A brief note on why we think that the statistical relational learning framework is a great advancement over deterministic logic -- in particular in the context of model-based Reinforcement Learning
Invited Tutorial; video available from https://www.facebook.com/nipsfoundation/videos/15522226715356...
In the past few years there has been a lot of work lying at the intersection of probability theory, ...
This paper shows how methods from statistical relational learning can be used to address problems in...
A brief note on why we think that the statistical relational learning framework is a great advanceme...
We live in a richly interconnected world and, not surprisingly, we generate richly interconnected da...
The field of Statistical Relational Learning (SRL) is concerned with learning probabilistic models f...
Relational learning refers to learning from data that have a complex structure. This structure may ...
One key challenge in statistical relational learning (SRL) is scalable inference. Unfortunately, mo...
My research activity focuses on the field of Machine Learning. Two key challenges in most machine l...
This tutorial explains the core ideas behind lifted probabilistic inference in statistical relationa...
Statistical relational learning (SRL) augments probabilistic models with relational representations ...
One of the goals of artificial intelligence is to develop agents that learn and act in complex envir...
Invited talkThis talk shall introduce the field of statistical relational learning, which is concern...
In order to solve real-world tasks, intelligent machines need to be able to act in noisy worlds wher...
Abstract. Statistical relational learning (SRL) addresses one of the central open questions of AI: t...
Invited Tutorial; video available from https://www.facebook.com/nipsfoundation/videos/15522226715356...
In the past few years there has been a lot of work lying at the intersection of probability theory, ...
This paper shows how methods from statistical relational learning can be used to address problems in...
A brief note on why we think that the statistical relational learning framework is a great advanceme...
We live in a richly interconnected world and, not surprisingly, we generate richly interconnected da...
The field of Statistical Relational Learning (SRL) is concerned with learning probabilistic models f...
Relational learning refers to learning from data that have a complex structure. This structure may ...
One key challenge in statistical relational learning (SRL) is scalable inference. Unfortunately, mo...
My research activity focuses on the field of Machine Learning. Two key challenges in most machine l...
This tutorial explains the core ideas behind lifted probabilistic inference in statistical relationa...
Statistical relational learning (SRL) augments probabilistic models with relational representations ...
One of the goals of artificial intelligence is to develop agents that learn and act in complex envir...
Invited talkThis talk shall introduce the field of statistical relational learning, which is concern...
In order to solve real-world tasks, intelligent machines need to be able to act in noisy worlds wher...
Abstract. Statistical relational learning (SRL) addresses one of the central open questions of AI: t...
Invited Tutorial; video available from https://www.facebook.com/nipsfoundation/videos/15522226715356...
In the past few years there has been a lot of work lying at the intersection of probability theory, ...
This paper shows how methods from statistical relational learning can be used to address problems in...
DOI
Add to ORKG