26 citations · 34 across the 3 of their papers we have counts for
3 papers
cs.LG2023
Knowledge Transfer from Teachers to Learners in Growing-Batch Reinforcement Learning
Patrick Emedom-Nnamdi, Abram L. Friesen, Bobak Shahriari +2
Standard approaches to sequential decision-making exploit an agent's ability to continually interact with its environment and improve its control policy. However, due to safety, et…
cs.LG2016★ 8 cited
The Sum-Product Theorem: A Foundation for Learning Tractable Models
Abram L. Friesen, Pedro Domingos
Inference in expressive probabilistic models is generally intractable, which makes them difficult to learn and limits their applicability. Sum-product networks are a class of deep…
cs.AI2016★ 26 cited
Recursive Decomposition for Nonconvex Optimization
Abram L. Friesen, Pedro Domingos
Continuous optimization is an important problem in many areas of AI, including vision, robotics, probabilistic inference, and machine learning. Unfortunately, most real-world optim…