3 citations · 5 across the 3 of their papers we have counts for
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cs.LG2025
SIDE: Semantic ID Embedding for effective learning from sequences
Dinesh Ramasamy, Shakti Kumar, Chris Cadonic +4
Sequence-based recommendations models are driving the state-of-the-art for industrial ad-recommendation systems. Such systems typically deal with user histories or sequence lengths…
cs.LG2022★ 2 cited
GDC- Generalized Distribution Calibration for Few-Shot Learning
Shakti Kumar, Hussain Zaidi
Few shot learning is an important problem in machine learning as large labelled datasets take considerable time and effort to assemble. Most few-shot learning algorithms suffer fro…
cs.LG2020★ 3 cited
Adaptive Transformers in RL
Shakti Kumar, Jerrod Parker, Panteha Naderian
Recent developments in Transformers have opened new interesting areas of research in partially observable reinforcement learning tasks. Results from late 2019 showed that Transform…