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06/08/2023
Learnability with PAC Semantics for Multi-agent Beliefs
The tension between deduction and induction is perhaps the most fundamen...
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06/02/2022
A Scalable Shannon Entropy Estimator
We revisit the well-studied problem of estimating the Shannon entropy of...
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03/23/2022
An Example of the SAM+ Algorithm for Learning Action Models for Stochastic Worlds
In this technical report, we provide a complete example of running the S...
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12/21/2021
Provable Hierarchical Lifelong Learning with a Sketch-based Modular Architecture
We propose a modular architecture for the lifelong learning of hierarchi...
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11/15/2021
Conditional Linear Regression for Heterogeneous Covariances
Often machine learning and statistical models will attempt to describe t...
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07/12/2021
Polynomial Time Reinforcement Learning in Correlated FMDPs with Linear Value Functions
Many reinforcement learning (RL) environments in practice feature enormo...
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07/09/2021
Safe Learning of Lifted Action Models
Creating a domain model, even for classical, domain-independent planning...
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03/29/2021
One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks
Can deep learning solve multiple tasks simultaneously, even when they ar...
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02/19/2021
Probabilistic Generating Circuits
Generating functions, which are widely used in combinatorics and probabi...
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10/23/2020
Learning Implicitly with Noisy Data in Linear Arithmetic
Robustly learning in expressive languages with real-world data continues...
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06/24/2019
Query-driven PAC-Learning for Reasoning
We consider the problem of learning rules from a data set that support a...
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06/24/2019
Implicitly Learning to Reason in First-Order Logic
We consider the problem of answering queries about formulas of first-ord...
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11/22/2018
The Price of Uncertain Priors in Source Coding
We consider the problem of one-way communication when the recipient does...
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06/28/2018
Polynomial-time probabilistic reasoning with partial observations via implicit learning in probability logics
Standard approaches to probabilistic reasoning require that one possesse...
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06/26/2018
Conditional Sparse ℓ_p-norm Regression With Optimal Probability
We consider the following conditional linear regression problem: the tas...
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06/06/2018
Conditional Linear Regression
Work in machine learning and statistics commonly focuses on building mod...
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11/13/2017
Learning Abduction under Partial Observability
Juba recently proposed a formulation of learning abductive reasoning fro...
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05/24/2017
Efficient, Safe, and Probably Approximately Complete Learning of Action Models
In this paper we explore the theoretical boundaries of planning in a set...
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08/18/2016
Conditional Sparse Linear Regression
Machine learning and statistics typically focus on building models that ...
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09/01/2012