5 citations · 5 across the 8 of their papers we have counts for
6 papers · 1 filter
Pitfalls of Unlabeled Disagreement-Based Drift Detection in Streaming Tree Ensembles
Lara Sá Neves, Afonso Lourenço, Lizy K. John +1
Detecting concept drift in high-speed data streams remains challenging, particularly when models must operate on unlabeled data and avoid false alarms caused by benign shifts. Whil…
From Arithmetic to Logic: The Resilience of Logic and Lookup-Based Neural Networks Under Parameter Bit-Flips
Alan T. L. Bacellar, Sathvik Chemudupati, Shashank Nag +4
The deployment of deep neural networks (DNNs) in safety-critical edge environments necessitates robustness against hardware-induced bit-flip errors. While empirical studies indicat…
LL-ViT: Edge Deployable Vision Transformers with Look Up Table Neurons
Shashank Nag, Alan T. L. Bacellar, Zachary Susskind +9
Vision Transformers have been tremendously successful in computer vision tasks. However, their large computational, memory, and energy demands are a challenge for edge inference on…
nanoML for Human Activity Recognition
Alan T. L. Bacellar, Mugdha P. Jadhao, Shashank Nag +3
Human Activity Recognition (HAR) is critical for applications in healthcare, fitness, and IoT, but deploying accurate models on resource-constrained devices remains challenging due…
Shrinking the Giant : Quasi-Weightless Transformers for Low Energy Inference
Shashank Nag, Alan T. L. Bacellar, Zachary Susskind +9
Transformers are set to become ubiquitous with applications ranging from chatbots and educational assistants to visual recognition and remote sensing. However, their increasing com…
Differentiable Weightless Neural Networks
Alan T. L. Bacellar, Zachary Susskind, Mauricio Breternitz +4
We introduce the Differentiable Weightless Neural Network (DWN), a model based on interconnected lookup tables. Training of DWNs is enabled by a novel Extended Finite Difference te…