94 citations · 165 across the 11 of their papers we have counts for
6 papers · 1 filter
Learning Aggregation Functions
Giovanni Pellegrini, Alessandro Tibo, Paolo Frasconi +2
Learning on sets is increasingly gaining attention in the machine learning community, due to its widespread applicability. Typically, representations over sets are computed by usin…
A general framework for defining and optimizing robustness
Alessandro Tibo, Manfred Jaeger, Kim G. Larsen
Robustness of neural networks has recently attracted a great amount of interest. The many investigations in this area lack a precise common foundation of robustness concepts. There…
A Complete Characterization of Projectivity for Statistical Relational Models
Manfred Jaeger, Oliver Schulte
A generative probabilistic model for relational data consists of a family of probability distributions for relational structures over domains of different sizes. In most existing s…
Learning and Interpreting Multi-Multi-Instance Learning Networks
Alessandro Tibo, Manfred Jaeger, Paolo Frasconi
We introduce an extension of the multi-instance learning problem where examples are organized as nested bags of instances (e.g., a document could be represented as a bag of sentenc…
Numeric Input Relations for Relational Learning with Applications to Community Structure Analysis
Jiuchuan Jiang, Manfred Jaeger
Most work in the area of statistical relational learning (SRL) is focussed on discrete data, even though a few approaches for hybrid SRL models have been proposed that combine nume…
Learning Markov Decision Processes for Model Checking
Hua Mao, Yingke Chen, Manfred Jaeger +3
Constructing an accurate system model for formal model verification can be both resource demanding and time-consuming. To alleviate this shortcoming, algorithms have been proposed…