8 citations · 15 across the 9 of their papers we have counts for
9 papers
How to evaluate clustering with ground truth?
Pasi Fränti
External indexes can be used for cluster evaluation when ground truth is available. We review the most common external validity indexes focusing on set-matching-based measures. We…
Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Review
Chengmin Zhou, Ville Kyrki, Pasi Fränti +1
Bayesian inference has many advantages in decision making of agents (e.g. robotics/simulative agent) over a regular data-driven black-box neural network: Data-efficiency, generaliz…
Fixed-sized clusters -Means
Mikko I. Malinen, Pasi Fränti
We present a -means-based clustering algorithm, which optimizes the mean square error, for given cluster sizes. A straightforward application is balanced clustering, where the s…
What is wrong with MDPI: Is it a predator or a serious competitor?
Pasi Fränti
Hunt for predatory journals is based on binary division of the publishing world to legitime and predatory journals. This leads to difficulties in labeling publishers like MDPI with…
Hybrid of representation learning and reinforcement learning for dynamic and complex robotic motion planning
Chengmin Zhou, Xin Lu, Jiapeng Dai +3
Motion planning is the soul of robot decision making. Classical planning algorithms like graph search and reaction-based algorithms face challenges in cases of dense and dynamic ob…
Bayesian inference for data-efficient, explainable, and safe robotic motion planning: A review
Chengmin Zhou, Chao Wang, Haseeb Hassan +3
Bayesian inference has many advantages in robotic motion planning over four perspectives: The uncertainty quantification of the policy, safety (risk-aware) and optimum guarantees o…
Neighborhood Averaging for Improving Outlier Detectors
Jiawei Yang, Susanto Rahardja, Pasi Franti
We hypothesize that similar objects should have similar outlier scores. To our knowledge, all existing outlier detectors calculate the outlier score for each object independently r…
An advantage actor-critic algorithm for robotic motion planning in dense and dynamic scenarios
Chengmin Zhou, Bingding Huang, Pasi Fränti
Intelligent robots provide a new insight into efficiency improvement in industrial and service scenarios to replace human labor. However, these scenarios include dense and dynamic…
A review of motion planning algorithms for intelligent robotics
Chengmin Zhou, Bingding Huang, Pasi Fränti
We investigate and analyze principles of typical motion planning algorithms. These include traditional planning algorithms, supervised learning, optimal value reinforcement learnin…