activity
20192026
most citedOff-Policy Risk Assessment in Contextual Bandits

11 citations · 47 across the 26 of their papers we have counts for

collaborators
Showing 2021Show all

5 papers · 1 filter

cs.LG2021★ 5 cited

Action-Sufficient State Representation Learning for Control with Structural Constraints

Biwei Huang, Chaochao Lu, Liu Leqi +4

Perceived signals in real-world scenarios are usually high-dimensional and noisy, and finding and using their representation that contains essential and sufficient information requ…

cs.CY2021

When Curation Becomes Creation: Algorithms, Microcontent, and the Vanishing Distinction between Platforms and Creators

Liu Leqi, Dylan Hadfield-Menell, Zachary C. Lipton

Ever since social activity on the Internet began migrating from the wilds of the open web to the walled gardens erected by so-called platforms, debates have raged about the respons…

cs.LG2021★ 11 cited

Off-Policy Risk Assessment in Contextual Bandits

Audrey Huang, Liu Leqi, Zachary C. Lipton +1

Even when unable to run experiments, practitioners can evaluate prospective policies, using previously logged data. However, while the bandits literature has adopted a diverse set…

cs.LG2021★ 5 cited

On the Convergence and Optimality of Policy Gradient for Markov Coherent Risk

Audrey Huang, Liu Leqi, Zachary C. Lipton +1

In order to model risk aversion in reinforcement learning, an emerging line of research adapts familiar algorithms to optimize coherent risk functionals, a class that includes cond…

stat.ME2021★ 3 cited

Median Optimal Treatment Regimes

Liu Leqi, Edward H. Kennedy

Optimal treatment regimes are personalized policies for making a treatment decision based on subject characteristics, with the policy chosen to maximize some value. It is common to…