11 citations · 32 across the 12 of their papers we have counts for
13 papers
Latent-LoRA: Compact Latent-Space Adapters with Gradient-Free Routing for Continual Learning
Reza Rahimi Azghan, Gautham Krishna Gudur, Giulia Pedrielli +2
Large language models generalize well to individual tasks but lack an inherent mechanism for learning them sequentially, leading to catastrophic forgetting. To mitigate this, LoRA-…
Gated Adaptation for Continual Learning in Human Activity Recognition
Reza Rahimi Azghan, Gautham Krishna Gudur, Mohit Malu +4
Wearable sensors in Internet of Things (IoT) ecosystems increasingly support applications such as remote health monitoring, elderly care, and smart home automation, all of which re…
GluMind: Multimodal Parallel Attention and Knowledge Retention for Robust Cross-Population Blood Glucose Forecasting
Ebrahim Farahmand, Reza Rahimi Azghan, Nooshin Taheri Chatrudi +9
This paper proposes GluMind, a transformer-based multimodal framework designed for continual and long-term blood glucose forecasting. GluMind devises two attention mechanisms, incl…
CLAD-Net: Continual Activity Recognition in Multi-Sensor Wearable Systems
Reza Rahimi Azghan, Gautham Krishna Gudur, Mohit Malu +4
The rise of deep learning has greatly advanced human behavior monitoring using wearable sensors, particularly human activity recognition (HAR). While deep models have been widely s…
AttenGluco: Multimodal Transformer-Based Blood Glucose Forecasting on AI-READI Dataset
Ebrahim Farahmand, Reza Rahimi Azghan, Nooshin Taheri Chatrudi +6
Diabetes is a chronic metabolic disorder characterized by persistently high blood glucose levels (BGLs), leading to severe complications such as cardiovascular disease, neuropathy,…
SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors
Vijay Lingam, Atula Tejaswi, Aditya Vavre +7
Popular parameter-efficient fine-tuning (PEFT) methods, such as LoRA and its variants, freeze pre-trained model weights \(W\) and inject learnable matrices \(ΔW\). These \(ΔW\) mat…
Can Calibration Improve Sample Prioritization?
Ganesh Tata, Gautham Krishna Gudur, Gopinath Chennupati +1
Calibration can reduce overconfident predictions of deep neural networks, but can calibration also accelerate training? In this paper, we show that it can when used to prioritize s…
Zero-Shot Federated Learning with New Classes for Audio Classification
Gautham Krishna Gudur, Satheesh K. Perepu
Federated learning is an effective way of extracting insights from different user devices while preserving the privacy of users. However, new classes with completely unseen data di…
Bayesian Active Learning for Wearable Stress and Affect Detection
Abhijith Ragav, Gautham Krishna Gudur
In the recent past, psychological stress has been increasingly observed in humans, and early detection is crucial to prevent health risks. Stress detection using on-device deep lea…
Federated Learning with Heterogeneous Labels and Models for Mobile Activity Monitoring
Gautham Krishna Gudur, Satheesh K. Perepu
Various health-care applications such as assisted living, fall detection, etc., require modeling of user behavior through Human Activity Recognition (HAR). Such applications demand…
Resource-Constrained Federated Learning with Heterogeneous Labels and Models
Gautham Krishna Gudur, Bala Shyamala Balaji, Satheesh K. Perepu
Various IoT applications demand resource-constrained machine learning mechanisms for different applications such as pervasive healthcare, activity monitoring, speech recognition, r…
ActiveHARNet: Towards On-Device Deep Bayesian Active Learning for Human Activity Recognition
Gautham Krishna Gudur, Prahalathan Sundaramoorthy, Venkatesh Umaashankar
Various health-care applications such as assisted living, fall detection etc., require modeling of user behavior through Human Activity Recognition (HAR). HAR using mobile- and wea…
A Generic Multi-modal Dynamic Gesture Recognition System using Machine Learning
Gautham Krishna G, Karthik Subramanian Nathan, Yogesh Kumar B +3
Human computer interaction facilitates intelligent communication between humans and computers, in which gesture recognition plays a prominent role. This paper proposes a machine le…