Learning sparse relational transition models

Learning sparse relational transition models

© 7th International Conference on Learning Representations, ICLR 2019. All Rights Reserved. We present a representation for describing transition models in complex uncertain domains using relational rules. For any action, a rule selects a set of relevant objects and computes a distribution over prop...

Full description

Bibliographic Details
Main Authors:	Xia, V, Wang, Z, Allen, K, Silver, T, Kaelbling, LP
Format:	Article
Language:	English
Published:	2021
Online Access:	https://hdl.handle.net/1721.1/132315

Similar Items

Learning sparse relational transition models
by: Xia, Victoria F., et al.
Published: (2022)

Alternative to extended block sparse Bayesian learning and its relation to pattern-coupled sparse Bayesian learning
by: Wang, Lu, et al.
Published: (2020)

Neural relational inference with fast modular meta-learning
by: Alet, F, et al.
Published: (2021)

Learning models over relational data using sparse tensors and functional dependencies
by: Abo Khamis, M, et al.
Published: (2020)

GLIB: Efficient Exploration for Relational Model-Based Reinforcement Learning via Goal-Literal Babbling
by: Chitnis, Rohan, et al.
Published: (2022)

Phase transitions for greedy sparse approximation algorithms
by: Tanner, J, et al.
Published: (2010)

A sparse learning approach to relative-volatility-managed portfolio selection
by: Pun, Chi Seng
Published: (2022)

Sparse regularity and relative Szemerédi theorems
by: Zhao, Yufei
Published: (2015)

Learning nonlocal sparse and low-rank models for image compressive sensing: nonlocal sparse and low-rank modeling
by: Zha, Zhiyuan, et al.
Published: (2023)

Sparse distance metric learning
by: Choy, T
Published: (2014)

In-database learning with sparse tensors
by: Abo Khamis, M, et al.
Published: (2018)

Few-Shot Bayesian Imitation Learning with Logical Program Policies
by: Silver, Tom, et al.
Published: (2021)

Structured Bayesian learning for recovery of clustered sparse signal
by: Wang, Lu, et al.
Published: (2022)

Learning of probabilistic transition models for robotic actions via templates
by: Xia, Victoria(Victoria F.)
Published: (2019)

Sparse choice models
by: Farias, Vivek F., et al.
Published: (2014)

Learning Sparse Gaussian Graphical Model with l0-regularization
by: Mu, Beipeng, et al.
Published: (2014)

Extreme learning machine with sparse connections
by: Bai, Zuo
Published: (2015)

Discovering Structure by Learning Sparse Graphs
by: Lake, Brenden M, et al.
Published: (2017)

Sparse learning : statistical and optimization perspectives
by: Dedieu, Antoine
Published: (2018)

Learning Linear, Sparse, Factorial Codes
by: Olshausen, Bruno A.
Published: (2004)

Spatial locality-aware sparse coding and dictionary learning
by: Wang, Jiang, et al.
Published: (2014)

A sparse object category model for efficient learning and exhaustive recognition
by: Fergus, R, et al.
Published: (2005)

A sparse object category model for efficient learning and complete recognition
by: Fergus, R, et al.
Published: (2006)

Sparse high-dimensional regression: Exact scalable algorithms and phase transitions
by: Bertsimas, Dimitris, et al.
Published: (2021)

SparseRT: Accelerating Unstructured Sparsity on GPUs for Deep Learning Inference
by: Wang, Ziheng
Published: (2022)

Distributed machine learning with sparse heterogeneous data
by: Richards, D, et al.
Published: (2021)

High Dimensional Sparse Econometric Models: An Introduction
by: Belloni, Alexandre, et al.
Published: (2012)

Structured sparse representations for supervised and unsupervised learning
by: Zeng, Yijie
Published: (2020)

Sparse Representations for Fast, One-Shot Learning
by: Yip, Kenneth, et al.
Published: (2004)

Learning environment simulators from sparse signals
by: Shavit, Yonadav Goldwasser
Published: (2018)

Visual Inertial Odometry with Sparse Deep Learning
by: Saat, Berke
Published: (2023)

Sparse Recovery Using Sparse Matrices
by: Gilbert, Anna, et al.
Published: (2021)

Sparse recovery using sparse matrices
by: Berinde, Radu, et al.
Published: (2008)

Sparse Recovery Using Sparse Matrices
by: Gilbert, Anna, et al.
Published: (2012)

Simplicity bias in transformers and their ability to learn sparse boolean functions
by: Bhattamishra, S, et al.
Published: (2023)

Inference for High-Dimensional Sparse Econometric Models
by: Belloni, Alexandre, et al.
Published: (2019)

An investigation of sparse tensor formats for tensor libraries
by: Tew, Parker Allen
Published: (2018)

Beyond normality: Learning sparse probabilistic graphical models in the non-Gaussian setting
by: Morrison, Rebecca E., et al.
Published: (2020)

An improved auto-calibration algorithm based on sparse Bayesian learning framework
by: Zhao, Lifan, et al.
Published: (2013)

Sparse PCA from sparse linear regression
by: Bresler, Guy, et al.
Published: (2021)