Eray Özkural

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Frequency mining problem comprises the core of several data mining algorithms. Among frequent pattern discovery algorithms, FP-GROWTH employs a unique search strategy using compact structures resulting in a high performance algorithm that requires only two database passes. We introduce an enhanced version of this algorithm called FP-GROWTH-TINY which can(More)
We frame the question of what kind of subjective experience a brain simulation would have in contrast to a biological brain. We discuss the brain prosthesis thought experiment. Then, we identify finer questions relating to the original inquiry, and set out to answer them moving forward from both a general physicalist perspective, and pan-experientialism. We(More)
We introduce a transaction database distribution scheme that divides the frequent item set mining task in a top-down fashion. Our method operates on a graph where vertices correspond to frequent items and edges correspond to frequent item sets of size two. We show that partitioning this graph by a vertex separator is sufficient to decide a distribution of(More)
We investigate physical measures and limits of intelligence that are objective and useful. We propose a universal measure of operator induction fitness, and show how it can be used in a reinforcement learning model, and a self-preserving agent model based on the free energy principle. We extend logical depth and conceptual jump size measures to stochastic(More)
It is known that benign looking AI objectives may result in powerful AI drives that may pose a risk to the human society. We examine the alternative scenario of what happens when universal goals that are not human-centric are used for designing AI agents. We follow a design approach that tries to exclude malevolent motivations from AI’s, however, we see(More)