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cs.LG2026
FlexAct: Why Learn when you can Pick?
Ramnath Kumar, Kyle Ritscher, Junmin Judy +2
Learning activation functions has emerged as a promising direction in deep learning, allowing networks to adapt activation mechanisms to task-specific demands. In this work, we int…
cs.LG2024
EHI: End-to-end Learning of Hierarchical Index for Efficient Dense Retrieval
Ramnath Kumar, Anshul Mittal, Nilesh Gupta +3
Dense embedding-based retrieval is widely used for semantic search and ranking. However, conventional two-stage approaches, involving contrastive embedding learning followed by app…