96 citations · 491 across the 80 of their papers we have counts for
24 papers · 1 filter
Sample Efficient Active Algorithms for Offline Reinforcement Learning
Soumyadeep Roy, Shashwat Kushwaha, Ambedkar Dukkipati
Offline reinforcement learning (RL) enables policy learning from static data but often suffers from poor coverage of the state-action space and distributional shift problems. This…
Emergent Natural Language with Communication Games for Improving Image Captioning Capabilities without Additional Data
Parag Dutta, Ambedkar Dukkipati
Image captioning is an important problem in developing various AI systems, and these tasks require large volumes of annotated images to train the models. Since all existing labelle…
Active Reinforcement Learning Strategies for Offline Policy Improvement
Ambedkar Dukkipati, Ranga Shaarad Ayyagari, Bodhisattwa Dasgupta +2
Learning agents that excel at sequential decision-making tasks must continuously resolve the problem of exploration and exploitation for optimal learning. However, such interaction…
Temporal Abstraction in Reinforcement Learning with Offline Data
Ranga Shaarad Ayyagari, Anurita Ghosh, Ambedkar Dukkipati
Standard reinforcement learning algorithms with a single policy perform poorly on tasks in complex environments involving sparse rewards, diverse behaviors, or long-term planning.…
Deep Representation Learning for Forecasting Recursive and Multi-Relational Events in Temporal Networks
Tony Gracious, Ambedkar Dukkipati
Understanding relations arising out of interactions among entities can be very difficult, and predicting them is even more challenging. This problem has many applications in variou…
Deep Representation Learning for Prediction of Temporal Event Sets in the Continuous Time Domain
Parag Dutta, Kawin Mayilvaghanan, Pratyaksha Sinha +1
Temporal Point Processes (TPP) play an important role in predicting or forecasting events. Although these problems have been studied extensively, predicting multiple simultaneously…