Fangkai Yang | DeepAI

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Jun Wang
360 publications
Bo Liu
167 publications
Peter Stone
126 publications
Yuan Gao
112 publications
Shuang Li
106 publications
Lu Wang
104 publications
Dongmei Zhang
84 publications
Shiqi Zhang
45 publications
Joohyung Lee
32 publications
Bo Jin
29 publications
Pu Zhao
29 publications

∙ 08/03/2023

Diffusion-based Time Series Data Imputation for Microsoft 365

Reliability is extremely important for large-scale cloud systems like Mi...

0 Fangkai Yang, et al. ∙

∙ 05/19/2023

Introspective Tips: Large Language Model for In-Context Decision Making

The emergence of large language models (LLMs) has substantially influenc...

1 Liting Chen, et al. ∙

∙ 05/19/2023

Empower Large Language Model to Perform Better on Industrial Domain-Specific Question Answering

Large Language Model (LLM) has gained popularity and achieved remarkable...

0 Zezhong Wang, et al. ∙

∙ 11/21/2022

Learning Cooperative Oversubscription for Cloud by Chance-Constrained Multi-Agent Reinforcement Learning

Oversubscription is a common practice for improving cloud resource utili...

0 Junjie Sheng, et al. ∙

∙ 08/13/2021

TDM: Trustworthy Decision-Making via Interpretability Enhancement

Human-robot interactive decision-making is increasingly becoming ubiquit...

0 Daoming Lyu, et al. ∙

∙ 09/18/2019

A Human-Centered Data-Driven Planner-Actor-Critic Architecture via Logic Programming

Recent successes of Reinforcement Learning (RL) allow an agent to learn ...

0 Daoming Lyu, et al. ∙

∙ 09/17/2019

Proceedings 35th International Conference on Logic Programming (Technical Communications)

Since the first conference held in Marseille in 1982, ICLP has been the ...

0 Bart Bogaerts, et al. ∙

∙ 08/10/2019

Introduction to the 35th International Conference on Logic Programming Special Issue

We are proud to introduce this special issue of Theory and Practice of L...

0 Esra Erdem, et al. ∙

∙ 06/17/2019

PACMAN: A Planner-Actor-Critic Architecture for Human-Centered Planning and Learning

Conventional reinforcement learning (RL) allows an agent to learn polici...

5 Daoming Lyu, et al. ∙

∙ 05/06/2019

Interpretable Automated Machine Learning in Maana(TM) Knowledge Platform

Machine learning is becoming an essential part of developing solutions f...

0 Alexander Elkholy, et al. ∙

∙ 11/21/2018

Integrating Task-Motion Planning with Reinforcement Learning for Robust Decision Making in Mobile Robots

Task-motion planning (TMP) addresses the problem of efficiently generati...

0 Yuqian Jiang, et al. ∙

∙ 10/31/2018

SDRL: Interpretable and Data-efficient Deep Reinforcement Learning Leveraging Symbolic Planning

Deep reinforcement learning (DRL) has gained great success by learning d...

0 Daoming Lyu, et al. ∙

∙ 10/31/2018

SDRL: Interpretable and Data-efficient Deep Reinforcement LearningLeveraging Symbolic Planning

Deep reinforcement learning (DRL) has gained great success by learning d...

0 Daoming Lyu, et al. ∙

∙ 10/16/2018

Social Behavior Learning with Realistic Reward Shaping

Deep reinforcement learning has been widely applied in the field of robo...

0 Yuan Gao, et al. ∙

∙ 04/20/2018

PEORL: Integrating Symbolic Planning and Hierarchical Reinforcement Learning for Robust Decision-Making

Reinforcement learning and symbolic planning have both been used to buil...

0 Fangkai Yang, et al. ∙

∙ 12/20/2013

On the Semantics of Gringo

Input languages of answer set solvers are based on the mathematically si...

0 Amelia Harrison, et al. ∙

∙ 01/08/2013

Lloyd-Topor Completion and General Stable Models

We investigate the relationship between the generalization of program co...

0 Vladimir Lifschitz, et al. ∙

∙ 10/15/2012

Relational Theories with Null Values and Non-Herbrand Stable Models

Generalized relational theories with null values in the sense of Reiter ...

0 Vladimir Lifschitz, et al. ∙

∙ 03/23/2011

Representing First-Order Causal Theories by Logic Programs

Nonmonotonic causal logic, introduced by Norman McCain and Hudson Turner...

0 Paolo Ferraris, et al. ∙

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