3 citations · 8 across the 5 of their papers we have counts for
7 papers
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…
Loss Regularizing Robotic Terrain Classification
Shakti Deo Kumar, Sudhanshu Tripathi, Krishna Ujjwal +2
Locomotion mechanics of legged robots are suitable when pacing through difficult terrains. Recognising terrains for such robots are important to fully yoke the versatility of their…
Extended Feature Space-Based Automatic Melanoma Detection System
Shakti Kumar, Anuj Kumar
Melanoma is the deadliest form of skin cancer. Uncontrollable growth of melanocytes leads to melanoma. Melanoma has been growing wildly in the last few decades. In recent years, th…
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…
Learning Robust Latent Representations for Controllable Speech Synthesis
Shakti Kumar, Jithin Pradeep, Hussain Zaidi
State-of-the-art Variational Auto-Encoders (VAEs) for learning disentangled latent representations give impressive results in discovering features like pitch, pause duration, and a…
Adaptive Attention Span in Computer Vision
Jerrod Parker, Shakti Kumar, Joe Roussy
Recent developments in Transformers for language modeling have opened new areas of research in computer vision. Results from late 2019 showed vast performance increases in both obj…
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…