5 papers
Sample-Efficient L0-L2 Constrained Structure Learning of Sparse Ising Models
Antoine Dedieu, Miguel Lázaro-Gredilla, Dileep George
We consider the problem of learning the underlying graph of a sparse Ising model with nodes from i.i.d. samples. The most recent and best performing approaches combine an e…
From proprioception to long-horizon planning in novel environments: A hierarchical RL model
Nishad Gothoskar, Miguel Lázaro-Gredilla, Dileep George
For an intelligent agent to flexibly and efficiently operate in complex environments, they must be able to reason at multiple levels of temporal, spatial, and conceptual abstractio…
Query Training: Learning a Worse Model to Infer Better Marginals in Undirected Graphical Models with Hidden Variables
Miguel Lázaro-Gredilla, Wolfgang Lehrach, Nishad Gothoskar +3
Probabilistic graphical models (PGMs) provide a compact representation of knowledge that can be queried in a flexible way: after learning the parameters of a graphical model once,…
A Model of Fast Concept Inference with Object-Factorized Cognitive Programs
Daniel P. Sawyer, Miguel Lázaro-Gredilla, Dileep George
The ability of humans to quickly identify general concepts from a handful of images has proven difficult to emulate with robots. Recently, a computer architecture was developed tha…
Beyond imitation: Zero-shot task transfer on robots by learning concepts as cognitive programs
Miguel Lázaro-Gredilla, Dianhuan Lin, J. Swaroop Guntupalli +1
Humans can infer concepts from image pairs and apply those in the physical world in a completely different setting, enabling tasks like IKEA assembly from diagrams. If robots could…