Zobrazeno 1 - 10
of 78
pro vyhledávání: '"Kalganova, Tatiana"'
Autor:
Elhalwagy, Ayman, Kalganova, Tatiana
The generalisation of Neural Networks (NN) to multiple datasets is often overlooked in literature due to NNs typically being optimised for specific data sources. This becomes especially challenging in time-series-based multi-dataset models due to dif
Externí odkaz:
http://arxiv.org/abs/2305.08197
Autor:
Skackauskas, Jonas, Kalganova, Tatiana
Currently available dynamic optimization strategies for Ant Colony Optimization (ACO) algorithm offer a trade-off of slower algorithm convergence or significant penalty to solution quality after each dynamic change occurs. This paper proposes a discr
Externí odkaz:
http://arxiv.org/abs/2304.07646
Autor:
Elhalwagy, Ayman, Kalganova, Tatiana
Deep learning techniques have recently shown promise in the field of anomaly detection, providing a flexible and effective method of modelling systems in comparison to traditional statistical modelling and signal processing-based methods. However, th
Externí odkaz:
http://arxiv.org/abs/2202.05538
Autor:
Byerly, Adam, Kalganova, Tatiana
We provide a definition for class density that can be used to measure the aggregate similarity of the samples within each of the classes in a high-dimensional, unstructured dataset. We then put forth several candidate methods for calculating class de
Externí odkaz:
http://arxiv.org/abs/2202.03856
Autor:
Byerly, Adam, Kalganova, Tatiana
We show that, for each of five datasets of increasing complexity, certain training samples are more informative of class membership than others. These samples can be identified a priori to training by analyzing their position in reduced dimensional s
Externí odkaz:
http://arxiv.org/abs/2202.03238
We present a dataset consisting of high-resolution images of 13 micro-PCBs captured in various rotations and perspectives relative to the camera, with each sample labeled for PCB type, rotation category, and perspective categories. We then present th
Externí odkaz:
http://arxiv.org/abs/2101.11164
Autor:
Dzalbs, Ivars, Kalganova, Tatiana
The Multi-Depot Vehicle Routing Problem (MDVRP) is a real-world model of the simplistic Vehicle Routing Problem (VRP) that considers how to satisfy multiple customer demands from numerous depots. This paper introduces a hybrid 2-stage approach based
Externí odkaz:
http://arxiv.org/abs/2005.04157
The multidimensional knapsack problem is a well-known constrained optimization problem with many real-world engineering applications. In order to solve this NP-hard problem, a new modified Imperialist Competitive Algorithm with Constrained Assimilati
Externí odkaz:
http://arxiv.org/abs/2003.06617
This paper proposes an extension method for Ant Colony Optimization (ACO) algorithm called Dynamic Impact. Dynamic Impact is designed to solve challenging optimization problems that has nonlinear relationship between resource consumption and fitness
Externí odkaz:
http://arxiv.org/abs/2002.04099
Most capsule network designs rely on traditional matrix multiplication between capsule layers and computationally expensive routing mechanisms to deal with the capsule dimensional entanglement that the matrix multiplication introduces. By using Homog
Externí odkaz:
http://arxiv.org/abs/2001.09136