Publications

Utilization of deep reinforcement learning for discrete resource allocation problem in project management – a simulation experiment

This paper tests the applicability of deep reinforcement learning (DRL) algorithms to simulated problems of constrained discrete and online resource allocation in project management

Filip Wójcik

Utilization of deep reinforcement learning for discrete resource allocation problem in project management – a simulation experiment

Usage of deep neural networks as recommendation engines. Review of selected approaches

Presentation of modern architectures of deep learning algorithms as recommendation engines

Filip Wójcik

Usage of deep neural networks as recommendation engines. Review of selected approaches

Beyond the barrier of mistrust – an overview of selected methods for explaining predictions of machine learning models

Presentation of modern explainable artificial intelligence approaches.

Filip Wójcik

Beyond the barrier of mistrust – an overview of selected methods for explaining predictions of machine learning models

Improvement of e-commerce recommendation systems with deep hybrid collaborative filtering with content: A case study

A presentation of new algorithm for recommendations with hybrid deep learning architecture

Filip Wójcik, Michał Górnik

Improvement of e-commerce recommendation systems with deep hybrid collaborative filtering with content: A case study

Forecasting Daily Turnover Using Xgboost Algorithm – A Case Study

Analysis of XGBoost applications to financial forecasting and sales management.

Filip Wójcik

Forecasting Daily Turnover Using Xgboost Algorithm – A Case Study

Detecting business-relevant attributes in rule-based classification

Modern decision support systems make use of machine learning and artificial intelligence to solve complicated problems. One of them is …

dr hab. Iwona Chomiak-Orsa, prof. UE, Filip Wójcik

Detecting business-relevant attributes in rule-based classification