3 papers
cs.CV2025
Haphazard Inputs as Images in Online Learning
Rohit Agarwal, Aryan Dessai, Arif Ahmed Sekh +3
The field of varying feature space in online learning settings, also known as haphazard inputs, is very prominent nowadays due to its applicability in various fields. However, the…
cs.LG2024
Hedging Is Not All You Need: A Simple Baseline for Online Learning Under Haphazard Inputs
Himanshu Buckchash, Momojit Biswas, Rohit Agarwal +1
Handling haphazard streaming data, such as data from edge devices, presents a challenging problem. Over time, the incoming data becomes inconsistent, with missing, faulty, or new i…
cs.LG2024
packetLSTM: Dynamic LSTM Framework for Streaming Data with Varying Feature Space
Rohit Agarwal, Karaka Prasanth Naidu, Alexander Horsch +2
We study the online learning problem characterized by the varying input feature space of streaming data. Although LSTMs have been employed to effectively capture the temporal natur…