2 citations · 2 across the 5 of their papers we have counts for
5 papers
VidModEx: Interpretable and Efficient Black Box Model Extraction for High-Dimensional Spaces
Somnath Sendhil Kumar, Yuvaraj Govindarajulu, Pavan Kulkarni +1
In the domain of black-box model extraction, conventional methods reliant on soft labels or surrogate datasets struggle with scaling to high-dimensional input spaces and managing t…
Enhancing TinyML Security: Study of Adversarial Attack Transferability
Parin Shah, Yuvaraj Govindarajulu, Pavan Kulkarni +1
The recent strides in artificial intelligence (AI) and machine learning (ML) have propelled the rise of TinyML, a paradigm enabling AI computations at the edge without dependence o…
MISLEAD: Manipulating Importance of Selected features for Learning Epsilon in Evasion Attack Deception
Vidit Khazanchi, Pavan Kulkarni, Yuvaraj Govindarajulu +1
Emerging vulnerabilities in machine learning (ML) models due to adversarial attacks raise concerns about their reliability. Specifically, evasion attacks manipulate models by intro…
On the notion of Hallucinations from the lens of Bias and Validity in Synthetic CXR Images
Gauri Bhardwaj, Yuvaraj Govindarajulu, Sundaraparipurnan Narayanan +2
Medical imaging has revolutionized disease diagnosis, yet the potential is hampered by limited access to diverse and privacy-conscious datasets. Open-source medical datasets, while…
Targeted Attacks on Timeseries Forecasting
Yuvaraj Govindarajulu, Avinash Amballa, Pavan Kulkarni +1
Real-world deep learning models developed for Time Series Forecasting are used in several critical applications ranging from medical devices to the security domain. Many previous w…