Quantum Computing

Quantum Computing Workshop

Анализ работы реализации квантового алгоритма построения деревьев решений на квантовом симуляторе

Сафина Л. И., Маннапов И. М., Хадиев К. Р., Анализ работы реализации квантового алгоритма построения деревьев решений на квантовом симуляторе

The Classical and Quantum Improvements of Decision Tree Constructing Algorithms C5.0 and CART

The Classical and Quantum Improvements of Decision Tree Constructing Algorithms C5.0 and CART

Liliia Safina, Ilnaz Mannapov and Kamil Khadiev. The Classical and Quantum Improvements of Decision Tree Constructing Algorithms C5.0 and CART

Classical and Quantum Improvements of Generic Decision Tree Constructing Algorithm for Classification Problem

Classical and Quantum Improvements of Generic Decision Tree Constructing Algorithm for Classification Problem

Ilnaz Mannapov, Kamil Khadiev and Liliya Safina. Classical and Quantum Improvements of Generic Decision Tree Constructing Algorithm for Classification Problem

Classical and Quantum Improvements of Generic Decision Tree Constructing Algorithm for Classification Problem

Ilnaz Mannapov, Liliya Safina and Kamil Khadiev, Classical and Quantum Improvements of Generic Decision Tree Constructing Algorithm for Classification Problem

The Quantum Version Of Classification Decision Tree Constructing Algorithm C5.0

In the paper, we focus on complexity of C5.0 algorithm for constructing decision tree classifier that is the models for the classification problem from machine learning. In classical case the decision tree is constructed in O(hd(NM+N log N)) running time, where M is a number of classes, N is the

Mannapov I., Safina L., Khadiev K., The Quantum Version Of Classification Decision Tree Constructing Algorithm C5.0

The Quantum Version Of Classification Decision Tree Constructing Algorithms

We consider decision tree as a model for the classification problem from machine learning. We focus on complexity of decision tree constructing algorithms as C5.0, CART. In classical case the decision tree is constructed in O(hd(NM+NlogN)) running time, where M is a number of classes, N is the size

Lilia Safina, Ilnaz Mannapov, Kamil Khadiev "The Quantum Version Of Classification Decision Tree Constructing Algorithms"

Квантовые онлайн алгоритмы с подсказкой и ограниченной памятью

In this paper, we consider online algorithms. Typically the model is investigated with respect to competitive ratio. We consider algorithms with restricted memory (space) and explore their power. We focus on quantum and classical online algorithms with advice. We consider special problem $P_k$. This

Kamil Khadiev, Ilnaz Mannapov and Mansur Ziatdinov "Quantum Online Algorithms with Advice Bits and Restricted Memory"

Квантовые потоковые онлайн алгоритмы с подсказой

Our Results: -a quantum online streaming algorithm with 1 qubit of memory and 1 advice bit can be better than a classical online streaming algorithm with $o(\log n)$ bits of memory and $o(\log n)$ advice bits. -Quantum online streaming algorithm with a constant size of memory and $t$ advice bits c

"Quantum Online Streaming Algorithms with Advice"

Квантовые онлайн алгоритмы с ограниченной памятью

В работе рассмотрены потоковые онлайн алгоритмы в качестве онлайн алгоритмов с ограниченной памятью. Показан пример задач, для которых квантовые потоковые онлайн алгоритмы эффиктивнее классических

Quantum online algorithms with restricted memory

О квантовых онлайн-алгоритмах с ограниченной памятью и подсказчиком

Хадиев К. Р., Хадиева А. И., Ривош А. В., Кравченко Д., Зиятдинов М. Т., Маннапов И. М., Ямилов Р. Р. "О квантовых онлайн-алгоритмах с ограниченной памятью и подсказчиком"

Хадиев К. Р., Хадиева А. И., Ривош А. В., Кравченко Д., Зиятдинов М. Т., Маннапов И. М., Ямилов Р. Р. "О квантовых онлайн-алгоритмах с ограниченной памятью и подсказчиком"

КВАНТОВЫЕ ОНЛАЙН-АЛГОРИТМЫ С ПОДСКАЗЧИКОМ, ИСПОЛЬЗУЮЩИМ РАСПРЕДЕЛЕННЫЕ КУБИТЫ

Маннапов И.М., Хадиев К.Р. "КВАНТОВЫЕ ОНЛАЙН-АЛГОРИТМЫ С ПОДСКАЗЧИКОМ, ИСПОЛЬЗУЮЩИМ РАСПРЕДЕЛЕННЫЕ КУБИТЫ"

Quantum Streaming Algorithms for Online Minimization Problems and Quantum Online Algorithms with Advice

A streaming algorithm is a well-known computational model that has a relationship with automata and branching programs models. We consider a quantum version of streaming algorithms for solving online minimization problems (OMP). It is the first time when quantum streaming algorithms are explored for

Quantum Streaming Algorithms for Online Minimization Problems and Quantum Online Algorithms with Advice

Quantum versus Classical Online Algorithms with Advice and Restricted Memory

In this paper, we consider online algorithms. Typically the model is investigated with respect to competitive ratio. We consider algorithms with restricted memory (space) and explore their power. We focus on quantum and classical online algorithms. We show that there are problems that can be better

Kamil Khadiev, Aliya Khadieva, Dmitry Kravchenko, Alexander Rivosh and Ilnaz Mannapov, "Quantum versus Classical Online Algorithms with Advice and Restricted Memory"