190 citations · 715 across the 20 of their papers we have counts for
6 papers · 1 filter
Complexity-aware Adaptive Training and Inference for Edge-Cloud Distributed AI Systems
Yinghan Long, Indranil Chakraborty, Gopalakrishnan Srinivasan +1
The ubiquitous use of IoT and machine learning applications is creating large amounts of data that require accurate and real-time processing. Although edge-based smart data process…
On the Noise Stability and Robustness of Adversarially Trained Networks on NVM Crossbars
Chun Tao, Deboleena Roy, Indranil Chakraborty +1
Applications based on Deep Neural Networks (DNNs) have grown exponentially in the past decade. To match their increasing computational needs, several Non-Volatile Memory (NVM) cros…
Conditionally Deep Hybrid Neural Networks Across Edge and Cloud
Yinghan Long, Indranil Chakraborty, Kaushik Roy
The pervasiveness of "Internet-of-Things" in our daily life has led to a recent surge in fog computing, encompassing a collaboration of cloud computing and edge intelligence. To th…
Constructing Energy-efficient Mixed-precision Neural Networks through Principal Component Analysis for Edge Intelligence
Indranil Chakraborty, Deboleena Roy, Isha Garg +2
The `Internet of Things' has brought increased demand for AI-based edge computing in applications ranging from healthcare monitoring systems to autonomous vehicles. Quantization is…
Discretization based Solutions for Secure Machine Learning against Adversarial Attacks
Priyadarshini Panda, Indranil Chakraborty, Kaushik Roy
Adversarial examples are perturbed inputs that are designed (from a deep learning network's (DLN) parameter gradients) to mislead the DLN during test time. Intuitively, constrainin…
Efficient Hybrid Network Architectures for Extremely Quantized Neural Networks Enabling Intelligence at the Edge
Indranil Chakraborty, Deboleena Roy, Aayush Ankit +1
The recent advent of `Internet of Things' (IOT) has increased the demand for enabling AI-based edge computing. This has necessitated the search for efficient implementations of neu…