144 citations · 219 across the 11 of their papers we have counts for
7 papers
GAN-MPC: Training Model Predictive Controllers with Parameterized Cost Functions using Demonstrations from Non-identical Experts
Returaj Burnwal, Anirban Santara, Nirav P. Bhatt +2
Model predictive control (MPC) is a popular approach for trajectory optimization in practical robotics applications. MPC policies can optimize trajectory parameters under kinodynam…
Clustering Indices based Automatic Classification Model Selection
Sudarsun Santhiappan, Nitin Shravan, Balaraman Ravindran
Classification model selection is a process of identifying a suitable model class for a given classification task on a dataset. Traditionally, model selection is based on cross-val…
GrabQC: Graph based Query Contextualization for automated ICD coding
Jeshuren Chelladurai, Sudarsun Santhiappan, Balaraman Ravindran
Automated medical coding is a process of codifying clinical notes to appropriate diagnosis and procedure codes automatically from the standard taxonomies such as ICD (International…
Exploration for Multi-task Reinforcement Learning with Deep Generative Models
Sai Praveen Bangaru, JS Suhas, Balaraman Ravindran
Exploration in multi-task reinforcement learning is critical in training agents to deduce the underlying MDP. Many of the existing exploration frameworks such as , ,…
EPOpt: Learning Robust Neural Network Policies Using Model Ensembles
Aravind Rajeswaran, Sarvjeet Ghotra, Balaraman Ravindran +1
Sample complexity and safety are major challenges when learning policies with reinforcement learning for real-world tasks, especially when the policies are represented using rich f…
Fractional Moments on Bandit Problems
Ananda Narayanan B, Balaraman Ravindran
Reinforcement learning addresses the dilemma between exploration to find profitable actions and exploitation to act according to the best observations already made. Bandit problems…