activity
20182020
most citedCROSSBOW: Scaling Deep Learning with Small Batch Sizes on Multi-GPU Servers

12 citations · 18 across the 3 of their papers we have counts for

collaborators

8 papers

cs.AI20206 cited

Entropia: A Family of Entropy-Based Conformance Checking Measures for Process Mining

Artem Polyvyanyy, Hanan Alkhammash, Claudio Di Ciccio +6

This paper presents a command-line tool, called Entropia, that implements a family of conformance checking measures for process mining founded on the notion of entropy from informa…

cs.AI2020

Partial Order Resolution of Event Logs for Process Conformance Checking

Han van der Aa, Henrik Leopold, Matthias Weidlich

While supporting the execution of business processes, information systems record event logs. Conformance checking relies on these logs to analyze whether the recorded behavior of a…

cs.DB2020

PRIPEL: Privacy-Preserving Event Log Publishing Including Contextual Information

Stephan A. Fahrenkrog-Petersen, Han van der Aa, Matthias Weidlich

Event logs capture the execution of business processes in terms of executed activities and their execution context. Since logs contain potentially sensitive information about the i…

cs.SE2020

Quantifying the Re-identification Risk of Event Logs for Process Mining

S. Nuñez von Voigt, S. A. Fahrenkrog-Petersen, D. Janssen +5

Event logs recorded during the execution of business processes constitute a valuable source of information. Applying process mining techniques to them, event logs may reveal the ac…

cs.CR2019

Secure Multi-Party Computation for Inter-Organizational Process Mining

Gamal Elkoumy, Stephan A. Fahrenkrog-Petersen, Marlon Dumas +3

Process mining is a family of techniques for analysing business processes based on event logs extracted from information systems. Mainstream process mining tools are designed for i…

cs.LG2019

Parallel Computation of Graph Embeddings

Chi Thang Duong, Hongzhi Yin, Thanh Dat Hoang +4

Graph embedding aims at learning a vector-based representation of vertices that incorporates the structure of the graph. This representation then enables inference of graph propert…