Text-based reinforcement learning agents have predominantly been neural
...
With the growing interest in large language models, the need for evaluat...
We introduce Logical Offline Cycle Consistency Optimization (LOCCO), a
s...
Knowledge Base Question Answering (KBQA) tasks that involve complex reas...
Recent work on neuro-symbolic inductive logic programming has led to
pro...
We present Logical Optimal Actions (LOA), an action decision architectur...
Deep reinforcement learning (RL) methods often require many trials befor...
Knowledge Base Question Answering (KBQA) tasks that in-volve complex
rea...
This paper introduces Logical Credal Networks, an expressive probabilist...
Recent interest in Knowledge Base Completion (KBC) has led to a plethora...
Entity linking (EL), the task of disambiguating mentions in text by link...
Conventional deep reinforcement learning methods are sample-inefficient ...
Answering logical queries over incomplete knowledge bases is challenging...
Knowledge base question answering (KBQA) is an important task in Natural...
Knowledgebase question answering systems are heavily dependent on relati...
Real-valued logics underlie an increasing number of neuro-symbolic
appro...
We propose a novel framework seamlessly providing key properties of both...
Artificial Intelligence (AI) can now automate the algorithm selection,
f...
Data science is labor-intensive and human experts are scarce but heavily...
The rapid advancement of artificial intelligence (AI) is changing our li...
We study the automated machine learning (AutoML) problem of jointly sele...
We provide a formulation for Local Support Vector Machines (LSVMs) that
...
We present a stochastic setting for optimization problems with nonsmooth...
In this work we consider the stochastic minimization of nonsmooth convex...
In this paper we address the problem of pool based active learning, and
...