Lei Song
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View article: Monte Carlo Tree Search based Space Transfer for Black-box Optimization
Monte Carlo Tree Search based Space Transfer for Black-box Optimization Open
Bayesian optimization (BO) is a popular method for computationally expensive black-box optimization. However, traditional BO methods need to solve new problems from scratch, leading to slow convergence. Recent studies try to extend BO to a…
View article: Α Descent-based Method on the Duality Gap for Solving Zero-sum Games
Α Descent-based Method on the Duality Gap for Solving Zero-sum Games Open
We focus on the design of algorithms for finding equilibria in 2-player zero-sum games. Although it is well known that such problems can be solved by a single linear program, there has been a surge of interest in recent years for simpler a…
View article: Stochastic Bayesian Optimization with Unknown Continuous Context Distribution via Kernel Density Estimation
Stochastic Bayesian Optimization with Unknown Continuous Context Distribution via Kernel Density Estimation Open
Bayesian optimization (BO) is a sample-efficient method and has been widely used for optimizing expensive black-box functions. Recently, there has been a considerable interest in BO literature in optimizing functions that are affected by c…
View article: Stochastic Bayesian Optimization with Unknown Continuous Context Distribution via Kernel Density Estimation
Stochastic Bayesian Optimization with Unknown Continuous Context Distribution via Kernel Density Estimation Open
Bayesian optimization (BO) is a sample-efficient method and has been widely used for optimizing expensive black-box functions. Recently, there has been a considerable interest in BO literature in optimizing functions that are affected by c…
View article: A Versatile Multi-Agent Reinforcement Learning Benchmark for Inventory Management
A Versatile Multi-Agent Reinforcement Learning Benchmark for Inventory Management Open
Multi-agent reinforcement learning (MARL) models multiple agents that interact and learn within a shared environment. This paradigm is applicable to various industrial scenarios such as autonomous driving, quantitative trading, and invento…
View article: Personal safety risk analysis of power enterprises under the background of new power system
Personal safety risk analysis of power enterprises under the background of new power system Open
Personal safety risk management is one of the important components of power enterprise safety management. The key is to quantify the risk value. Based on the accident cause theory, combined with the particularity of the subject, object and…
View article: Drug repositioning based on heterogeneous networks and variational graph autoencoders
Drug repositioning based on heterogeneous networks and variational graph autoencoders Open
Predicting new therapeutic effects (drug repositioning) of existing drugs plays an important role in drug development. However, traditional wet experimental prediction methods are usually time-consuming and costly. The emergence of more an…
View article: Multi-Agent Reinforcement Learning with Shared Resources for Inventory Management
Multi-Agent Reinforcement Learning with Shared Resources for Inventory Management Open
In this paper, we consider the inventory management (IM) problem where we need to make replenishment decisions for a large number of stock keeping units (SKUs) to balance their supply and demand. In our setting, the constraint on the share…
View article: TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets
TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets Open
We consider an offline reinforcement learning (RL) setting where the agent need to learn from a dataset collected by rolling out multiple behavior policies. There are two challenges for this setting: 1) The optimal trade-off between optimi…
View article: Monte Carlo Tree Search based Variable Selection for High Dimensional Bayesian Optimization
Monte Carlo Tree Search based Variable Selection for High Dimensional Bayesian Optimization Open
Bayesian optimization (BO) is a class of popular methods for expensive black-box optimization, and has been widely applied to many scenarios. However, BO suffers from the curse of dimensionality, and scaling it to high-dimensional problems…
View article: A Research on the Sharing Platform of Wild Bird Data in Yunnan Province Based on Blockchain and Interstellar File System
A Research on the Sharing Platform of Wild Bird Data in Yunnan Province Based on Blockchain and Interstellar File System Open
Sharing scientific data is an effective means to rationally exploit scientific data and is vital to promote the development of the industrial chain and improve the level of science and technology. In recent years, the popularity of the ope…
View article: Evidence Mechanism of Power Dispatching Instruction Based on Blockchain
Evidence Mechanism of Power Dispatching Instruction Based on Blockchain Open
With the development and application of energy Internet technology, the collaborative interaction of "source network, load and storage" has become the development trend of power grid dispatching. The large-scale access of renewable energy …