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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...
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06/13/2023
Multi-Fidelity Multi-Armed Bandits Revisited
We study the multi-fidelity multi-armed bandit (MF-MAB), an extension of...
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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...
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06/02/2023
An Empirical Study on Challenging Math Problem Solving with GPT-4
Employing Large Language Models (LLMs) to address mathematical problems ...
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05/28/2023
HyperTime: Hyperparameter Optimization for Combating Temporal Distribution Shifts
In this work, we propose a hyperparameter optimization method named Hype...
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06/29/2022
Provably Efficient Reinforcement Learning for Online Adaptive Influence Maximization
Online influence maximization aims to maximize the influence spread of a...
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11/11/2021
Fair AutoML
We present an end-to-end automated machine learning system to find machi...
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06/09/2021
ChaCha for Online AutoML
We propose the ChaCha (Champion-Challengers) algorithm for making an onl...
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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...
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09/05/2020
Unifying Clustered and Non-stationary Bandits
Non-stationary bandits and online clustering of bandits lift the restric...
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07/16/2020
Fast Distributed Bandits for Online Recommendation Systems
Contextual bandit algorithms are commonly used in recommender systems, w...
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05/23/2020
Seamlessly Unifying Attributes and Items: Conversational Recommendation for Cold-Start Users
Static recommendation methods like collaborative filtering suffer from t...
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05/04/2020
Cost Effective Optimization for Cost-related Hyperparameters
The increasing demand for democratizing machine learning algorithms for ...
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02/21/2020
Estimation-Action-Reflection: Towards Deep Interaction Between Conversational and Recommender Systems
Recommender systems are embracing conversational technologies to obtain ...
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11/12/2019
FLO: Fast and Lightweight Hyperparameter Optimization for AutoML
Integrating ML models in software is of growing interest. Building accur...
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06/10/2019
Variance Reduction in Gradient Exploration for Online Learning to Rank
Online Learning to Rank (OL2R) algorithms learn from implicit user feedb...
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06/09/2019
Factorization Bandits for Online Influence Maximization
We study the problem of online influence maximization in social networks...
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05/23/2018