ILP turns 20: biography and future challenges
Abstract Inductive Logic Programming (ILP) is an area of Machine Learning which has now
reached its twentieth year. Using the analogy of a human biography this paper recalls the …
reached its twentieth year. Using the analogy of a human biography this paper recalls the …
Utilization of default logic for analyzing a metabolic system in discrete time
Metabolic pathways are seen as high criticalities in our understanding of mechanisms of
biological functions. This article focuses on automatic synthesis of the metabolic pathways …
biological functions. This article focuses on automatic synthesis of the metabolic pathways …
[PDF][PDF] Scalable relational learning for event recognition
N Katzouris - 2017 - iit.demokritos.gr
Event recognition systems rely on knowledge bases of event definitions to infer occurrences
of events in time. Using a logical framework for representing and reasoning about events …
of events in time. Using a logical framework for representing and reasoning about events …
Bayesian inference for statistical abduction using Markov chain Monte Carlo
Abduction is one of the basic logical inferences (deduction, induction and abduction) and
derives the best explanations for our observation. Statistical abduction attempts to define a …
derives the best explanations for our observation. Statistical abduction attempts to define a …
Time series discretization via MDL-based histogram density estimation
Y Kameya - 2011 IEEE 23rd international conference on tools …, 2011 - ieeexplore.ieee.org
In knowledge discovery from real-valued time series, discretization is often a key
preprocessing that extends the applicability of sophisticated tools for symbolic data mining …
preprocessing that extends the applicability of sophisticated tools for symbolic data mining …
Parallel and memory-efficient preprocessing for metagenome assembly
The analysis of high-throughput metagenomic sequencing data poses significant
computational challenges. Most current de novo assembly tools use the de Bruijn graph …
computational challenges. Most current de novo assembly tools use the de Bruijn graph …
Automated scientific assistant for cancer and chemoprevention
Logical modeling of cell biological phenomena has the potential to facilitate both the
understanding of the mechanisms that underly the phenomena as well as the process of …
understanding of the mechanisms that underly the phenomena as well as the process of …
[PDF][PDF] Logical modeling of cancer and chemoprevention
Logical modeling of cell biological phenomena has the potential to facilitate both the
understanding of the mechanisms that underly the phenomena as well as the process of …
understanding of the mechanisms that underly the phenomena as well as the process of …
Variational Bayes inference for logic-based probabilistic models on BDDs
Abduction is one of the basic logical inferences (deduction, induction and abduction) and
derives the best explanations for our observation. Statistical abduction attempts to define a …
derives the best explanations for our observation. Statistical abduction attempts to define a …
Default Logic for Diagnostic of Discrete Time System
Signaling pathways are seen as high criticalities in our understanding of mechanisms of
biological functions. In this paper, we propose default logic for diagnostic of Discrete Time …
biological functions. In this paper, we propose default logic for diagnostic of Discrete Time …