4 papers · 1 filter
Improving Selective Classification with Pairwise Queries for Binary Classification
Harsh Vardhan, Sunav Choudhary, Natwar Modani +1
In selective classification, a model predicts the labels of data samples where it is confident, and abstains from predicting labels for samples on which it is not confident. The re…
Investigation into In-Context Learning Capabilities of Transformers
Rushil Chandrupatla, Leo Bangayan, Sebastian Leng
Transformers have demonstrated a strong ability for in-context learning (ICL), enabling models to solve previously unseen tasks using only example input output pairs provided at in…
Client Selection in Federated Learning with Data Heterogeneity and Network Latencies
Harsh Vardhan, Xiaofan Yu, Tajana Rosing +1
Federated learning (FL) is a distributed machine learning paradigm where multiple clients conduct local training based on their private data, then the updated models are sent to a…
Effectiveness of Distributed Gradient Descent with Local Steps for Overparameterized Models
Heng Zhu, Harsh Vardhan, Arya Mazumdar
In distributed training of machine learning models, gradient descent with local iterative steps, commonly known as Local (Stochastic) Gradient Descent (Local-(S)GD) or Federated av…