Ara
Toplam kayıt 18, listelenen: 11-18
A Bi-criteria Hybrid Genetic Algorithm with Robustness Objective for the Course Timetabling Problem
(Patat, 2016)
Traditional methods of generating timetables may not yield robust solutions
that may easily be adapted to changing inputs. Incorporating late changes
by making minimum modifications is an important need in many ...
Search Space Sampling by Simulated Annealing for Identifying Robust Solutions in Course Timetabling
(Institute of Electrical and Electronics Engineers Inc., 2020)
For many combinatorial optimization problems, it
is important to identify solutions that can be repaired without
degrading solution quality in case changes in the data associated
with the constraints make the initial ...
EEG Sinyallerinin Sınıflandırılmasında Evrimsel Öznitelik Seçim Metotlarının Kullanılması
(Marmara Üniversitesi, 2021)
Elektroensefalografi beyindeki elektriksel akımın ölçülmesi ile elde edilen sinyallerdir. Bu sinyallerin sınıflandırılması özellikle beyin sinyalleri ile ilgili rahatsızlıkların teşhis, tanı ve tedavisine katkı sağladığı ...
Bi-criteria Simulated Annealing for the Curriculum-based Course Timetabling Problem With Robustness Approximation
(Springer, 2022)
In the process of developing a university’s weekly course timetable, changes in the data, such as the available time periods
of professors or rooms, render the timetable infeasible, requiring the administrators to repair ...
A Comparison of Different Loss Computations in Siamese Networks for Authorship Verification
(Springer, 2023)
In this study, we consider the author verification problem as a binary
classification problem where the aim is to identify whether the two inputs belong to
the same author or not. For this task, we have used several ...
Novel Surrogate Measures Based on a Similarity Network for Neural Architecture Search
(IEEE, 2023)
We propose two novel surrogate measures to predict the validation accuracy of the classification
produced by a given neural architecture, thus eliminating the need to train it, in order to speed up neural
architecture ...
Az Örnekle Öğrenme Problemleri için MAML ve ProtoNet Algoritmalarının İncelenmesi
(Osman Sağdıç, 2021)
Derin sinir ağları ile özellikle görüntü veri kümeleri üzerinde çok başarılı sonuçlar elde edilmektedir. Ancak bu başarının arkasında
büyük ölçekli etiketli veri kümeleri yatmaktadır. Derin öğrenme ağlarının özelleşmiş ...
Triplet MAML for Few-shot Classification Problems
(Springer, 2023)
In this study, we propose a TripletMAML algorithm as an extension to Model-Agnostic Meta-Learning (MAML) which is the most widely-used optimization-based meta-learning algorithm. We approach MAML from a metric-learning ...