4 papers · 1 filter
LP-NAS: Linear Programming-based Neural Architecture Search
Abhishek Shukla, Ankur Sinha, Faiz Hamid
Neural Architecture Search (NAS) aims to automate neural network architecture design, reducing reliance on human expertise. Among the various NAS methods, differentiable NAS has ga…
Designing Compact Neural Architectures via Neuron Gating and Mixed Activation
Abhishek Shukla, Ankur Sinha, Faiz Hamid
Neural Architecture Search (NAS) is naturally formulated as a bilevel optimization problem, where the upper-level optimizes the architecture using validation performance and the lo…
Bilevel Optimization for Neural Architecture Search
Abhishek Shukla, Ankur Sinha, Faiz Hamid
Bilevel optimization has become an influential and widely adopted framework for addressing hierarchical optimization problems in machine learning, providing an effective approach t…
LiFT: Local Search via Linear Programming for Overfitting-Controlled Transformers
Abhishek Shukla, Anikeit Khanna, Ankur Sinha +1
This paper proposes a Linear Programming (LP)-based local search framework for fine-tuning pretrained transformer models with explicit control against overfitting. The approach for…