activity
20162024
most citedEvolutionary Simplicial Learning as a Generative and Compact Sparse Framework for Classification

2 citations · 5 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CC2024

A computing machinery using a continuous memory tape

Yigit Oktar

By considering a discrete tape where each cell corresponds to an integer, thus to a possible sum, a pseudo-polynomial solution can be given to subset sum problem, which is an NP-co…

math.OC2021

Casting graph isomorphism as a point set registration problem using a simplex embedding and sampling

Yigit Oktar

Graph isomorphism is an important problem as its worst-case time complexity is not yet fully understood. In this study, we try to draw parallels between a related optimization prob…

cs.CV2020★ 1 cited

On the Preservation of Spatio-temporal Information in Machine Learning Applications

Yigit Oktar, Mehmet Turkan

In conventional machine learning applications, each data attribute is assumed to be orthogonal to others. Namely, every pair of dimension is orthogonal to each other and thus there…

cs.LG2020★ 2 cited

Evolutionary Simplicial Learning as a Generative and Compact Sparse Framework for Classification

Yigit Oktar, Mehmet Turkan

Dictionary learning for sparse representations has been successful in many reconstruction tasks. Simplicial learning is an adaptation of dictionary learning, where subspaces become…

cs.AI2020

Self-recognition in conversational agents

Yigit Oktar, Erdem Okur, Mehmet Turkan

In a standard Turing test, a machine has to prove its humanness to the judges. By successfully imitating a thinking entity such as a human, this machine then proves that it can als…

cs.CV2019★ 2 cited

Convolutional Neural Networks: A Binocular Vision Perspective

Yigit Oktar, Diclehan Karakaya, Oguzhan Ulucan +1

It is arguable that whether the single camera captured (monocular) image datasets are sufficient enough to train and test convolutional neural networks (CNNs) for imitating the bio…

cs.CV2017

Boosting Dictionary Learning with Error Codes

Yigit Oktar, Mehmet Turkan

In conventional sparse representations based dictionary learning algorithms, initial dictionaries are generally assumed to be proper representatives of the system at hand. However,…

cs.CV2016

Depth Estimation from Single Image using Sparse Representations

Yigit Oktar

Monocular depth estimation is an interesting and challenging problem as there is no analytic mapping known between an intensity image and its depth map. Recently there has been a l…