1 citations · 2 across the 9 of their papers we have counts for
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Abstract Reward Processes: Leveraging State Abstraction for Consistent Off-Policy Evaluation
Shreyas Chaudhari, Ameet Deshpande, Bruno Castro da Silva +1
Evaluating policies using off-policy data is crucial for applying reinforcement learning to real-world problems such as healthcare and autonomous driving. Previous methods for off-…
Evaluating a Generative Adversarial Framework for Information Retrieval
Ameet Deshpande, Mitesh M. Khapra
Recent advances in Generative Adversarial Networks (GANs) have resulted in its widespread applications to multiple domains. A recent model, IRGAN, applies this framework to Informa…
Discovering hierarchies using Imitation Learning from hierarchy aware policies
Ameet Deshpande, Harshavardhan Kamarthi, Balaraman Ravindran
Learning options that allow agents to exhibit temporally higher order behavior has proven to be useful in increasing exploration, reducing sample complexity and for various transfe…
Improvements on Hindsight Learning
Ameet Deshpande, Srikanth Sarma, Ashutosh Jha +1
Sparse reward problems are one of the biggest challenges in Reinforcement Learning. Goal-directed tasks are one such sparse reward problems where a reward signal is received only w…
FigureNet: A Deep Learning model for Question-Answering on Scientific Plots
Revanth Reddy, Rahul Ramesh, Ameet Deshpande +1
Deep Learning has managed to push boundaries in a wide variety of tasks. One area of interest is to tackle problems in reasoning and understanding, with an aim to emulate human int…