D. Kazakov

发表

Machine Learning for Agents and Multi-Agent Systems

Daniel Kudenko, Eduardo Alonso, Dimitar Kazakov, 2008 .

Machine Learning and Inductive Logic Programming for Multi-agent Systems

Daniel Kudenko, Dimitar Kazakov, D. Kudenko, 2001, EASSS.

Adaptive Agents and Multi-Agent Systems II: Adaptation and Multi-Agent Learning

Daniel Kudenko, Eduardo Alonso, Dimitar Kazakov, 2003, Adaptive Agents and Multi-Agent Systems.

Using WordNet Similarity and Antonymy Relations to Aid Document Retrieval

D. Kazakov, Thomas de Simone, 2005 .

Knowledge Discovery : Enhancing Data Mining and Decision Support Integration

D. Kazakov, R. Alfred, 2005 .

Predicting User Preferences with XGBoost Learning to Rank Method

D. Kazakov, N. N. Qomariyah, A. Fajar, 2020, 2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI).

Chapter I Machine Learning for Agents and Multi-Agent Systems

D. Kudenko, D. Kazakov, 2002 .

Data Summarization Approach to Relational Domain Learning Based on Frequent Pattern to Support the Development of Decision Making

Rayner Alfred, Dimitar Kazakov, D. Kazakov, 2006, ADMA.

Topics Document for Entry in October 2007

Richard C. Paige, S. Stepney, A. Burns, 2007 .

Could Navigation Be the Key to Language ?

D. Kazakov, M. Bartlett, 2008 .

A MULTI-AGENT SIMULATION OF THE EVOLUTION OF LANGUAGE

D. Kazakov, M. Bartlett, 2008 .

On The Beneﬁt of Logic-based Approach to Learn Pairwise Comparisons

D. Kazakov, N. N. Qomariyah, A. Fajar, 2020 .

Inductive learning of lexical semantics with typed unification grammars

D. Kazakov, Simon Dobnik, 2007 .

INTERPLAY BETWEEN LANGUAGE, NAVIGATION AND KIN SELECTION

D. Kazakov, 2010 .

Utilizing Chest X-rays for Age Prediction and Gender Classification

D. Kazakov, Chris Solomou, 2021, 2021 4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI).

A Tree-based Mortality Prediction Model of COVID-19 from Routine Blood Samples

D. Kazakov, N. N. Qomariyah, Ardimas Andi Purwita, 2021, 2021 International Conference on ICT for Smart Society (ICISS).

Inductive Logic Programming: 29th International Conference, ILP 2019, Plovdiv, Bulgaria, September 3–5, 2019, Proceedings

Yuzuru Tanaka, Randy Goebel, Dimitar Kazakov, 2020, ILP.

The Self-Cognisant Robot

Dimitar Kazakov, D. Kazakov, 2012, Cognitive Computation.

Learning implicational models of universal grammar parameters

Dimitar Kazakov, Cristina Guardiano, Giuseppe Longobardi, 2018 .

Machine Learning Models of Universal Grammar Parameter Dependencies

Dimitar Kazakov, Cristina Guardiano, Dimitris Michelioudakis, 2017 .

Natural Language Processing Applications of Machine Learning

Dimitar Kazakov, Fl Dimitar Kazakov, D. Kazakov, 1999 .

Discretization Numbers for Multiple-Instances Problem in Relational Database

Rayner Alfred, Dimitar Kazakov, D. Kazakov, 2007, ADBIS.

Aggregating Multiple Instances in Relational Database Using Semi-Supervised Genetic Algorithm-based Clustering Technique

Dimitar Kazakov, Rayner Alfred, D. Kazakov, 2007, ADBIS Research Communications.

Proceedings of the Workshop on Exploring Syntactically Annotated Corpora

Dimitar Kazakov, Petya Osenova, Kiril Simov, 2005 .

Evolutionary pressures promoting complexity in navigation and communication

Dimitar Kazakov, Mark Bartlett, D. Kazakov, 2013 .

Evolutionary Algorithms with Extended Fitness

D. Kazakov, 2007 .

The origins of syntax: from navigation to language

Dimitar Kazakov, Mark Bartlett, D. Kazakov, 2005, Connect. Sci..

Comparing Resource Sharing with Information Exchange in Co-operative Agents, and the Role of Environment Structure

Dimitar Kazakov, Mark Bartlett, D. Kazakov, 2004, Adaptive Agents and Multi-Agent Systems.

COOPERATIVE NAVIGATION AND THE FACULTY OF LANGUAGE

Dimitar Kazakov, Mark Bartlett, D. Kazakov, 2004, Appl. Artif. Intell..

Unsupervised Learning of Word Segmentation Rules with Genetic Algorithms and Inductive Logic Programming

Suresh Manandhar, Dimitar Kazakov, D. Kazakov, 2001, Machine Learning.

Ontology Graph Embeddings and ILP for Financial Forecasting

D. Kazakov, C. Erten, 2021, ILP.

Achievements and Prospects of Learning Word Morphology with Inductive Logic Programming

Dimitar Kazakov, D. Kazakov, 2001, Learning Language in Logic.

Moving Nature-Inspired Algorithms to Parallel, Asynchronous and Decentralised Environments

Daniel Kudenko, Edward Curry, Dimitar Kazakov, 2005, SOAS.

Evolving the Game of Life

Dimitar Kazakov, Matthew Sweet, D. Kazakov, 2004, Adaptive Agents and Multi-Agent Systems.

Could Navigation Be the Key to Language ?

D. Kazakov, M. Bartlett, 2008 .

The Role of Environment Structure in Multi-Agent Simulations of Language Evolution

Dimitar Kazakov, Mark Bartlett, D. Kazakov, 2004 .

Deep reinforcement learning based parameter control in differential evolution

Manuel López-Ibáñez, Dimitar Kazakov, Mudita Sharma, 2019, GECCO.

Challenges in Relational Learning for Real-Time Systems Applications

Iain Bate, Dimitar Kazakov, Mark Bartlett, 2008, ILP.

New Directions in Worst-Case Execution Time analysis

Iain Bate, Dimitar Kazakov, D. Kazakov, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Clustering Approach to Generalized Pattern Identification Based on Multi-instanced Objects with DARA

Rayner Alfred, Dimitar Kazakov, D. Kazakov, 2007, ADBIS Research Communications.

Towards New Methods for Developing Real-Time Systems: Automatically Deriving Loop Bounds Using Machine Learning

Iain Bate, Dimitar Kazakov, D. Kazakov, 2006, 2006 IEEE Conference on Emerging Technologies and Factory Automation.

Pattern-Based Transformation Approach to Relational Domain Learning Using Dynamic Aggregation for Relational Attributes

Rayner Alfred, Dimitar Kazakov, D. Kazakov, 2006, DMIN.

Hybridisation of artificial bee colony algorithm on four classes of real-valued optimisation functions

Dimitar Kazakov, Mudita Sharma, D. Kazakov, 2017, GECCO.

Pair Trading with an Ontology of SEC Financial Reports

Can Erten, Neel Chotai, Dimitar Kazakov, 2020, 2020 IEEE Symposium Series on Computational Intelligence (SSCI).

System of Systems Hazard Analysis Using Simulation and Machine Learning

Tim Kelly, Dimitar Kazakov, Robert Alexander, 2006, SAFECOMP.

The Self-Cognisant Robot

D. Kazakov, 2012, Cognitive Computation.

Learning from Ordinal Data with Inductive Logic Programming in Description Logic

Dimitar Kazakov, Nunung Nurul Qomariyah, D. Kazakov, 2017, ILP.

Guaranteed Loop Bound Identification from Program Traces for WCET

Iain Bate, Dimitar Kazakov, Mark Bartlett, 2009, 2009 15th IEEE Real-Time and Embedded Technology and Applications Symposium.

Stochastic Simulation of Inherited Kinship-Driven Altruism

Dimitar Kazakov, Heather R. Turner, Heather Turner, 2002, Adaptive Agents and Multi-Agents Systems.

SAX Discretization Does Not Guarantee Equiprobable Symbols

Dimitar Kazakov, Matthew Butler, D. Kazakov, 2015, IEEE Transactions on Knowledge and Data Engineering.

Modeling the behavior of the stock market with an Artificial Immune System

Dimitar Kazakov, Matthew Butler, D. Kazakov, 2010, IEEE Congress on Evolutionary Computation.

Multi-Task Learning Framework for Stance Detection and Veracity Prediction

Fatima T. AL-Khawaldeh, D. Kazakov, Tommy Yuan, 2020 .

Social Learning through Evolution of Language

D. Kazakov, M. Bartlett, 2003, Artificial Evolution.

WordNet-based text document clustering

Dimitar Kazakov, Julian Sedding, D. Kazakov, 2004 .

A genetic-based pairwise trip planner recommender system

Dimitar Kazakov, Nunung Nurul Qomariyah, D. Kazakov, 2021, J. Big Data.

A learning adaptive Bollinger band system

Dimitar Kazakov, Matthew Butler, D. Kazakov, 2012, 2012 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr).

Unified Framework for the Adaptive Operator Selection of Discrete Parameters pdf

Dimitar Kazakov, Mudita Sharma, Manuel Lopez-Ibanez, 2020, ArXiv.

Performance Assessment of Recursive Probability Matching for Adaptive Operator Selection in Differential Evolution

Manuel López-Ibáñez, Dimitar Kazakov, Mudita Sharma, 2018, PPSN.

Testing implications of the Adaptive Market Hypothesis via computational intelligence

Dimitar Kazakov, Matthew Butler, D. Kazakov, 2012, 2012 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr).

Perspectives Generation via Multi-Head Attention Mechanism and Common-Sense Knowledge

Fatima T. AL-Khawaldeh, D. Kazakov, Tommy Yuan, 2022, International Journal on Cybernetics & Informatics.

Adaptive Agents and Multi-Agent Systems

Daniel Kudenko, Eduardo Alonso, Dimitar Kazakov, 2003, Lecture Notes in Computer Science.

Equation Discovery for Macroeconomic Modelling

Dimitar Kazakov, Tsvetomira Tsenova, D. Kazakov, 2008, ICAART.

Learning Binary Preference Relations: A Comparison of Logic-based and Statistical Approaches

Dimitar Kazakov, Nunung Nurul Qomariyah, D. Kazakov, 2017, IntRS@RecSys.

Hierarchical model-based clustering of relational data with aggregates

Rayner Alfred, Dimitar Kazakov, D. Kazakov, 2004, SAC '04.

Ieee International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications Handling Datasets in a Multi-relational Environment: Cluster Dispersion Vs Cluster Purity

R. Alfred, D. Kazakov, D. Kazakov, 2022 .