research
∙
12/29/2022
Offline Policy Optimization in RL with Variance Regularizaton
Learning policies from fixed offline datasets is a key challenge to scal...
share
research
∙
09/18/2022
Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective
While reinforcement learning (RL) methods that learn an internal model o...
research
∙
04/18/2022
INFOrmation Prioritization through EmPOWERment in Visual Model-Based RL
Model-based reinforcement learning (RL) algorithms designed for handling...
research
∙
10/12/2021
Auditing Robot Learning for Safety and Compliance during Deployment
Robots of the future are going to exhibit increasingly human-like and su...
research
∙
09/25/2021
Auditing AI models for Verified Deployment under Semantic Specifications
Auditing trained deep learning (DL) models prior to deployment is vital ...
research
∙
01/18/2021
Learning by Watching: Physical Imitation of Manipulation Skills from Human Videos
We present an approach for physical imitation from human videos for robo...
research
∙
11/27/2020
Skill Transfer via Partially Amortized Hierarchical Planning
To quickly solve new tasks in complex environments, intelligent agents n...
research
∙
10/27/2020
Conservative Safety Critics for Exploration
Safe exploration presents a major challenge in reinforcement learning (R...
research
∙
10/19/2020
D2RL: Deep Dense Architectures in Reinforcement Learning
While improvements in deep learning architectures have played a crucial ...
research
∙
09/25/2020
Continual Model-Based Reinforcement Learning with Hypernetworks
Effective planning in model-based reinforcement learning (MBRL) and mode...
research
∙
09/02/2020
A Bayesian Approach with Type-2 Student-tMembership Function for T-S Model Identification
Clustering techniques have been proved highly suc-cessful for Takagi-Sug...
research
∙
07/01/2020
De-anonymization of authors through arXiv submissions during double-blind review
In this paper, we investigate the effects of releasing arXiv preprints o...
research
∙
06/15/2020
Generalized Adversarially Learned Inference
Allowing effective inference of latent vectors while training GANs can g...
research
∙
05/21/2020
LEAF: Latent Exploration Along the Frontier
Self-supervised goal proposal and reaching is a key component for explor...
research
∙
05/21/2020
Dynamics-Aware Latent Space Reachability for Exploration in Temporally-Extended Tasks
Self-supervised goal proposal and reaching is a key component of efficie...
research
∙
04/28/2020
DiVA: Diverse Visual Feature Aggregation forDeep Metric Learning
Visual Similarity plays an important role in many computer vision applic...
research
∙
04/28/2020
DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning
Visual Similarity plays an important role in many computer vision applic...
research
∙
04/19/2020
Model-Predictive Control via Cross-Entropy and Gradient-Based Optimization
Recent works in high-dimensional model-predictive control and model-base...
research
∙
03/10/2020
DIBS: Diversity inducing Information Bottleneck in Model Ensembles
Although deep learning models have achieved state-of-the-art performance...
research
∙
11/19/2019
MANGA: Method Agnostic Neural-policy Generalization and Adaptation
In this paper we target the problem of transferring policies across mult...
research
∙
06/07/2019
A Generative Framework for Zero-Shot Learning with Adversarial Domain Adaptation
In this paper, we present a domain adaptation based generative framework...
research
∙
12/16/2018
New tab page recommendations cause a strong suppression of exploratory web browsing behaviors
Through a combination of experimental and simulation results, we illustr...
research
∙
10/11/2018
A Data-Efficient Framework for Training and Sim-to-Real Transfer of Navigation Policies
Learning effective visuomotor policies for robots purely from data is ch...
research
∙
07/17/2018
Explanations for Temporal Recommendations
Recommendation systems are an integral part of Artificial Intelligence (...
research
∙
07/17/2018