6 citations · 6 across the 3 of their papers we have counts for
8 papers
Active In-Context Learning for Tabular Foundation Models
Wilailuck Treerath, Fabrizio Pittorino
Active learning (AL) reduces labeling cost by querying informative samples, but in tabular settings its cold-start gains are often limited because uncertainty estimates are unrelia…
SQUAD: Scalable Quorum Adaptive Decisions via ensemble of early exit neural networks
Matteo Gambella, Fabrizio Pittorino, Giuliano Casale +1
Early-exit neural networks have become popular for reducing inference latency by allowing intermediate predictions when sufficient confidence is achieved. However, standard approac…
DQT: Dynamic Quantization Training via Dequantization-Free Nested Integer Arithmetic
Hazem Hesham Yousef Shalby, Fabrizio Pittorino, Francesca Palermo +2
The deployment of deep neural networks on resource-constrained devices relies on quantization. While static, uniform quantization applies a fixed bit-width to all inputs, it fails…
InfoQ: Mixed-Precision Quantization via Global Information Flow
Mehmet Emre Akbulut, Hazem Hesham Yousef Shalby, Fabrizio Pittorino +1
Mixed-precision quantization (MPQ) is crucial for deploying deep neural networks on resource-constrained devices, but finding the optimal bit-width for each layer represents a comp…
Architecture-Aware Minimization (AM): How to Find Flat Minima in Neural Architecture Search
Matteo Gambella, Fabrizio Pittorino, Manuel Roveri
Neural Architecture Search (NAS) has become an essential tool for designing effective and efficient neural networks. In this paper, we investigate the geometric properties of neura…
Quantifying Cryptocurrency Unpredictability: A Comprehensive Study of Complexity and Forecasting
Francesco Puoti, Fabrizio Pittorino, Manuel Roveri
This paper offers a thorough examination of the univariate predictability in cryptocurrency time-series. By exploiting a combination of complexity measure and model predictions we…