96 citations · 491 across the 80 of their papers we have counts for
86 papers
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…
Semi-supervised Deep Transfer for Regression without Domain Alignment
Mainak Biswas, Ambedkar Dukkipati, Devarajan Sridharan
Deep learning models deployed in real-world applications (e.g., medicine) face challenges because source models do not generalize well to domain-shifted target data. Many successfu…
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…
Predictive AI with External Knowledge Infusion: Datasets and Benchmarks for Stock Markets
Ambedkar Dukkipati, Kawin Mayilvaghanan, Naveen Kumar Pallekonda +2
Fluctuations in stock prices are influenced by a complex interplay of factors that go beyond mere historical data. These factors, themselves influenced by external forces, encompas…
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.…