5 papers
Reducing Oracle Feedback with Vision-Language Embeddings for Preference-Based RL
Udita Ghosh, Dripta S. Raychaudhuri, Jiachen Li +2
Preference-based reinforcement learning can learn effective reward functions from comparisons, but its scalability is constrained by the high cost of oracle feedback. Lightweight v…
Towards Source-Free Machine Unlearning
Sk Miraj Ahmed, Umit Yigit Basaran, Dripta S. Raychaudhuri +5
As machine learning becomes more pervasive and data privacy regulations evolve, the ability to remove private or copyrighted information from trained models is becoming an increasi…
Robust Offline Imitation Learning from Diverse Auxiliary Data
Udita Ghosh, Dripta S. Raychaudhuri, Jiachen Li +2
Offline imitation learning enables learning a policy solely from a set of expert demonstrations, without any environment interaction. To alleviate the issue of distribution shift a…
Preference VLM: Leveraging VLMs for Scalable Preference-Based Reinforcement Learning
Udita Ghosh, Dripta S. Raychaudhuri, Jiachen Li +2
Preference-based reinforcement learning (RL) offers a promising approach for aligning policies with human intent but is often constrained by the high cost of human feedback. In thi…
STRIDE: Single-video based Temporally Continuous Occlusion-Robust 3D Pose Estimation
Rohit Lal, Saketh Bachu, Yash Garg +6
The capability to accurately estimate 3D human poses is crucial for diverse fields such as action recognition, gait recognition, and virtual/augmented reality. However, a persisten…