4 papers
Online and Streaming Algorithms for Constrained -Submodular Maximization
Fabian Spaeh, Alina Ene, Huy L. Nguyen
Constrained -submodular maximization is a general framework that captures many discrete optimization problems such as ad allocation, influence maximization, personalized recomme…
Learning Mixtures of Markov Chains with Quality Guarantees
Fabian Spaeh, Charalampos E. Tsourakakis
A large number of modern applications ranging from listening songs online and browsing the Web to using a navigation app on a smartphone generate a plethora of user trails. Cluster…
Online Ad Allocation with Predictions
Fabian Spaeh, Alina Ene
Display Ads and the generalized assignment problem are two well-studied online packing problems with important applications in ad allocation and other areas. In both problems, ad i…
Global Evaluation for Decision Tree Learning
Fabian Spaeh, Sven Kosub
We transfer distances on clusterings to the building process of decision trees, and as a consequence extend the classical ID3 algorithm to perform modifications based on the global…