to obtain ...

0 Wenqiang Lei, et al. ∙

∙ 11/12/2019

FLO: Fast and Lightweight Hyperparameter Optimization for AutoML

Integrating ML models in software is of growing interest. Building accur...

58 Chi Wang, et al. ∙

∙ 06/10/2019

Variance Reduction in Gradient Exploration for Online Learning to Rank

Online Learning to Rank (OL2R) algorithms learn from implicit user feedb...

0 Huazheng Wang, et al. ∙

∙ 06/09/2019

Factorization Bandits for Online Influence Maximization

We study the problem of online influence maximization in social networks...

0 Qingyun Wu, et al. ∙

∙ 05/23/2018

Learning Contextual Bandits in a Non-stationary Environment

Multi-armed bandit algorithms have become a reference solution for handl...

0 Qingyun Wu, et al. ∙

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