6 citations · 10 across the 8 of their papers we have counts for
5 papers · 1 filter
Evaluating Pretrained models for Deployable Lifelong Learning
Kiran Lekkala, Eshan Bhargava, Yunhao Ge +1
We create a novel benchmark for evaluating a Deployable Lifelong Learning system for Visual Reinforcement Learning (RL) that is pretrained on a curated dataset, and propose a novel…
Value Explicit Pretraining for Learning Transferable Representations
Kiran Lekkala, Henghui Bao, Sumedh A. Sontakke +2
Understanding visual inputs for a given task amidst varied changes is a key challenge posed by visual reinforcement learning agents. We propose \textit{Value Explicit Pretraining}…
Lightweight Learner for Shared Knowledge Lifelong Learning
Yunhao Ge, Yuecheng Li, Di Wu +12
In Lifelong Learning (LL), agents continually learn as they encounter new conditions and tasks. Most current LL is limited to a single agent that learns tasks sequentially. Dedicat…
Attentive Feature Reuse for Multi Task Meta learning
Kiran Lekkala, Laurent Itti
We develop new algorithms for simultaneous learning of multiple tasks (e.g., image classification, depth estimation), and for adapting to unseen task/domain distributions within th…
Meta Adaptation using Importance Weighted Demonstrations
Kiran Lekkala, Sami Abu-El-Haija, Laurent Itti
Imitation learning has gained immense popularity because of its high sample-efficiency. However, in real-world scenarios, where the trajectory distribution of most of the tasks dyn…