5 accepted papers
We study program-learning methods that are efficient in both samples and computation. Classical learning theory suggests that when the target admits a short program description (for example, a short piece of ``Python code''), it can be learned from relatively few examples by performing ERM over the …
Because it is difficult to precisely specify complex objectives, reinforcement learning policies are often optimized using proxy reward functions that only approximate the true goal. However, optimizing proxy rewards frequently leads to reward hacking: the optimized reward function ceases to be a go…
Freezing of Gait (FoG) is one of the incapacitating motor symptoms that appear in patients with Parkinson’s Disease (PD). FoG manifests gait impairments and imposes unforeseen difficulties in commencing the locomotion. Frequent episodes of FoG often lead to fall-related injuries and impart dreadful…
Freezing of Gait (FoG) is a paroxysmal and devitalizing symptom associated with Parkinson’s disease (PD). Episodes of FoG impedes gait and augments fall propensity, often leading to serious fall-injury. In this paper, we present a method for online detection of FoG using a wearable motion sensor. Th…
Multi-fingered dexterous hands are versatile and capable of acquiring a diverse set of skills such as grasping, in-hand manipulation, and tool use. To fully utilize their versatility in real-world scenarios, we require algorithms and policies that can control them using on-board sensing capabilities…