36 citations · 247 across the 59 of their papers we have counts for
16 papers · 1 filter
Neuromotor Hierarchy Network: Physiological Inductive Biases for Robust Generalization in sEMG Decoding
He Wang, Hongyuan Qi, Zhaoxian Zhang +4
Surface electromyography (sEMG) provides a wearable, noninvasive interface to neuromuscular activity for movement decoding and human-computer interaction. Population-scale decoding…
On the effectiveness of reward functions in reinforcement learning for confidence calibration of large language models
Chee Heng Tan, Zhuoyi Lin, Mehul Motani +1
In this paper, we consider the setting where large language models (LLMs) are trained using reinforcement learning (RL) to simultaneously improve reasoning accuracy and verbalize t…
Tab-PET: Graph-Based Positional Encodings for Tabular Transformers
Yunze Leng, Rohan Ghosh, Mehul Motani
Supervised learning with tabular data presents unique challenges, including low data sizes, the absence of structural cues, and heterogeneous features spanning both categorical and…
Teaching the Teacher: The Role of Teacher-Student Smoothness Alignment in Genetic Programming-based Symbolic Distillation
Soumyadeep Dhar, Kei Sen Fong, Mehul Motani
Obtaining human-readable symbolic formulas via genetic programming-based symbolic distillation of a deep neural network trained on the target dataset presents a promising yet under…
Local Intrinsic Dimensional Entropy
Rohan Ghosh, Mehul Motani
Most entropy measures depend on the spread of the probability distribution over the sample space , and the maximum entropy achievable scales proportionately with the s…
Optimizing Learning Rate Schedules for Iterative Pruning of Deep Neural Networks
Shiyu Liu, Rohan Ghosh, John Tan Chong Min +1
The importance of learning rate (LR) schedules on network pruning has been observed in a few recent works. As an example, Frankle and Carbin (2019) highlighted that winning tickets…